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2405.06244
Martin N\"agele
Susanne Armbruster, Matthias Mnich, Martin N\"agele
A $(\frac32+\frac1{\mathrm{e}})$-Approximation Algorithm for Ordered TSP
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a new $(\frac32+\frac1{\mathrm{e}})$-approximation algorithm for the Ordered Traveling Salesperson Problem (Ordered TSP). Ordered TSP is a variant of the classical metric Traveling Salesperson Problem (TSP) where a specified subset of vertices needs to appear on the output Hamiltonian cycle in a given orde...
[ { "created": "Fri, 10 May 2024 04:56:07 GMT", "version": "v1" } ]
2024-05-13
[ [ "Armbruster", "Susanne", "" ], [ "Mnich", "Matthias", "" ], [ "Nägele", "Martin", "" ] ]
We present a new $(\frac32+\frac1{\mathrm{e}})$-approximation algorithm for the Ordered Traveling Salesperson Problem (Ordered TSP). Ordered TSP is a variant of the classical metric Traveling Salesperson Problem (TSP) where a specified subset of vertices needs to appear on the output Hamiltonian cycle in a given order,...
0712.3870
Bruce Hajek
Bruce Hajek
Substitute Valuations: Generation and Structure
Revision includes more background and explanations
null
10.1016/j.peva.2008.07.001
null
cs.GT cs.PF
null
Substitute valuations (in some contexts called gross substitute valuations) are prominent in combinatorial auction theory. An algorithm is given in this paper for generating a substitute valuation through Monte Carlo simulation. In addition, the geometry of the set of all substitute valuations for a fixed number of g...
[ { "created": "Sat, 22 Dec 2007 16:52:39 GMT", "version": "v1" }, { "created": "Thu, 13 Mar 2008 16:14:03 GMT", "version": "v2" }, { "created": "Mon, 19 May 2008 14:50:58 GMT", "version": "v3" } ]
2014-08-15
[ [ "Hajek", "Bruce", "" ] ]
Substitute valuations (in some contexts called gross substitute valuations) are prominent in combinatorial auction theory. An algorithm is given in this paper for generating a substitute valuation through Monte Carlo simulation. In addition, the geometry of the set of all substitute valuations for a fixed number of goo...
2209.03054
R. Teal Witter
Lisa Hellerstein, Thomas Lidbetter, R. Teal Witter
A Local Search Algorithm for the Min-Sum Submodular Cover Problem
Correct funding information
null
null
null
cs.DS
http://creativecommons.org/licenses/by/4.0/
We consider the problem of solving the Min-Sum Submodular Cover problem using local search. The Min-Sum Submodular Cover problem generalizes the NP-complete Min-Sum Set Cover problem, replacing the input set cover instance with a monotone submodular set function. A simple greedy algorithm achieves an approximation fa...
[ { "created": "Wed, 7 Sep 2022 10:34:51 GMT", "version": "v1" }, { "created": "Mon, 4 Dec 2023 15:08:10 GMT", "version": "v2" } ]
2023-12-05
[ [ "Hellerstein", "Lisa", "" ], [ "Lidbetter", "Thomas", "" ], [ "Witter", "R. Teal", "" ] ]
We consider the problem of solving the Min-Sum Submodular Cover problem using local search. The Min-Sum Submodular Cover problem generalizes the NP-complete Min-Sum Set Cover problem, replacing the input set cover instance with a monotone submodular set function. A simple greedy algorithm achieves an approximation fact...
2208.08782
Georgios Amanatidis
Georgios Amanatidis, Haris Aziz, Georgios Birmpas, Aris Filos-Ratsikas, Bo Li, Herv\'e Moulin, Alexandros A. Voudouris, Xiaowei Wu
Fair Division of Indivisible Goods: Recent Progress and Open Questions
This survey unifies and extends preliminary versions that appeared in IJCAI 2022 (arXiv:2202.07551) and SIGecom Exchanges (arXiv:2202.08713). It has been accepted for publication to the journal of Artificial Intelligence (AIJ)
null
10.1016/j.artint.2023.103965
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Allocating resources to individuals in a fair manner has been a topic of interest since ancient times, with most of the early mathematical work on the problem focusing on resources that are infinitely divisible. Over the last decade, there has been a surge of papers studying computational questions regarding the indi...
[ { "created": "Thu, 18 Aug 2022 11:32:14 GMT", "version": "v1" }, { "created": "Wed, 21 Jun 2023 15:44:21 GMT", "version": "v2" } ]
2023-06-22
[ [ "Amanatidis", "Georgios", "" ], [ "Aziz", "Haris", "" ], [ "Birmpas", "Georgios", "" ], [ "Filos-Ratsikas", "Aris", "" ], [ "Li", "Bo", "" ], [ "Moulin", "Hervé", "" ], [ "Voudouris", "Alexandros A.", "" ...
Allocating resources to individuals in a fair manner has been a topic of interest since ancient times, with most of the early mathematical work on the problem focusing on resources that are infinitely divisible. Over the last decade, there has been a surge of papers studying computational questions regarding the indivi...
2407.11494
Guowei Xu
Guowei Xu, Jiale Tao, Wen Li and Lixin Duan
Learning Semantic Latent Directions for Accurate and Controllable Human Motion Prediction
Accepted to ECCV 2024
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the realm of stochastic human motion prediction (SHMP), researchers have often turned to generative models like GANS, VAEs and diffusion models. However, most previous approaches have struggled to accurately predict motions that are both realistic and coherent with past motion due to a lack of guidance on the late...
[ { "created": "Tue, 16 Jul 2024 08:31:59 GMT", "version": "v1" } ]
2024-07-17
[ [ "Xu", "Guowei", "" ], [ "Tao", "Jiale", "" ], [ "Li", "Wen", "" ], [ "Duan", "Lixin", "" ] ]
In the realm of stochastic human motion prediction (SHMP), researchers have often turned to generative models like GANS, VAEs and diffusion models. However, most previous approaches have struggled to accurately predict motions that are both realistic and coherent with past motion due to a lack of guidance on the latent...
2302.05536
Ze Shi Li
Ze Shi Li, Nowshin Nawar Arony, Kezia Devathasan, Daniela Damian
"Software is the easy part of Software Engineering" -- Lessons and Experiences from A Large-Scale, Multi-Team Capstone Course
2023 IEEE/ACM 45th International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET)
null
null
null
cs.SE
http://creativecommons.org/licenses/by/4.0/
Capstone courses in undergraduate software engineering are a critical final milestone for students. These courses allow students to create a software solution and demonstrate the knowledge they accumulated in their degrees. However, a typical capstone project team is small containing no more than 5 students and funct...
[ { "created": "Fri, 10 Feb 2023 22:33:35 GMT", "version": "v1" } ]
2023-02-14
[ [ "Li", "Ze Shi", "" ], [ "Arony", "Nowshin Nawar", "" ], [ "Devathasan", "Kezia", "" ], [ "Damian", "Daniela", "" ] ]
Capstone courses in undergraduate software engineering are a critical final milestone for students. These courses allow students to create a software solution and demonstrate the knowledge they accumulated in their degrees. However, a typical capstone project team is small containing no more than 5 students and functio...
1603.09434
Ibrahim AlShourbaji H
Ibrahim AlShourbaji, Samaher Al-Janabi and Ahmed Patel
Document Selection in a Distributed Search Engine Architecture
8 pages, 6 figures in Middle-East Journal of Scientific Research, IDOSI Publications, 2015
null
10.5829/idosi.mejsr.2015.23.07.22398
null
cs.IR cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Distributed Search Engine Architecture (DSEA) hosts numerous independent topic-specific search engines and selects a subset of the databases to search within the architecture. The objective of this approach is to reduce the amount of space needed to perform a search by querying only a subset of the total data availab...
[ { "created": "Thu, 31 Mar 2016 01:19:21 GMT", "version": "v1" } ]
2016-04-01
[ [ "AlShourbaji", "Ibrahim", "" ], [ "Al-Janabi", "Samaher", "" ], [ "Patel", "Ahmed", "" ] ]
Distributed Search Engine Architecture (DSEA) hosts numerous independent topic-specific search engines and selects a subset of the databases to search within the architecture. The objective of this approach is to reduce the amount of space needed to perform a search by querying only a subset of the total data available...
1604.08242
George Saon
George Saon, Tom Sercu, Steven Rennie and Hong-Kwang J. Kuo
The IBM 2016 English Conversational Telephone Speech Recognition System
Submitted to Interspeech 2016
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We describe a collection of acoustic and language modeling techniques that lowered the word error rate of our English conversational telephone LVCSR system to a record 6.6% on the Switchboard subset of the Hub5 2000 evaluation testset. On the acoustic side, we use a score fusion of three strong models: recurrent nets...
[ { "created": "Wed, 27 Apr 2016 21:00:03 GMT", "version": "v1" }, { "created": "Wed, 22 Jun 2016 16:30:37 GMT", "version": "v2" } ]
2016-06-23
[ [ "Saon", "George", "" ], [ "Sercu", "Tom", "" ], [ "Rennie", "Steven", "" ], [ "Kuo", "Hong-Kwang J.", "" ] ]
We describe a collection of acoustic and language modeling techniques that lowered the word error rate of our English conversational telephone LVCSR system to a record 6.6% on the Switchboard subset of the Hub5 2000 evaluation testset. On the acoustic side, we use a score fusion of three strong models: recurrent nets w...
2112.03502
Yufan Zhou
Yufan Zhou, Chunyuan Li, Changyou Chen, Jinhui Xu
A Generic Approach for Enhancing GANs by Regularized Latent Optimization
null
null
null
null
cs.LG cs.CV
http://creativecommons.org/licenses/by/4.0/
With the rapidly growing model complexity and data volume, training deep generative models (DGMs) for better performance has becoming an increasingly more important challenge. Previous research on this problem has mainly focused on improving DGMs by either introducing new objective functions or designing more express...
[ { "created": "Tue, 7 Dec 2021 05:22:50 GMT", "version": "v1" } ]
2021-12-08
[ [ "Zhou", "Yufan", "" ], [ "Li", "Chunyuan", "" ], [ "Chen", "Changyou", "" ], [ "Xu", "Jinhui", "" ] ]
With the rapidly growing model complexity and data volume, training deep generative models (DGMs) for better performance has becoming an increasingly more important challenge. Previous research on this problem has mainly focused on improving DGMs by either introducing new objective functions or designing more expressiv...
2310.08298
Shuhui Wu
Shuhui Wu, Yongliang Shen, Zeqi Tan, Wenqi Ren, Jietian Guo, Shiliang Pu, Weiming Lu
MProto: Multi-Prototype Network with Denoised Optimal Transport for Distantly Supervised Named Entity Recognition
Accepted to EMNLP-2023, camera ready version
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Distantly supervised named entity recognition (DS-NER) aims to locate entity mentions and classify their types with only knowledge bases or gazetteers and unlabeled corpus. However, distant annotations are noisy and degrade the performance of NER models. In this paper, we propose a noise-robust prototype network name...
[ { "created": "Thu, 12 Oct 2023 13:02:34 GMT", "version": "v1" } ]
2023-10-13
[ [ "Wu", "Shuhui", "" ], [ "Shen", "Yongliang", "" ], [ "Tan", "Zeqi", "" ], [ "Ren", "Wenqi", "" ], [ "Guo", "Jietian", "" ], [ "Pu", "Shiliang", "" ], [ "Lu", "Weiming", "" ] ]
Distantly supervised named entity recognition (DS-NER) aims to locate entity mentions and classify their types with only knowledge bases or gazetteers and unlabeled corpus. However, distant annotations are noisy and degrade the performance of NER models. In this paper, we propose a noise-robust prototype network named ...
2210.05492
Noam Brown
Anton Bakhtin, David J Wu, Adam Lerer, Jonathan Gray, Athul Paul Jacob, Gabriele Farina, Alexander H Miller, Noam Brown
Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning
null
null
null
null
cs.GT cs.AI cs.LG cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
No-press Diplomacy is a complex strategy game involving both cooperation and competition that has served as a benchmark for multi-agent AI research. While self-play reinforcement learning has resulted in numerous successes in purely adversarial games like chess, Go, and poker, self-play alone is insufficient for achi...
[ { "created": "Tue, 11 Oct 2022 14:47:35 GMT", "version": "v1" } ]
2022-10-12
[ [ "Bakhtin", "Anton", "" ], [ "Wu", "David J", "" ], [ "Lerer", "Adam", "" ], [ "Gray", "Jonathan", "" ], [ "Jacob", "Athul Paul", "" ], [ "Farina", "Gabriele", "" ], [ "Miller", "Alexander H", "" ], [ ...
No-press Diplomacy is a complex strategy game involving both cooperation and competition that has served as a benchmark for multi-agent AI research. While self-play reinforcement learning has resulted in numerous successes in purely adversarial games like chess, Go, and poker, self-play alone is insufficient for achiev...
1904.03693
Carlos Mastalli
Carlos Mastalli, Ioannis Havoutis, Alexander W. Winkler, Darwin G. Caldwell and Claudio Semini
On-line and on-board planning and perception for quadrupedal locomotion
7 pages, International Conference on Technologies for Practical Robot Applications
published 2015
10.1109/TePRA.2015.7219685
null
cs.RO cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a legged motion planning approach for quadrupedal locomotion over challenging terrain. We decompose the problem into body action planning and footstep planning. We use a lattice representation together with a set of defined body movement primitives for computing a body action plan. The lattice representati...
[ { "created": "Sun, 7 Apr 2019 17:27:14 GMT", "version": "v1" } ]
2019-04-09
[ [ "Mastalli", "Carlos", "" ], [ "Havoutis", "Ioannis", "" ], [ "Winkler", "Alexander W.", "" ], [ "Caldwell", "Darwin G.", "" ], [ "Semini", "Claudio", "" ] ]
We present a legged motion planning approach for quadrupedal locomotion over challenging terrain. We decompose the problem into body action planning and footstep planning. We use a lattice representation together with a set of defined body movement primitives for computing a body action plan. The lattice representation...
1307.6328
Md. Maklachur Rahman
Mohammad Ibrahim Khan, Md. Maklachur Rahman and Md. Iqbal Hasan Sarker
Digital Watermarking for Image AuthenticationBased on Combined DCT, DWT and SVD Transformation
8 pages, 7 figures and 2 tables
IJCSI International Journal of Computer Science Issues, Vol. 10, Issue 3, No 1, May 2013
null
null
cs.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a hybrid digital image watermarking based on Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD) in a zigzag order. From DWT we choose the high band to embed the watermark that facilities to add more information, gives more invisibility and robu...
[ { "created": "Wed, 24 Jul 2013 08:32:38 GMT", "version": "v1" } ]
2013-07-25
[ [ "Khan", "Mohammad Ibrahim", "" ], [ "Rahman", "Md. Maklachur", "" ], [ "Sarker", "Md. Iqbal Hasan", "" ] ]
This paper presents a hybrid digital image watermarking based on Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD) in a zigzag order. From DWT we choose the high band to embed the watermark that facilities to add more information, gives more invisibility and robust...
2304.03896
Kosta Dakic
Kosta Dakic, Bassel Al Homssi, Sumeet Walia, Akram Al-Hourani
Spiking Neural Networks for Detecting Satellite-Based Internet-of-Things Signals
null
null
null
null
cs.IT eess.SP math.IT
http://creativecommons.org/licenses/by/4.0/
With the rapid growth of IoT networks, ubiquitous coverage is becoming increasingly necessary. Low Earth Orbit (LEO) satellite constellations for IoT have been proposed to provide coverage to regions where terrestrial systems cannot. However, LEO constellations for uplink communications are severely limited by the hi...
[ { "created": "Sat, 8 Apr 2023 03:13:18 GMT", "version": "v1" } ]
2023-04-11
[ [ "Dakic", "Kosta", "" ], [ "Homssi", "Bassel Al", "" ], [ "Walia", "Sumeet", "" ], [ "Al-Hourani", "Akram", "" ] ]
With the rapid growth of IoT networks, ubiquitous coverage is becoming increasingly necessary. Low Earth Orbit (LEO) satellite constellations for IoT have been proposed to provide coverage to regions where terrestrial systems cannot. However, LEO constellations for uplink communications are severely limited by the high...
2003.00246
M. A. Teeti
M. A. Teeti
Downlink Secrecy Rate of One-Bit Massive MIMO System with Active Eavesdropping
49 pages (onecolumn), 12 figures (Available in IEEE ACCESS(early access): https://ieeexplore.ieee.org/document/9006840)
null
10.1109/ACCESS.2020.2975540
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this study, we consider the physical layer security in the downlink of a Massive MIMO system employing one-bit quantization at the base station (BS). We assume an active eavesdropper that attempts to spoiling the channel estimation acquisition at the BS for a legitimate user, whereas overhearing on downlink transm...
[ { "created": "Sat, 29 Feb 2020 11:56:03 GMT", "version": "v1" } ]
2020-03-03
[ [ "Teeti", "M. A.", "" ] ]
In this study, we consider the physical layer security in the downlink of a Massive MIMO system employing one-bit quantization at the base station (BS). We assume an active eavesdropper that attempts to spoiling the channel estimation acquisition at the BS for a legitimate user, whereas overhearing on downlink transmis...
2304.07186
Magdalena Fuentes
Lucas S. Maia, Mart\'in Rocamora, Luiz W. P. Biscainho, Magdalena Fuentes
Adapting Meter Tracking Models to Latin American Music
Accepted at ISMIR 2022. This version was made after a bug fix in the code, which lead to minor modifications in the results (updated in Figure 1 and Table 1). The paper's conclusions remain unchanged
null
null
null
cs.SD eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Beat and downbeat tracking models have improved significantly in recent years with the introduction of deep learning methods. However, despite these improvements, several challenges remain. Particularly, the adaptation of available models to underrepresented music traditions in MIR is usually synonymous with collecti...
[ { "created": "Fri, 14 Apr 2023 14:57:40 GMT", "version": "v1" } ]
2023-04-17
[ [ "Maia", "Lucas S.", "" ], [ "Rocamora", "Martín", "" ], [ "Biscainho", "Luiz W. P.", "" ], [ "Fuentes", "Magdalena", "" ] ]
Beat and downbeat tracking models have improved significantly in recent years with the introduction of deep learning methods. However, despite these improvements, several challenges remain. Particularly, the adaptation of available models to underrepresented music traditions in MIR is usually synonymous with collecting...
2210.05063
Maryam Khademi
Berk Iskender, Zhenlin Xu, Simon Kornblith, En-Hung Chu, Maryam Khademi
Improving Dense Contrastive Learning with Dense Negative Pairs
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many contrastive representation learning methods learn a single global representation of an entire image. However, dense contrastive representation learning methods such as DenseCL (Wang et al., 2021) can learn better representations for tasks requiring stronger spatial localization of features, such as multi-label c...
[ { "created": "Tue, 11 Oct 2022 00:26:59 GMT", "version": "v1" }, { "created": "Tue, 10 Jan 2023 23:47:45 GMT", "version": "v2" } ]
2023-01-12
[ [ "Iskender", "Berk", "" ], [ "Xu", "Zhenlin", "" ], [ "Kornblith", "Simon", "" ], [ "Chu", "En-Hung", "" ], [ "Khademi", "Maryam", "" ] ]
Many contrastive representation learning methods learn a single global representation of an entire image. However, dense contrastive representation learning methods such as DenseCL (Wang et al., 2021) can learn better representations for tasks requiring stronger spatial localization of features, such as multi-label cla...
2311.03426
Farnoosh Javadi
Farnoosh Javadi, Walid Ahmed, Habib Hajimolahoseini, Foozhan Ataiefard, Mohammad Hassanpour, Saina Asani, Austin Wen, Omar Mohamed Awad, Kangling Liu, Yang Liu
GQKVA: Efficient Pre-training of Transformers by Grouping Queries, Keys, and Values
null
null
null
null
cs.LG cs.AI cs.CV
http://creativecommons.org/licenses/by/4.0/
Massive transformer-based models face several challenges, including slow and computationally intensive pre-training and over-parametrization. This paper addresses these challenges by proposing a versatile method called GQKVA, which generalizes query, key, and value grouping techniques. GQKVA is designed to speed up t...
[ { "created": "Mon, 6 Nov 2023 17:29:24 GMT", "version": "v1" }, { "created": "Wed, 13 Dec 2023 16:57:19 GMT", "version": "v2" } ]
2023-12-14
[ [ "Javadi", "Farnoosh", "" ], [ "Ahmed", "Walid", "" ], [ "Hajimolahoseini", "Habib", "" ], [ "Ataiefard", "Foozhan", "" ], [ "Hassanpour", "Mohammad", "" ], [ "Asani", "Saina", "" ], [ "Wen", "Austin", "" ...
Massive transformer-based models face several challenges, including slow and computationally intensive pre-training and over-parametrization. This paper addresses these challenges by proposing a versatile method called GQKVA, which generalizes query, key, and value grouping techniques. GQKVA is designed to speed up tra...
2407.07541
Kirill Paramonov
Kirill Paramonov, Jia-Xing Zhong, Umberto Michieli, Jijoong Moon, Mete Ozay
Swiss DINO: Efficient and Versatile Vision Framework for On-device Personal Object Search
8 pages, 2 figures, accepted to IROS2024
null
null
null
cs.CV cs.AI cs.RO
http://creativecommons.org/licenses/by-nc-sa/4.0/
In this paper, we address a recent trend in robotic home appliances to include vision systems on personal devices, capable of personalizing the appliances on the fly. In particular, we formulate and address an important technical task of personal object search, which involves localization and identification of person...
[ { "created": "Wed, 10 Jul 2024 11:05:02 GMT", "version": "v1" } ]
2024-07-11
[ [ "Paramonov", "Kirill", "" ], [ "Zhong", "Jia-Xing", "" ], [ "Michieli", "Umberto", "" ], [ "Moon", "Jijoong", "" ], [ "Ozay", "Mete", "" ] ]
In this paper, we address a recent trend in robotic home appliances to include vision systems on personal devices, capable of personalizing the appliances on the fly. In particular, we formulate and address an important technical task of personal object search, which involves localization and identification of personal...
2311.03228
Ekapol Chuangsuwanich
Peerat Limkonchotiwat, Wuttikorn Ponwitayarat, Lalita Lowphansirikul, Can Udomcharoenchaikit, Ekapol Chuangsuwanich, Sarana Nutanong
An Efficient Self-Supervised Cross-View Training For Sentence Embedding
Accepted to TACL. The code and pre-trained models are available at https://github.com/mrpeerat/SCT
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Self-supervised sentence representation learning is the task of constructing an embedding space for sentences without relying on human annotation efforts. One straightforward approach is to finetune a pretrained language model (PLM) with a representation learning method such as contrastive learning. While this approa...
[ { "created": "Mon, 6 Nov 2023 16:12:25 GMT", "version": "v1" } ]
2023-11-07
[ [ "Limkonchotiwat", "Peerat", "" ], [ "Ponwitayarat", "Wuttikorn", "" ], [ "Lowphansirikul", "Lalita", "" ], [ "Udomcharoenchaikit", "Can", "" ], [ "Chuangsuwanich", "Ekapol", "" ], [ "Nutanong", "Sarana", "" ] ]
Self-supervised sentence representation learning is the task of constructing an embedding space for sentences without relying on human annotation efforts. One straightforward approach is to finetune a pretrained language model (PLM) with a representation learning method such as contrastive learning. While this approach...
1503.02330
Patrik Huber
Patrik Huber, Zhen-Hua Feng, William Christmas, Josef Kittler, Matthias R\"atsch
Fitting 3D Morphable Models using Local Features
Submitted to ICIP 2015; 4 pages, 4 figures
Proceedings of the IEEE International Conference on Image Processing (ICIP) 2015, pages 1195-1199
10.1109/ICIP.2015.7350989
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a novel fitting method that uses local image features to fit a 3D Morphable Model to 2D images. To overcome the obstacle of optimising a cost function that contains a non-differentiable feature extraction operator, we use a learning-based cascaded regression method that learns the gradient d...
[ { "created": "Sun, 8 Mar 2015 21:57:49 GMT", "version": "v1" } ]
2016-05-13
[ [ "Huber", "Patrik", "" ], [ "Feng", "Zhen-Hua", "" ], [ "Christmas", "William", "" ], [ "Kittler", "Josef", "" ], [ "Rätsch", "Matthias", "" ] ]
In this paper, we propose a novel fitting method that uses local image features to fit a 3D Morphable Model to 2D images. To overcome the obstacle of optimising a cost function that contains a non-differentiable feature extraction operator, we use a learning-based cascaded regression method that learns the gradient dir...
2004.04877
Nathaniel Weir
Nathaniel Weir, Adam Poliak, Benjamin Van Durme
Probing Neural Language Models for Human Tacit Assumptions
To be published in CogSci 2020
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Humans carry stereotypic tacit assumptions (STAs) (Prince, 1978), or propositional beliefs about generic concepts. Such associations are crucial for understanding natural language. We construct a diagnostic set of word prediction prompts to evaluate whether recent neural contextualized language models trained on larg...
[ { "created": "Fri, 10 Apr 2020 01:48:50 GMT", "version": "v1" }, { "created": "Tue, 16 Jun 2020 15:55:51 GMT", "version": "v2" } ]
2020-06-17
[ [ "Weir", "Nathaniel", "" ], [ "Poliak", "Adam", "" ], [ "Van Durme", "Benjamin", "" ] ]
Humans carry stereotypic tacit assumptions (STAs) (Prince, 1978), or propositional beliefs about generic concepts. Such associations are crucial for understanding natural language. We construct a diagnostic set of word prediction prompts to evaluate whether recent neural contextualized language models trained on large ...
2407.05067
Richard Hlad\'ik
Richard Hlad\'ik, Jakub T\v{e}tek
Smooth Sensitivity Revisited: Towards Optimality
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Smooth sensitivity is one of the most commonly used techniques for designing practical differentially private mechanisms. In this approach, one computes the smooth sensitivity of a given query $q$ on the given input $D$ and releases $q(D)$ with noise added proportional to this smooth sensitivity. One question remains...
[ { "created": "Sat, 6 Jul 2024 13:09:36 GMT", "version": "v1" } ]
2024-07-09
[ [ "Hladík", "Richard", "" ], [ "Tětek", "Jakub", "" ] ]
Smooth sensitivity is one of the most commonly used techniques for designing practical differentially private mechanisms. In this approach, one computes the smooth sensitivity of a given query $q$ on the given input $D$ and releases $q(D)$ with noise added proportional to this smooth sensitivity. One question remains: ...
1810.06807
Kartik Hegde
Kartik Hegde, Rohit Agrawal, Yulun Yao, Christopher W. Fletcher
Morph: Flexible Acceleration for 3D CNN-based Video Understanding
Appears in the proceedings of the 51st Annual IEEE/ACM International Symposium on Microarchitecture (MICRO), 2018
null
null
null
cs.LG cs.AR cs.NE stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The past several years have seen both an explosion in the use of Convolutional Neural Networks (CNNs) and the design of accelerators to make CNN inference practical. In the architecture community, the lion share of effort has targeted CNN inference for image recognition. The closely related problem of video recogniti...
[ { "created": "Tue, 16 Oct 2018 04:49:15 GMT", "version": "v1" } ]
2018-10-17
[ [ "Hegde", "Kartik", "" ], [ "Agrawal", "Rohit", "" ], [ "Yao", "Yulun", "" ], [ "Fletcher", "Christopher W.", "" ] ]
The past several years have seen both an explosion in the use of Convolutional Neural Networks (CNNs) and the design of accelerators to make CNN inference practical. In the architecture community, the lion share of effort has targeted CNN inference for image recognition. The closely related problem of video recognition...
2106.00339
Zhenhao Li
Zhenhao Li, Tse-Hsun (Peter) Chen, Jinqiu Yang, Weiyi Shang
Studying Duplicate Logging Statements and Their Relationships with Code Clones
Accepted at IEEE Transactions on Software Engineering
null
10.1109/TSE.2021.3060918
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we focus on studying duplicate logging statements, which are logging statements that have the same static text message. We manually studied over 4K duplicate logging statements and their surrounding code in five large-scale open source systems. We uncovered five patterns of duplicate logging code smell...
[ { "created": "Tue, 1 Jun 2021 09:19:43 GMT", "version": "v1" } ]
2021-06-02
[ [ "Li", "Zhenhao", "", "Peter" ], [ "Tse-Hsun", "", "", "Peter" ], [ "Chen", "", "" ], [ "Yang", "Jinqiu", "" ], [ "Shang", "Weiyi", "" ] ]
In this paper, we focus on studying duplicate logging statements, which are logging statements that have the same static text message. We manually studied over 4K duplicate logging statements and their surrounding code in five large-scale open source systems. We uncovered five patterns of duplicate logging code smells....
2403.06772
Han Gao
Philippe Balbiani, Han Gao, \c{C}i\u{g}dem Gencer, Nicola Olivetti
Local Intuitionistic Modal Logics and Their Calculi
null
null
null
null
cs.LO
http://creativecommons.org/licenses/by/4.0/
We investigate intuitionistic modal logics with locally interpreted $\square$ and $\lozenge$. The basic logic LIK is stronger than constructive modal logic WK and incomparable with intuitionistic modal logic IK. We propose an axiomatization of LIK and some of its extensions. We propose bi-nested calculi for LIK and t...
[ { "created": "Mon, 11 Mar 2024 14:39:51 GMT", "version": "v1" } ]
2024-03-12
[ [ "Balbiani", "Philippe", "" ], [ "Gao", "Han", "" ], [ "Gencer", "Çiğdem", "" ], [ "Olivetti", "Nicola", "" ] ]
We investigate intuitionistic modal logics with locally interpreted $\square$ and $\lozenge$. The basic logic LIK is stronger than constructive modal logic WK and incomparable with intuitionistic modal logic IK. We propose an axiomatization of LIK and some of its extensions. We propose bi-nested calculi for LIK and the...
2008.12760
Roozbeh Mottaghi
Luca Weihs, Jordi Salvador, Klemen Kotar, Unnat Jain, Kuo-Hao Zeng, Roozbeh Mottaghi, Aniruddha Kembhavi
AllenAct: A Framework for Embodied AI Research
null
null
null
null
cs.CV cs.AI cs.LG cs.MA cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The domain of Embodied AI, in which agents learn to complete tasks through interaction with their environment from egocentric observations, has experienced substantial growth with the advent of deep reinforcement learning and increased interest from the computer vision, NLP, and robotics communities. This growth has ...
[ { "created": "Fri, 28 Aug 2020 17:35:22 GMT", "version": "v1" } ]
2020-08-31
[ [ "Weihs", "Luca", "" ], [ "Salvador", "Jordi", "" ], [ "Kotar", "Klemen", "" ], [ "Jain", "Unnat", "" ], [ "Zeng", "Kuo-Hao", "" ], [ "Mottaghi", "Roozbeh", "" ], [ "Kembhavi", "Aniruddha", "" ] ]
The domain of Embodied AI, in which agents learn to complete tasks through interaction with their environment from egocentric observations, has experienced substantial growth with the advent of deep reinforcement learning and increased interest from the computer vision, NLP, and robotics communities. This growth has be...
2310.06260
Arthur dos Santos
Arthur dos Santos, Jayr Pereira, Rodrigo Nogueira, Bruno Masiero, Shiva Sander-Tavallaey, Elias Zea
An experiment on an automated literature survey of data-driven speech enhancement methods
null
null
null
null
cs.SD cs.CL eess.AS
http://creativecommons.org/licenses/by/4.0/
The increasing number of scientific publications in acoustics, in general, presents difficulties in conducting traditional literature surveys. This work explores the use of a generative pre-trained transformer (GPT) model to automate a literature survey of 116 articles on data-driven speech enhancement methods. The m...
[ { "created": "Tue, 10 Oct 2023 02:07:24 GMT", "version": "v1" } ]
2023-10-11
[ [ "Santos", "Arthur dos", "" ], [ "Pereira", "Jayr", "" ], [ "Nogueira", "Rodrigo", "" ], [ "Masiero", "Bruno", "" ], [ "Sander-Tavallaey", "Shiva", "" ], [ "Zea", "Elias", "" ] ]
The increasing number of scientific publications in acoustics, in general, presents difficulties in conducting traditional literature surveys. This work explores the use of a generative pre-trained transformer (GPT) model to automate a literature survey of 116 articles on data-driven speech enhancement methods. The mai...
2311.14505
Viktoriia Naboka-Krell
Victor Bystrov, Viktoriia Naboka-Krell, Anna Staszewska-Bystrova, Peter Winker
Analysing the Impact of Removing Infrequent Words on Topic Quality in LDA Models
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
An initial procedure in text-as-data applications is text preprocessing. One of the typical steps, which can substantially facilitate computations, consists in removing infrequent words believed to provide limited information about the corpus. Despite popularity of vocabulary pruning, not many guidelines on how to im...
[ { "created": "Fri, 24 Nov 2023 14:20:12 GMT", "version": "v1" } ]
2023-11-27
[ [ "Bystrov", "Victor", "" ], [ "Naboka-Krell", "Viktoriia", "" ], [ "Staszewska-Bystrova", "Anna", "" ], [ "Winker", "Peter", "" ] ]
An initial procedure in text-as-data applications is text preprocessing. One of the typical steps, which can substantially facilitate computations, consists in removing infrequent words believed to provide limited information about the corpus. Despite popularity of vocabulary pruning, not many guidelines on how to impl...
2211.15457
Sahand Rezaei-Shoshtari Mr.
Sahand Rezaei-Shoshtari, Charlotte Morissette, Francois Robert Hogan, Gregory Dudek, David Meger
Hypernetworks for Zero-shot Transfer in Reinforcement Learning
AAAI 2023
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, hypernetworks are trained to generate behaviors across a range of unseen task conditions, via a novel TD-based training objective and data from a set of near-optimal RL solutions for training tasks. This work relates to meta RL, contextual RL, and transfer learning, with a particular focus on zero-shot...
[ { "created": "Mon, 28 Nov 2022 15:48:35 GMT", "version": "v1" }, { "created": "Mon, 2 Jan 2023 20:14:02 GMT", "version": "v2" } ]
2023-01-04
[ [ "Rezaei-Shoshtari", "Sahand", "" ], [ "Morissette", "Charlotte", "" ], [ "Hogan", "Francois Robert", "" ], [ "Dudek", "Gregory", "" ], [ "Meger", "David", "" ] ]
In this paper, hypernetworks are trained to generate behaviors across a range of unseen task conditions, via a novel TD-based training objective and data from a set of near-optimal RL solutions for training tasks. This work relates to meta RL, contextual RL, and transfer learning, with a particular focus on zero-shot p...
1903.07137
Wenlin Wang
Wenlin Wang, Zhe Gan, Hongteng Xu, Ruiyi Zhang, Guoyin Wang, Dinghan Shen, Changyou Chen, Lawrence Carin
Topic-Guided Variational Autoencoders for Text Generation
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a topic-guided variational autoencoder (TGVAE) model for text generation. Distinct from existing variational autoencoder (VAE) based approaches, which assume a simple Gaussian prior for the latent code, our model specifies the prior as a Gaussian mixture model (GMM) parametrized by a neural topic module. E...
[ { "created": "Sun, 17 Mar 2019 17:42:29 GMT", "version": "v1" } ]
2019-03-19
[ [ "Wang", "Wenlin", "" ], [ "Gan", "Zhe", "" ], [ "Xu", "Hongteng", "" ], [ "Zhang", "Ruiyi", "" ], [ "Wang", "Guoyin", "" ], [ "Shen", "Dinghan", "" ], [ "Chen", "Changyou", "" ], [ "Carin", "Law...
We propose a topic-guided variational autoencoder (TGVAE) model for text generation. Distinct from existing variational autoencoder (VAE) based approaches, which assume a simple Gaussian prior for the latent code, our model specifies the prior as a Gaussian mixture model (GMM) parametrized by a neural topic module. Eac...
2109.08307
Yining Huang
Yining Huang, Shaoze Lin, Yijun Wei, Keke Tang
Sinoledge: A Knowledge Engine based on Logical Reasoning and Distributed Micro Services
null
null
null
null
cs.AI cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a knowledge engine called Sinoledge mainly for doctors, physicians, and researchers in medical field to organize thoughts, manage reasoning process, test and deploy to production environments effortlessly. Our proposal can be related to rule engine usually used in business or medical fields. More important...
[ { "created": "Sun, 29 Aug 2021 08:09:53 GMT", "version": "v1" } ]
2021-09-21
[ [ "Huang", "Yining", "" ], [ "Lin", "Shaoze", "" ], [ "Wei", "Yijun", "" ], [ "Tang", "Keke", "" ] ]
We propose a knowledge engine called Sinoledge mainly for doctors, physicians, and researchers in medical field to organize thoughts, manage reasoning process, test and deploy to production environments effortlessly. Our proposal can be related to rule engine usually used in business or medical fields. More importantly...
2011.05632
Ashwin Balakrishna
Michael Danielczuk, Ashwin Balakrishna, Daniel S. Brown, Shivin Devgon, Ken Goldberg
Exploratory Grasping: Asymptotically Optimal Algorithms for Grasping Challenging Polyhedral Objects
Conference on Robot Learning (CoRL) 2020. First two authors contributed equally
null
null
null
cs.RO cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
There has been significant recent work on data-driven algorithms for learning general-purpose grasping policies. However, these policies can consistently fail to grasp challenging objects which are significantly out of the distribution of objects in the training data or which have very few high quality grasps. Motiva...
[ { "created": "Wed, 11 Nov 2020 08:42:30 GMT", "version": "v1" }, { "created": "Thu, 12 Nov 2020 01:21:35 GMT", "version": "v2" } ]
2020-11-13
[ [ "Danielczuk", "Michael", "" ], [ "Balakrishna", "Ashwin", "" ], [ "Brown", "Daniel S.", "" ], [ "Devgon", "Shivin", "" ], [ "Goldberg", "Ken", "" ] ]
There has been significant recent work on data-driven algorithms for learning general-purpose grasping policies. However, these policies can consistently fail to grasp challenging objects which are significantly out of the distribution of objects in the training data or which have very few high quality grasps. Motivate...
1509.06418
Varun Jog
Varun Jog and Po-Ling Loh
Information-theoretic bounds for exact recovery in weighted stochastic block models using the Renyi divergence
32 pages
null
null
null
cs.IT cs.SI math.IT math.ST stat.TH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We derive sharp thresholds for exact recovery of communities in a weighted stochastic block model, where observations are collected in the form of a weighted adjacency matrix, and the weight of each edge is generated independently from a distribution determined by the community membership of its endpoints. Our main r...
[ { "created": "Mon, 21 Sep 2015 22:26:14 GMT", "version": "v1" } ]
2015-09-23
[ [ "Jog", "Varun", "" ], [ "Loh", "Po-Ling", "" ] ]
We derive sharp thresholds for exact recovery of communities in a weighted stochastic block model, where observations are collected in the form of a weighted adjacency matrix, and the weight of each edge is generated independently from a distribution determined by the community membership of its endpoints. Our main res...
2405.17708
Allen Nie
Allen Nie, Yash Chandak, Christina J. Yuan, Anirudhan Badrinath, Yannis Flet-Berliac, Emma Brunskil
OPERA: Automatic Offline Policy Evaluation with Re-weighted Aggregates of Multiple Estimators
22 pages
null
null
null
cs.LG cs.AI stat.ML
http://creativecommons.org/licenses/by/4.0/
Offline policy evaluation (OPE) allows us to evaluate and estimate a new sequential decision-making policy's performance by leveraging historical interaction data collected from other policies. Evaluating a new policy online without a confident estimate of its performance can lead to costly, unsafe, or hazardous outc...
[ { "created": "Mon, 27 May 2024 23:51:20 GMT", "version": "v1" } ]
2024-05-29
[ [ "Nie", "Allen", "" ], [ "Chandak", "Yash", "" ], [ "Yuan", "Christina J.", "" ], [ "Badrinath", "Anirudhan", "" ], [ "Flet-Berliac", "Yannis", "" ], [ "Brunskil", "Emma", "" ] ]
Offline policy evaluation (OPE) allows us to evaluate and estimate a new sequential decision-making policy's performance by leveraging historical interaction data collected from other policies. Evaluating a new policy online without a confident estimate of its performance can lead to costly, unsafe, or hazardous outcom...
2304.14050
Yulong Huang
Yulong Huang, Yang Zhang, Qifan Wang, Chenxu Wang, Fuli Feng
Prediction then Correction: An Abductive Prediction Correction Method for Sequential Recommendation
null
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sequential recommender models typically generate predictions in a single step during testing, without considering additional prediction correction to enhance performance as humans would. To improve the accuracy of these models, some researchers have attempted to simulate human analogical reasoning to correct predicti...
[ { "created": "Thu, 27 Apr 2023 09:28:35 GMT", "version": "v1" } ]
2023-04-28
[ [ "Huang", "Yulong", "" ], [ "Zhang", "Yang", "" ], [ "Wang", "Qifan", "" ], [ "Wang", "Chenxu", "" ], [ "Feng", "Fuli", "" ] ]
Sequential recommender models typically generate predictions in a single step during testing, without considering additional prediction correction to enhance performance as humans would. To improve the accuracy of these models, some researchers have attempted to simulate human analogical reasoning to correct prediction...
2012.12431
Levent Guvenc
Sukru Yaren Gelbal, Bilin Aksun-Guvenc, Levent Guvenc
SmartShuttle: Model Based Design and Evaluation of Automated On-Demand Shuttles for Solving the First-Mile and Last-Mile Problem in a Smart City
49 pages, 44 figures
null
null
null
cs.RO cs.SY eess.SY
http://creativecommons.org/licenses/by-nc-nd/4.0/
The final project report for the SmartShuttle sub-project of the Ohio State University is presented in this report. This has been a two year project where the unified, scalable and replicable automated driving architecture introduced by the Automated Driving Lab of the Ohio State University has been further developed...
[ { "created": "Wed, 23 Dec 2020 01:00:01 GMT", "version": "v1" }, { "created": "Fri, 4 Mar 2022 18:10:53 GMT", "version": "v2" } ]
2022-03-07
[ [ "Gelbal", "Sukru Yaren", "" ], [ "Aksun-Guvenc", "Bilin", "" ], [ "Guvenc", "Levent", "" ] ]
The final project report for the SmartShuttle sub-project of the Ohio State University is presented in this report. This has been a two year project where the unified, scalable and replicable automated driving architecture introduced by the Automated Driving Lab of the Ohio State University has been further developed, ...
2407.02946
Eric Stumpe
Eric Stumpe, Gernot Bodner, Francesco Flagiello, Matthias Zeppelzauer
3D Multimodal Image Registration for Plant Phenotyping
53 pages, 13 Figures, preprint submitted to Computers and Electronics in Agriculture
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
The use of multiple camera technologies in a combined multimodal monitoring system for plant phenotyping offers promising benefits. Compared to configurations that only utilize a single camera technology, cross-modal patterns can be recorded that allow a more comprehensive assessment of plant phenotypes. However, the...
[ { "created": "Wed, 3 Jul 2024 09:29:46 GMT", "version": "v1" } ]
2024-07-04
[ [ "Stumpe", "Eric", "" ], [ "Bodner", "Gernot", "" ], [ "Flagiello", "Francesco", "" ], [ "Zeppelzauer", "Matthias", "" ] ]
The use of multiple camera technologies in a combined multimodal monitoring system for plant phenotyping offers promising benefits. Compared to configurations that only utilize a single camera technology, cross-modal patterns can be recorded that allow a more comprehensive assessment of plant phenotypes. However, the e...
1704.05124
Samson Abramsky
Samson Abramsky, Anuj Dawar and Pengming Wang
The pebbling comonad in finite model theory
To appear in LiCS 2017
null
null
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Pebble games are a powerful tool in the study of finite model theory, constraint satisfaction and database theory. Monads and comonads are basic notions of category theory which are widely used in semantics of computation and in modern functional programming. We show that existential k-pebble games have a natural com...
[ { "created": "Mon, 17 Apr 2017 21:11:06 GMT", "version": "v1" } ]
2017-04-19
[ [ "Abramsky", "Samson", "" ], [ "Dawar", "Anuj", "" ], [ "Wang", "Pengming", "" ] ]
Pebble games are a powerful tool in the study of finite model theory, constraint satisfaction and database theory. Monads and comonads are basic notions of category theory which are widely used in semantics of computation and in modern functional programming. We show that existential k-pebble games have a natural comon...
2307.01009
Roberto Ammendola
Roberto Ammendola, Andrea Biagioni, Carlotta Chiarini, Andrea Ciardiello, Paolo Cretaro, Ottorino Frezza, Francesca Lo Cicero, Alessandro Lonardo, Michele Martinelli, Pier Stanislao Paolucci, Cristian Rossi, Francesco Simula, Matteo Turisini, Piero Vicini
APEIRON: composing smart TDAQ systems for high energy physics experiments
Under review in Journal of Physics: Conference Series (ACAT 2022)
null
null
null
cs.DC physics.ins-det
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
APEIRON is a framework encompassing the general architecture of a distributed heterogeneous processing platform and the corresponding software stack, from the low level device drivers up to the high level programming model. The framework is designed to be efficiently used for studying, prototyping and deploying smart...
[ { "created": "Mon, 3 Jul 2023 13:41:13 GMT", "version": "v1" } ]
2023-07-04
[ [ "Ammendola", "Roberto", "" ], [ "Biagioni", "Andrea", "" ], [ "Chiarini", "Carlotta", "" ], [ "Ciardiello", "Andrea", "" ], [ "Cretaro", "Paolo", "" ], [ "Frezza", "Ottorino", "" ], [ "Cicero", "Francesca Lo", ...
APEIRON is a framework encompassing the general architecture of a distributed heterogeneous processing platform and the corresponding software stack, from the low level device drivers up to the high level programming model. The framework is designed to be efficiently used for studying, prototyping and deploying smart t...
2303.01571
Johannes Schmidt
Nadia Creignou, Fr\'ed\'eric Olive, Johannes Schmidt
Complexity of Reasoning with Cardinality Minimality Conditions
null
null
null
null
cs.CC
http://creativecommons.org/licenses/by/4.0/
Many AI-related reasoning problems are based on the problem of satisfiability of propositional formulas with some cardinality-minimality condition. While the complexity of the satisfiability problem (SAT) is well understood when considering systematically all fragments of propositional logic within Schaefer's framewo...
[ { "created": "Thu, 2 Mar 2023 20:53:42 GMT", "version": "v1" } ]
2023-03-06
[ [ "Creignou", "Nadia", "" ], [ "Olive", "Frédéric", "" ], [ "Schmidt", "Johannes", "" ] ]
Many AI-related reasoning problems are based on the problem of satisfiability of propositional formulas with some cardinality-minimality condition. While the complexity of the satisfiability problem (SAT) is well understood when considering systematically all fragments of propositional logic within Schaefer's framework...
2210.08282
Trung Pham
Trung Xuan Pham, Jin Woong Choi, Rusty John Lloyd Mina, Thanh Nguyen, Sultan Rizky Madjid, Chang Dong Yoo
LAD: A Hybrid Deep Learning System for Benign Paroxysmal Positional Vertigo Disorders Diagnostic
Accepted to IEEE Access 2022, 13 pages, 14 figures
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Herein, we introduce "Look and Diagnose" (LAD), a hybrid deep learning-based system that aims to support doctors in the medical field in diagnosing effectively the Benign Paroxysmal Positional Vertigo (BPPV) disorder. Given the body postures of the patient in the Dix-Hallpike and lateral head turns test, the visual i...
[ { "created": "Sat, 15 Oct 2022 13:07:27 GMT", "version": "v1" } ]
2022-10-18
[ [ "Pham", "Trung Xuan", "" ], [ "Choi", "Jin Woong", "" ], [ "Mina", "Rusty John Lloyd", "" ], [ "Nguyen", "Thanh", "" ], [ "Madjid", "Sultan Rizky", "" ], [ "Yoo", "Chang Dong", "" ] ]
Herein, we introduce "Look and Diagnose" (LAD), a hybrid deep learning-based system that aims to support doctors in the medical field in diagnosing effectively the Benign Paroxysmal Positional Vertigo (BPPV) disorder. Given the body postures of the patient in the Dix-Hallpike and lateral head turns test, the visual inf...
1704.01918
Hassan Naseri
Hassan Naseri, Visa Koivunen
A Bayesian algorithm for distributed network localization using distance and direction data
Notice: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
null
null
null
cs.IT math.IT stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A reliable, accurate, and affordable positioning service is highly required in wireless networks. In this paper, the novel Message Passing Hybrid Localization (MPHL) algorithm is proposed to solve the problem of cooperative distributed localization using distance and direction estimates. This hybrid approach combines...
[ { "created": "Thu, 6 Apr 2017 16:32:50 GMT", "version": "v1" }, { "created": "Mon, 28 Aug 2017 16:19:20 GMT", "version": "v2" } ]
2017-08-29
[ [ "Naseri", "Hassan", "" ], [ "Koivunen", "Visa", "" ] ]
A reliable, accurate, and affordable positioning service is highly required in wireless networks. In this paper, the novel Message Passing Hybrid Localization (MPHL) algorithm is proposed to solve the problem of cooperative distributed localization using distance and direction estimates. This hybrid approach combines t...
2404.17297
Zhang Cheng
Zhang Cheng, Jiyang Wu, Di Wang, Qinxiang Cao
Denotation-based Compositional Compiler Verification
38 pages, 8 figures
null
null
null
cs.PL
http://creativecommons.org/licenses/by/4.0/
A desired but challenging property of compiler verification is compositionality in the sense that the compilation correctness of a program can be deduced from that of its substructures ranging from statements, functions, and modules incrementally. Previously proposed approaches have devoted extensive effort to module...
[ { "created": "Fri, 26 Apr 2024 10:06:06 GMT", "version": "v1" }, { "created": "Thu, 16 May 2024 03:44:34 GMT", "version": "v2" } ]
2024-05-17
[ [ "Cheng", "Zhang", "" ], [ "Wu", "Jiyang", "" ], [ "Wang", "Di", "" ], [ "Cao", "Qinxiang", "" ] ]
A desired but challenging property of compiler verification is compositionality in the sense that the compilation correctness of a program can be deduced from that of its substructures ranging from statements, functions, and modules incrementally. Previously proposed approaches have devoted extensive effort to module-l...
2302.08130
Chung-Che Wang
Chung-Che Wang, Yu-Chun Lin, Yu-Teng Hsu, Jyh-Shing Roger Jang
Personalized Audio Quality Preference Prediction
null
null
null
null
cs.SD cs.LG eess.AS
http://creativecommons.org/licenses/by/4.0/
This paper proposes to use both audio input and subject information to predict the personalized preference of two audio segments with the same content in different qualities. A siamese network is used to compare the inputs and predict the preference. Several different structures for each side of the siamese network a...
[ { "created": "Thu, 16 Feb 2023 07:49:06 GMT", "version": "v1" } ]
2023-02-17
[ [ "Wang", "Chung-Che", "" ], [ "Lin", "Yu-Chun", "" ], [ "Hsu", "Yu-Teng", "" ], [ "Jang", "Jyh-Shing Roger", "" ] ]
This paper proposes to use both audio input and subject information to predict the personalized preference of two audio segments with the same content in different qualities. A siamese network is used to compare the inputs and predict the preference. Several different structures for each side of the siamese network are...
1712.10285
Bo Dai
Bo Dai, Albert Shaw, Lihong Li, Lin Xiao, Niao He, Zhen Liu, Jianshu Chen, Le Song
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation
28 pages, 13 figures. To appear at the 35th International Conference on Machine Learning (ICML 2018)
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
When function approximation is used, solving the Bellman optimality equation with stability guarantees has remained a major open problem in reinforcement learning for decades. The fundamental difficulty is that the Bellman operator may become an expansion in general, resulting in oscillating and even divergent behavi...
[ { "created": "Fri, 29 Dec 2017 17:27:59 GMT", "version": "v1" }, { "created": "Tue, 29 May 2018 00:35:24 GMT", "version": "v2" }, { "created": "Thu, 31 May 2018 20:42:41 GMT", "version": "v3" }, { "created": "Tue, 5 Jun 2018 18:55:26 GMT", "version": "v4" } ]
2018-06-07
[ [ "Dai", "Bo", "" ], [ "Shaw", "Albert", "" ], [ "Li", "Lihong", "" ], [ "Xiao", "Lin", "" ], [ "He", "Niao", "" ], [ "Liu", "Zhen", "" ], [ "Chen", "Jianshu", "" ], [ "Song", "Le", "" ] ]
When function approximation is used, solving the Bellman optimality equation with stability guarantees has remained a major open problem in reinforcement learning for decades. The fundamental difficulty is that the Bellman operator may become an expansion in general, resulting in oscillating and even divergent behavior...
2306.04814
Shuwen Liu
Shuwen Liu, Bernardo Cuenca Grau, Ian Horrocks, Egor V. Kostylev
Revisiting Inferential Benchmarks for Knowledge Graph Completion
Accepted by the 20th International Conference on Principles of Knowledge Representation and Reasoning (KR 2023)
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
Knowledge Graph (KG) completion is the problem of extending an incomplete KG with missing facts. A key feature of Machine Learning approaches for KG completion is their ability to learn inference patterns, so that the predicted facts are the results of applying these patterns to the KG. Standard completion benchmarks...
[ { "created": "Wed, 7 Jun 2023 22:35:39 GMT", "version": "v1" } ]
2023-06-09
[ [ "Liu", "Shuwen", "" ], [ "Grau", "Bernardo Cuenca", "" ], [ "Horrocks", "Ian", "" ], [ "Kostylev", "Egor V.", "" ] ]
Knowledge Graph (KG) completion is the problem of extending an incomplete KG with missing facts. A key feature of Machine Learning approaches for KG completion is their ability to learn inference patterns, so that the predicted facts are the results of applying these patterns to the KG. Standard completion benchmarks, ...
2004.00605
Tomas Hodan
Tomas Hodan, Daniel Barath, Jiri Matas
EPOS: Estimating 6D Pose of Objects with Symmetries
Accepted to CVPR 2020
null
null
null
cs.CV cs.LG cs.RO eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a new method for estimating the 6D pose of rigid objects with available 3D models from a single RGB input image. The method is applicable to a broad range of objects, including challenging ones with global or partial symmetries. An object is represented by compact surface fragments which allow handling sym...
[ { "created": "Wed, 1 Apr 2020 17:41:08 GMT", "version": "v1" } ]
2020-04-02
[ [ "Hodan", "Tomas", "" ], [ "Barath", "Daniel", "" ], [ "Matas", "Jiri", "" ] ]
We present a new method for estimating the 6D pose of rigid objects with available 3D models from a single RGB input image. The method is applicable to a broad range of objects, including challenging ones with global or partial symmetries. An object is represented by compact surface fragments which allow handling symme...
2008.04581
Pietro Hiram Guzzi
Pietro Hiram Guzzi
Using Network Embeddings for Improving Network Alignment
null
null
null
null
cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Network (or Graph) Alignment Algorithms aims to reveal structural similarities among graphs. In particular Local Network Alignment Algorithms (LNAs) finds local regions of similarity among two or more networks. Such algorithms are in general based on a set of seed nodes that are used to grow an alignment. Almost all ...
[ { "created": "Tue, 11 Aug 2020 08:41:19 GMT", "version": "v1" } ]
2020-08-12
[ [ "Guzzi", "Pietro Hiram", "" ] ]
Network (or Graph) Alignment Algorithms aims to reveal structural similarities among graphs. In particular Local Network Alignment Algorithms (LNAs) finds local regions of similarity among two or more networks. Such algorithms are in general based on a set of seed nodes that are used to grow an alignment. Almost all LN...
cs/0410041
Ryutaroh Matsumoto
Kenji Tanaka, Ryutaroh Matsumoto, Tomohiko Uyematsu
Maximum Mutual Information of Space-Time Block Codes with Symbolwise Decodability
6 pages, 2 figures, using isita2004.sty, appeared in Proc. ISITA 2004, pp. 1025-1030, Parma, Italy, Oct. 10-13, 2004
null
null
null
cs.IT math.IT
null
In this paper, we analyze the performance of space-time block codes which enable symbolwise maximum likelihood decoding. We derive an upper bound of maximum mutual information (MMI) on space-time block codes that enable symbolwise maximum likelihood decoding for a frequency non-selective quasi-static fading channel. ...
[ { "created": "Mon, 18 Oct 2004 08:24:04 GMT", "version": "v1" } ]
2007-07-13
[ [ "Tanaka", "Kenji", "" ], [ "Matsumoto", "Ryutaroh", "" ], [ "Uyematsu", "Tomohiko", "" ] ]
In this paper, we analyze the performance of space-time block codes which enable symbolwise maximum likelihood decoding. We derive an upper bound of maximum mutual information (MMI) on space-time block codes that enable symbolwise maximum likelihood decoding for a frequency non-selective quasi-static fading channel. MM...
2010.09245
Scott Leask
Scott Leask, Vincent McDonell
Extraction of Discrete Spectra Modes from Video Data Using a Deep Convolutional Koopman Network
7 pages, 6 figures
null
null
null
cs.CV math.DS physics.flu-dyn
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent deep learning extensions in Koopman theory have enabled compact, interpretable representations of nonlinear dynamical systems which are amenable to linear analysis. Deep Koopman networks attempt to learn the Koopman eigenfunctions which capture the coordinate transformation to globally linearize system dynamic...
[ { "created": "Mon, 19 Oct 2020 06:26:29 GMT", "version": "v1" } ]
2020-10-20
[ [ "Leask", "Scott", "" ], [ "McDonell", "Vincent", "" ] ]
Recent deep learning extensions in Koopman theory have enabled compact, interpretable representations of nonlinear dynamical systems which are amenable to linear analysis. Deep Koopman networks attempt to learn the Koopman eigenfunctions which capture the coordinate transformation to globally linearize system dynamics....
2206.00637
Beni Egressy
Beni Egressy, Roger Wattenhofer
Graph Neural Networks with Precomputed Node Features
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Most Graph Neural Networks (GNNs) cannot distinguish some graphs or indeed some pairs of nodes within a graph. This makes it impossible to solve certain classification tasks. However, adding additional node features to these models can resolve this problem. We introduce several such augmentations, including (i) posit...
[ { "created": "Wed, 1 Jun 2022 17:16:37 GMT", "version": "v1" }, { "created": "Sat, 17 Sep 2022 12:25:24 GMT", "version": "v2" } ]
2022-09-20
[ [ "Egressy", "Beni", "" ], [ "Wattenhofer", "Roger", "" ] ]
Most Graph Neural Networks (GNNs) cannot distinguish some graphs or indeed some pairs of nodes within a graph. This makes it impossible to solve certain classification tasks. However, adding additional node features to these models can resolve this problem. We introduce several such augmentations, including (i) positio...
2104.08167
Donghan Yu
Donghan Yu and Yiming Yang
Improving Hyper-Relational Knowledge Graph Completion
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Different from traditional knowledge graphs (KGs) where facts are represented as entity-relation-entity triplets, hyper-relational KGs (HKGs) allow triplets to be associated with additional relation-entity pairs (a.k.a qualifiers) to convey more complex information. How to effectively and efficiently model the triple...
[ { "created": "Fri, 16 Apr 2021 15:26:41 GMT", "version": "v1" } ]
2021-04-19
[ [ "Yu", "Donghan", "" ], [ "Yang", "Yiming", "" ] ]
Different from traditional knowledge graphs (KGs) where facts are represented as entity-relation-entity triplets, hyper-relational KGs (HKGs) allow triplets to be associated with additional relation-entity pairs (a.k.a qualifiers) to convey more complex information. How to effectively and efficiently model the triplet-...
2301.06215
Jingyi Su
Yan Wu, Jingyi Su, David D. Moran, and Chris D. Near
Automated Software Testing Starting from Static Analysis: Current State of the Art
5 pages
null
null
null
cs.SE
http://creativecommons.org/licenses/by/4.0/
The mass production of complex software has made it impossible to manually test it for security vulnerabilities. Automated security testing tools come in a variety of flavors, function at various stages of software development, and target different categories of software vulnerabilities. It is great that we have a pl...
[ { "created": "Sun, 15 Jan 2023 23:45:43 GMT", "version": "v1" } ]
2023-01-18
[ [ "Wu", "Yan", "" ], [ "Su", "Jingyi", "" ], [ "Moran", "David D.", "" ], [ "Near", "Chris D.", "" ] ]
The mass production of complex software has made it impossible to manually test it for security vulnerabilities. Automated security testing tools come in a variety of flavors, function at various stages of software development, and target different categories of software vulnerabilities. It is great that we have a plet...
2307.02435
Prateek Yadav
Prateek Yadav, Qing Sun, Hantian Ding, Xiaopeng Li, Dejiao Zhang, Ming Tan, Xiaofei Ma, Parminder Bhatia, Ramesh Nallapati, Murali Krishna Ramanathan, Mohit Bansal, Bing Xiang
Exploring Continual Learning for Code Generation Models
ACL 2023
null
null
null
cs.LG cs.CL cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large-scale code generation models such as Codex and CodeT5 have achieved impressive performance. However, libraries are upgraded or deprecated very frequently and re-training large-scale language models is computationally expensive. Therefore, Continual Learning (CL) is an important aspect that remains underexplored...
[ { "created": "Wed, 5 Jul 2023 16:58:39 GMT", "version": "v1" } ]
2023-07-06
[ [ "Yadav", "Prateek", "" ], [ "Sun", "Qing", "" ], [ "Ding", "Hantian", "" ], [ "Li", "Xiaopeng", "" ], [ "Zhang", "Dejiao", "" ], [ "Tan", "Ming", "" ], [ "Ma", "Xiaofei", "" ], [ "Bhatia", "Parm...
Large-scale code generation models such as Codex and CodeT5 have achieved impressive performance. However, libraries are upgraded or deprecated very frequently and re-training large-scale language models is computationally expensive. Therefore, Continual Learning (CL) is an important aspect that remains underexplored i...
2208.13771
Alexander Siemenn
Alexander E. Siemenn, Zekun Ren, Qianxiao Li, Tonio Buonassisi
Fast Bayesian Optimization of Needle-in-a-Haystack Problems using Zooming Memory-Based Initialization (ZoMBI)
Paper 16 pages; SI 6 pages
npj Comput Mater 9, 79 (2023)
10.1038/s41524-023-01048-x
null
cs.LG cond-mat.mtrl-sci math.OC
http://creativecommons.org/licenses/by/4.0/
Needle-in-a-Haystack problems exist across a wide range of applications including rare disease prediction, ecological resource management, fraud detection, and material property optimization. A Needle-in-a-Haystack problem arises when there is an extreme imbalance of optimum conditions relative to the size of the dat...
[ { "created": "Fri, 26 Aug 2022 23:57:41 GMT", "version": "v1" }, { "created": "Fri, 3 Feb 2023 03:02:13 GMT", "version": "v2" } ]
2023-09-11
[ [ "Siemenn", "Alexander E.", "" ], [ "Ren", "Zekun", "" ], [ "Li", "Qianxiao", "" ], [ "Buonassisi", "Tonio", "" ] ]
Needle-in-a-Haystack problems exist across a wide range of applications including rare disease prediction, ecological resource management, fraud detection, and material property optimization. A Needle-in-a-Haystack problem arises when there is an extreme imbalance of optimum conditions relative to the size of the datas...
2302.05371
Tor Lattimore
Tor Lattimore and Andr\'as Gy\"orgy
A Second-Order Method for Stochastic Bandit Convex Optimisation
27 pages
null
null
null
cs.LG math.OC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce a simple and efficient algorithm for unconstrained zeroth-order stochastic convex bandits and prove its regret is at most $(1 + r/d)[d^{1.5} \sqrt{n} + d^3] polylog(n, d, r)$ where $n$ is the horizon, $d$ the dimension and $r$ is the radius of a known ball containing the minimiser of the loss.
[ { "created": "Fri, 10 Feb 2023 16:49:58 GMT", "version": "v1" } ]
2023-02-13
[ [ "Lattimore", "Tor", "" ], [ "György", "András", "" ] ]
We introduce a simple and efficient algorithm for unconstrained zeroth-order stochastic convex bandits and prove its regret is at most $(1 + r/d)[d^{1.5} \sqrt{n} + d^3] polylog(n, d, r)$ where $n$ is the horizon, $d$ the dimension and $r$ is the radius of a known ball containing the minimiser of the loss.
1908.03809
Jonathan Howe
Jonathan Howe, Kyle Pula, Aaron A. Reite
Conditional Generative Adversarial Networks for Data Augmentation and Adaptation in Remotely Sensed Imagery
null
null
10.1117/12.2529586
null
cs.CV cs.LG eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The difficulty in obtaining labeled data relevant to a given task is among the most common and well-known practical obstacles to applying deep learning techniques to new or even slightly modified domains. The data volumes required by the current generation of supervised learning algorithms typically far exceed what a...
[ { "created": "Sat, 10 Aug 2019 21:26:54 GMT", "version": "v1" } ]
2019-09-24
[ [ "Howe", "Jonathan", "" ], [ "Pula", "Kyle", "" ], [ "Reite", "Aaron A.", "" ] ]
The difficulty in obtaining labeled data relevant to a given task is among the most common and well-known practical obstacles to applying deep learning techniques to new or even slightly modified domains. The data volumes required by the current generation of supervised learning algorithms typically far exceed what a h...
1112.6007
Giorgio Ottaviani
J. M. Landsberg and Giorgio Ottaviani
New lower bounds for the border rank of matrix multiplication
9 pages. Version 1 contained an error in the proof of its main theorem and in the course of fixing it we proved a stronger statement. v3: proof of main theorem moved up
null
null
null
cs.CC math.AG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The border rank of the matrix multiplication operator for n by n matrices is a standard measure of its complexity. Using techniques from algebraic geometry and representation theory, we show the border rank is at least 2n^2-n. Our bounds are better than the previous lower bound (due to Lickteig in 1985) of 3/2 n^2+ n...
[ { "created": "Tue, 27 Dec 2011 19:24:57 GMT", "version": "v1" }, { "created": "Tue, 6 Mar 2012 15:25:01 GMT", "version": "v2" }, { "created": "Sun, 2 Jun 2013 20:52:52 GMT", "version": "v3" } ]
2013-06-04
[ [ "Landsberg", "J. M.", "" ], [ "Ottaviani", "Giorgio", "" ] ]
The border rank of the matrix multiplication operator for n by n matrices is a standard measure of its complexity. Using techniques from algebraic geometry and representation theory, we show the border rank is at least 2n^2-n. Our bounds are better than the previous lower bound (due to Lickteig in 1985) of 3/2 n^2+ n/2...
2210.06346
Xin Li
Xin Li, Xuli Tang, Qikai Cheng
Predicting the clinical citation count of biomedical papers using multilayer perceptron neural network
25 pages, 8 figures
Journal of Informetrics 2022
null
null
cs.CL cs.LG
http://creativecommons.org/licenses/by/4.0/
The number of clinical citations received from clinical guidelines or clinical trials has been considered as one of the most appropriate indicators for quantifying the clinical impact of biomedical papers. Therefore, the early prediction of the clinical citation count of biomedical papers is critical to scientific ac...
[ { "created": "Wed, 7 Sep 2022 12:08:24 GMT", "version": "v1" }, { "created": "Sat, 15 Oct 2022 10:41:49 GMT", "version": "v2" }, { "created": "Fri, 21 Oct 2022 07:15:53 GMT", "version": "v3" } ]
2022-10-24
[ [ "Li", "Xin", "" ], [ "Tang", "Xuli", "" ], [ "Cheng", "Qikai", "" ] ]
The number of clinical citations received from clinical guidelines or clinical trials has been considered as one of the most appropriate indicators for quantifying the clinical impact of biomedical papers. Therefore, the early prediction of the clinical citation count of biomedical papers is critical to scientific acti...
2007.10064
Niloofar Yazdani
Niloofar Yazdani, Lars Nielsen, and Daniel E. Lucani
Memory-aware Online Compression of CAN Bus Data for Future Vehicular Systems
6 pages, 7 figures
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Vehicles generate a large amount of data from their internal sensors. This data is not only useful for a vehicle's proper operation, but it provides car manufacturers with the ability to optimize performance of individual vehicles and companies with fleets of vehicles (e.g., trucks, taxis, tractors) to optimize their...
[ { "created": "Mon, 20 Jul 2020 12:54:42 GMT", "version": "v1" } ]
2020-07-21
[ [ "Yazdani", "Niloofar", "" ], [ "Nielsen", "Lars", "" ], [ "Lucani", "Daniel E.", "" ] ]
Vehicles generate a large amount of data from their internal sensors. This data is not only useful for a vehicle's proper operation, but it provides car manufacturers with the ability to optimize performance of individual vehicles and companies with fleets of vehicles (e.g., trucks, taxis, tractors) to optimize their o...
2110.02896
Jan Hartman
Andra\v{z} De Luisa, Jan Hartman, David Nabergoj, Samo Pahor, Marko Rus, Bozhidar Stevanoski, Jure Dem\v{s}ar, Erik \v{S}trumbelj
Predicting the Popularity of Games on Steam
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
The video game industry has seen rapid growth over the last decade. Thousands of video games are released and played by millions of people every year, creating a large community of players. Steam is a leading gaming platform and social networking site, which allows its users to purchase and store games. A by-product ...
[ { "created": "Wed, 6 Oct 2021 16:21:15 GMT", "version": "v1" } ]
2021-10-07
[ [ "De Luisa", "Andraž", "" ], [ "Hartman", "Jan", "" ], [ "Nabergoj", "David", "" ], [ "Pahor", "Samo", "" ], [ "Rus", "Marko", "" ], [ "Stevanoski", "Bozhidar", "" ], [ "Demšar", "Jure", "" ], [ "Štr...
The video game industry has seen rapid growth over the last decade. Thousands of video games are released and played by millions of people every year, creating a large community of players. Steam is a leading gaming platform and social networking site, which allows its users to purchase and store games. A by-product of...
2307.05069
EPTCS
Panagiotis Papadamos (Technical University of Denmark), Nina Gierasimczuk (Technical University of Denmark)
Cognitive Bias and Belief Revision
In Proceedings TARK 2023, arXiv:2307.04005
EPTCS 379, 2023, pp. 441-454
10.4204/EPTCS.379.34
null
cs.LO cs.AI
http://creativecommons.org/licenses/by/4.0/
In this paper we formalise three types of cognitive bias within the framework of belief revision: confirmation bias, framing bias, and anchoring bias. We interpret them generally, as restrictions on the process of iterated revision, and we apply them to three well-known belief revision methods: conditioning, lexicogr...
[ { "created": "Tue, 11 Jul 2023 07:13:52 GMT", "version": "v1" } ]
2023-07-12
[ [ "Papadamos", "Panagiotis", "", "Technical University of Denmark" ], [ "Gierasimczuk", "Nina", "", "Technical University of Denmark" ] ]
In this paper we formalise three types of cognitive bias within the framework of belief revision: confirmation bias, framing bias, and anchoring bias. We interpret them generally, as restrictions on the process of iterated revision, and we apply them to three well-known belief revision methods: conditioning, lexicograp...
2307.08467
Tin Barisin
Tin Barisin and Jesus Angulo and Katja Schladitz and Claudia Redenbach
Riesz feature representation: scale equivariant scattering network for classification tasks
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Scattering networks yield powerful and robust hierarchical image descriptors which do not require lengthy training and which work well with very few training data. However, they rely on sampling the scale dimension. Hence, they become sensitive to scale variations and are unable to generalize to unseen scales. In thi...
[ { "created": "Mon, 17 Jul 2023 13:21:28 GMT", "version": "v1" }, { "created": "Thu, 11 Jan 2024 13:38:29 GMT", "version": "v2" } ]
2024-01-12
[ [ "Barisin", "Tin", "" ], [ "Angulo", "Jesus", "" ], [ "Schladitz", "Katja", "" ], [ "Redenbach", "Claudia", "" ] ]
Scattering networks yield powerful and robust hierarchical image descriptors which do not require lengthy training and which work well with very few training data. However, they rely on sampling the scale dimension. Hence, they become sensitive to scale variations and are unable to generalize to unseen scales. In this ...
1307.4815
Yongpeng Wu
Yongpeng Wu, Chengshan Xiao, Xiqi Gao, John D. Matyjas, and Zhi Ding
Linear Precoder Design for MIMO Interference Channels with Finite-Alphabet Signaling
15 pages, 13 figures, IEEE Transaction on Communications, accepted for publication
null
10.1109/TCOMM.2013.072213.130132
null
cs.IT math.IT
http://creativecommons.org/licenses/by/3.0/
This paper investigates the linear precoder design for $K$-user interference channels of multiple-input multiple-output (MIMO) transceivers under finite alphabet inputs. We first obtain general explicit expressions of the achievable rate for users in the MIMO interference channel systems. We study optimal transmissio...
[ { "created": "Thu, 18 Jul 2013 02:40:11 GMT", "version": "v1" } ]
2016-11-18
[ [ "Wu", "Yongpeng", "" ], [ "Xiao", "Chengshan", "" ], [ "Gao", "Xiqi", "" ], [ "Matyjas", "John D.", "" ], [ "Ding", "Zhi", "" ] ]
This paper investigates the linear precoder design for $K$-user interference channels of multiple-input multiple-output (MIMO) transceivers under finite alphabet inputs. We first obtain general explicit expressions of the achievable rate for users in the MIMO interference channel systems. We study optimal transmission ...
2403.09450
Zhangheng Li
Zhangheng Li, Junyuan Hong, Bo Li, Zhangyang Wang
Shake to Leak: Fine-tuning Diffusion Models Can Amplify the Generative Privacy Risk
null
null
null
null
cs.LG cs.CR
http://creativecommons.org/licenses/by/4.0/
While diffusion models have recently demonstrated remarkable progress in generating realistic images, privacy risks also arise: published models or APIs could generate training images and thus leak privacy-sensitive training information. In this paper, we reveal a new risk, Shake-to-Leak (S2L), that fine-tuning the p...
[ { "created": "Thu, 14 Mar 2024 14:48:37 GMT", "version": "v1" }, { "created": "Mon, 22 Apr 2024 16:48:39 GMT", "version": "v2" } ]
2024-04-23
[ [ "Li", "Zhangheng", "" ], [ "Hong", "Junyuan", "" ], [ "Li", "Bo", "" ], [ "Wang", "Zhangyang", "" ] ]
While diffusion models have recently demonstrated remarkable progress in generating realistic images, privacy risks also arise: published models or APIs could generate training images and thus leak privacy-sensitive training information. In this paper, we reveal a new risk, Shake-to-Leak (S2L), that fine-tuning the pre...
2306.15121
William Godoy
William F. Godoy, Pedro Valero-Lara, Keita Teranishi, Prasanna Balaprakash, Jeffrey S. Vetter
Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation
Accepted at the Sixteenth International Workshop on Parallel Programming Models and Systems Software for High-End Computing (P2S2), 2023 to be held in conjunction with ICPP 2023: The 52nd International Conference on Parallel Processing. 10 pages, 6 figures, 5 tables
null
10.1145/3605731.3605886
null
cs.AI cs.ET cs.PL
http://creativecommons.org/licenses/by/4.0/
We evaluate AI-assisted generative capabilities on fundamental numerical kernels in high-performance computing (HPC), including AXPY, GEMV, GEMM, SpMV, Jacobi Stencil, and CG. We test the generated kernel codes for a variety of language-supported programming models, including (1) C++ (e.g., OpenMP [including offload]...
[ { "created": "Tue, 27 Jun 2023 00:11:31 GMT", "version": "v1" } ]
2023-09-20
[ [ "Godoy", "William F.", "" ], [ "Valero-Lara", "Pedro", "" ], [ "Teranishi", "Keita", "" ], [ "Balaprakash", "Prasanna", "" ], [ "Vetter", "Jeffrey S.", "" ] ]
We evaluate AI-assisted generative capabilities on fundamental numerical kernels in high-performance computing (HPC), including AXPY, GEMV, GEMM, SpMV, Jacobi Stencil, and CG. We test the generated kernel codes for a variety of language-supported programming models, including (1) C++ (e.g., OpenMP [including offload], ...
2301.12193
Pengyu Zhang
Pengyu Zhang, Yingbo Zhou, Ming Hu, Xin Fu, Xian Wei, and Mingsong Chen
CyclicFL: A Cyclic Model Pre-Training Approach to Efficient Federated Learning
null
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Since random initial models in Federated Learning (FL) can easily result in unregulated Stochastic Gradient Descent (SGD) processes, existing FL methods greatly suffer from both slow convergence and poor accuracy, especially for non-IID scenarios. To address this problem, we propose a novel FL method named CyclicFL, ...
[ { "created": "Sat, 28 Jan 2023 13:28:34 GMT", "version": "v1" } ]
2023-01-31
[ [ "Zhang", "Pengyu", "" ], [ "Zhou", "Yingbo", "" ], [ "Hu", "Ming", "" ], [ "Fu", "Xin", "" ], [ "Wei", "Xian", "" ], [ "Chen", "Mingsong", "" ] ]
Since random initial models in Federated Learning (FL) can easily result in unregulated Stochastic Gradient Descent (SGD) processes, existing FL methods greatly suffer from both slow convergence and poor accuracy, especially for non-IID scenarios. To address this problem, we propose a novel FL method named CyclicFL, wh...
2308.02263
Jinyu Long
Jinyu Long and Jetic G\=u and Binhao Bai and Zhibo Yang and Ping Wei and Junli Li
Efficient Monaural Speech Enhancement using Spectrum Attention Fusion
null
null
null
null
cs.SD cs.CL eess.AS
http://creativecommons.org/licenses/by/4.0/
Speech enhancement is a demanding task in automated speech processing pipelines, focusing on separating clean speech from noisy channels. Transformer based models have recently bested RNN and CNN models in speech enhancement, however at the same time they are much more computationally expensive and require much more ...
[ { "created": "Fri, 4 Aug 2023 11:39:29 GMT", "version": "v1" } ]
2023-08-07
[ [ "Long", "Jinyu", "" ], [ "Gū", "Jetic", "" ], [ "Bai", "Binhao", "" ], [ "Yang", "Zhibo", "" ], [ "Wei", "Ping", "" ], [ "Li", "Junli", "" ] ]
Speech enhancement is a demanding task in automated speech processing pipelines, focusing on separating clean speech from noisy channels. Transformer based models have recently bested RNN and CNN models in speech enhancement, however at the same time they are much more computationally expensive and require much more hi...
1909.11759
Wei Cai
Wei Cai, Xiaoguang Li, Lizuo Liu
A Phase Shift Deep Neural Network for High Frequency Approximation and Wave Problems
arXiv admin note: substantial text overlap with arXiv:1905.01389
null
null
null
cs.LG cs.NA math.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a phase shift deep neural network (PhaseDNN), which provides a uniform wideband convergence in approximating high frequency functions and solutions of wave equations. The PhaseDNN makes use of the fact that common DNNs often achieve convergence in the low frequency range first, and a series ...
[ { "created": "Mon, 23 Sep 2019 20:45:08 GMT", "version": "v1" }, { "created": "Fri, 13 Dec 2019 23:49:49 GMT", "version": "v2" } ]
2019-12-17
[ [ "Cai", "Wei", "" ], [ "Li", "Xiaoguang", "" ], [ "Liu", "Lizuo", "" ] ]
In this paper, we propose a phase shift deep neural network (PhaseDNN), which provides a uniform wideband convergence in approximating high frequency functions and solutions of wave equations. The PhaseDNN makes use of the fact that common DNNs often achieve convergence in the low frequency range first, and a series of...
1803.05573
Tim Salimans
Tim Salimans, Han Zhang, Alec Radford, Dimitris Metaxas
Improving GANs Using Optimal Transport
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present Optimal Transport GAN (OT-GAN), a variant of generative adversarial nets minimizing a new metric measuring the distance between the generator distribution and the data distribution. This metric, which we call mini-batch energy distance, combines optimal transport in primal form with an energy distance defi...
[ { "created": "Thu, 15 Mar 2018 02:34:46 GMT", "version": "v1" } ]
2018-03-16
[ [ "Salimans", "Tim", "" ], [ "Zhang", "Han", "" ], [ "Radford", "Alec", "" ], [ "Metaxas", "Dimitris", "" ] ]
We present Optimal Transport GAN (OT-GAN), a variant of generative adversarial nets minimizing a new metric measuring the distance between the generator distribution and the data distribution. This metric, which we call mini-batch energy distance, combines optimal transport in primal form with an energy distance define...
2207.11971
Yingyi Chen
Yingyi Chen, Xi Shen, Yahui Liu, Qinghua Tao, Johan A.K. Suykens
Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer
Accepted to Pattern Recognition Letters 2022. Project page: https://yingyichen-cyy.github.io/Jigsaw-ViT/
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The success of Vision Transformer (ViT) in various computer vision tasks has promoted the ever-increasing prevalence of this convolution-free network. The fact that ViT works on image patches makes it potentially relevant to the problem of jigsaw puzzle solving, which is a classical self-supervised task aiming at reo...
[ { "created": "Mon, 25 Jul 2022 08:18:18 GMT", "version": "v1" }, { "created": "Thu, 5 Jan 2023 14:55:55 GMT", "version": "v2" } ]
2023-01-06
[ [ "Chen", "Yingyi", "" ], [ "Shen", "Xi", "" ], [ "Liu", "Yahui", "" ], [ "Tao", "Qinghua", "" ], [ "Suykens", "Johan A. K.", "" ] ]
The success of Vision Transformer (ViT) in various computer vision tasks has promoted the ever-increasing prevalence of this convolution-free network. The fact that ViT works on image patches makes it potentially relevant to the problem of jigsaw puzzle solving, which is a classical self-supervised task aiming at reord...
2102.06599
Jack Turner
Jack Turner, Elliot J. Crowley, Michael O'Boyle
Neural Architecture Search as Program Transformation Exploration
null
null
null
null
cs.LG cs.PL
http://creativecommons.org/licenses/by-nc-sa/4.0/
Improving the performance of deep neural networks (DNNs) is important to both the compiler and neural architecture search (NAS) communities. Compilers apply program transformations in order to exploit hardware parallelism and memory hierarchy. However, legality concerns mean they fail to exploit the natural robustnes...
[ { "created": "Fri, 12 Feb 2021 16:11:05 GMT", "version": "v1" } ]
2021-02-15
[ [ "Turner", "Jack", "" ], [ "Crowley", "Elliot J.", "" ], [ "O'Boyle", "Michael", "" ] ]
Improving the performance of deep neural networks (DNNs) is important to both the compiler and neural architecture search (NAS) communities. Compilers apply program transformations in order to exploit hardware parallelism and memory hierarchy. However, legality concerns mean they fail to exploit the natural robustness ...
2005.00749
Zheng Wang
Jie Ren, Lu Yuan, Petteri Nurmi, Xiaoming Wang, Miao Ma, Ling Gao, Zhanyong Tang, Jie Zheng, Zheng Wang
Smart, Adaptive Energy Optimization for Mobile Web Interactions
Accepted to be published at INFOCOM 2020
null
null
null
cs.NI cs.HC cs.PF
http://creativecommons.org/licenses/by/4.0/
Web technology underpins many interactive mobile applications. However, energy-efficient mobile web interactions is an outstanding challenge. Given the increasing diversity and complexity of mobile hardware, any practical optimization scheme must work for a wide range of users, mobile platforms and web workloads. Thi...
[ { "created": "Sat, 2 May 2020 08:51:07 GMT", "version": "v1" } ]
2020-05-05
[ [ "Ren", "Jie", "" ], [ "Yuan", "Lu", "" ], [ "Nurmi", "Petteri", "" ], [ "Wang", "Xiaoming", "" ], [ "Ma", "Miao", "" ], [ "Gao", "Ling", "" ], [ "Tang", "Zhanyong", "" ], [ "Zheng", "Jie", "...
Web technology underpins many interactive mobile applications. However, energy-efficient mobile web interactions is an outstanding challenge. Given the increasing diversity and complexity of mobile hardware, any practical optimization scheme must work for a wide range of users, mobile platforms and web workloads. This ...
1401.0503
Z\'ador D\'aniel Kelemen
Z\'ador D\'aniel Kelemen
Process Based Unification for Multi-Model Software Process Improvement
PhD Thesis
ISBN: 978-90-386-3313-8, 2013, Technische Universiteit Eindhoven
10.6100/IR741509
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A number of differences among quality approaches exist and there can be various situations in which the usage of multiple approaches is required, e.g. to strengthen a particular process with multiple quality approaches or to reach certification of the compliance to a number of standards. First of all it has to be dec...
[ { "created": "Mon, 30 Dec 2013 19:58:36 GMT", "version": "v1" } ]
2014-01-03
[ [ "Kelemen", "Zádor Dániel", "" ] ]
A number of differences among quality approaches exist and there can be various situations in which the usage of multiple approaches is required, e.g. to strengthen a particular process with multiple quality approaches or to reach certification of the compliance to a number of standards. First of all it has to be decid...
2310.19018
Md Taimur Ahad
Md Taimur Ahad and Yousuf Rayhan Emon
Securing Refugee Identity: A Literature Review on Blockchain-based Smart Contract
null
null
null
null
cs.CR cs.CY
http://creativecommons.org/licenses/by/4.0/
Identity documentation for refugees is a complex process and crucial for host nations. A secured identity management system ensures both security and the efficient provision of services for the host nation and the donor organizations. Realizing the benefits, a handful of studies enriched the blockchain-based security...
[ { "created": "Sun, 29 Oct 2023 14:16:26 GMT", "version": "v1" } ]
2023-10-31
[ [ "Ahad", "Md Taimur", "" ], [ "Emon", "Yousuf Rayhan", "" ] ]
Identity documentation for refugees is a complex process and crucial for host nations. A secured identity management system ensures both security and the efficient provision of services for the host nation and the donor organizations. Realizing the benefits, a handful of studies enriched the blockchain-based security i...
0903.0695
Shai Haim
Shai Haim and Toby Walsh
Online Estimation of SAT Solving Runtime
6 pages, 3 figures. Proc. of the 11th International Conf. on Theory and Applications of Satisfiability Testing, Guangzhou, China, May 2008
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present an online method for estimating the cost of solving SAT problems. Modern SAT solvers present several challenges to estimate search cost including non-chronological backtracking, learning and restarts. Our method uses a linear model trained on data gathered at the start of search. We show the effectiveness ...
[ { "created": "Wed, 4 Mar 2009 04:56:07 GMT", "version": "v1" } ]
2009-03-05
[ [ "Haim", "Shai", "" ], [ "Walsh", "Toby", "" ] ]
We present an online method for estimating the cost of solving SAT problems. Modern SAT solvers present several challenges to estimate search cost including non-chronological backtracking, learning and restarts. Our method uses a linear model trained on data gathered at the start of search. We show the effectiveness of...
2308.01037
Nicolas Guidotti
Nicolas L. Guidotti, Juan A. Acebr\'on, Jos\'e Monteiro
A Fast Monte Carlo algorithm for evaluating matrix functions with application in complex networks
To be published in the Journal of Scientific Computing
null
null
null
cs.DS
http://creativecommons.org/licenses/by/4.0/
We propose a novel stochastic algorithm that randomly samples entire rows and columns of the matrix as a way to approximate an arbitrary matrix function using the power series expansion. This contrasts with existing Monte Carlo methods, which only work with one entry at a time, resulting in a significantly better con...
[ { "created": "Wed, 2 Aug 2023 09:29:13 GMT", "version": "v1" }, { "created": "Tue, 19 Dec 2023 15:40:24 GMT", "version": "v2" }, { "created": "Tue, 13 Feb 2024 11:59:48 GMT", "version": "v3" }, { "created": "Mon, 26 Feb 2024 13:13:05 GMT", "version": "v4" } ]
2024-02-27
[ [ "Guidotti", "Nicolas L.", "" ], [ "Acebrón", "Juan A.", "" ], [ "Monteiro", "José", "" ] ]
We propose a novel stochastic algorithm that randomly samples entire rows and columns of the matrix as a way to approximate an arbitrary matrix function using the power series expansion. This contrasts with existing Monte Carlo methods, which only work with one entry at a time, resulting in a significantly better conve...
2005.11018
Jingge Zhu
Jingge Zhu
Semi-Supervised Learning: the Case When Unlabeled Data is Equally Useful
Published in UAI 2020. This version: an error in Lemma 2 is corrected
null
null
null
cs.LG cs.IT math.IT stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Semi-supervised learning algorithms attempt to take advantage of relatively inexpensive unlabeled data to improve learning performance. In this work, we consider statistical models where the data distributions can be characterized by continuous parameters. We show that under certain conditions on the distribution, un...
[ { "created": "Fri, 22 May 2020 06:05:00 GMT", "version": "v1" }, { "created": "Mon, 25 May 2020 06:53:36 GMT", "version": "v2" }, { "created": "Mon, 17 Jul 2023 05:15:23 GMT", "version": "v3" } ]
2023-07-18
[ [ "Zhu", "Jingge", "" ] ]
Semi-supervised learning algorithms attempt to take advantage of relatively inexpensive unlabeled data to improve learning performance. In this work, we consider statistical models where the data distributions can be characterized by continuous parameters. We show that under certain conditions on the distribution, unla...
2206.08978
Jamell Dacon
Jamell Dacon
Towards a Deep Multi-layered Dialectal Language Analysis: A Case Study of African-American English
Accepted to the NAACL 2022 (HCI+NLP) Workshop
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Currently, natural language processing (NLP) models proliferate language discrimination leading to potentially harmful societal impacts as a result of biased outcomes. For example, part-of-speech taggers trained on Mainstream American English (MAE) produce non-interpretable results when applied to African American En...
[ { "created": "Fri, 3 Jun 2022 01:05:58 GMT", "version": "v1" } ]
2022-06-22
[ [ "Dacon", "Jamell", "" ] ]
Currently, natural language processing (NLP) models proliferate language discrimination leading to potentially harmful societal impacts as a result of biased outcomes. For example, part-of-speech taggers trained on Mainstream American English (MAE) produce non-interpretable results when applied to African American Engl...
1107.1359
Nicolas Catusse
Nicolas Catusse, Victor Chepoi, Karim Nouioua, Yann Vaxes
Bidirected minimum Manhattan network problem
14 pages, 16 figures
null
null
null
cs.CG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the bidirected minimum Manhattan network problem, given a set T of n terminals in the plane, we need to construct a network N(T) of minimum total length with the property that the edges of N(T) are axis-parallel and oriented in a such a way that every ordered pair of terminals is connected in N(T) by a directed Ma...
[ { "created": "Thu, 7 Jul 2011 12:00:51 GMT", "version": "v1" } ]
2011-07-08
[ [ "Catusse", "Nicolas", "" ], [ "Chepoi", "Victor", "" ], [ "Nouioua", "Karim", "" ], [ "Vaxes", "Yann", "" ] ]
In the bidirected minimum Manhattan network problem, given a set T of n terminals in the plane, we need to construct a network N(T) of minimum total length with the property that the edges of N(T) are axis-parallel and oriented in a such a way that every ordered pair of terminals is connected in N(T) by a directed Manh...
2208.07740
Yansong Zhang
Yansong Zhang, Bo Shen, Yingsi Zhao
Rational Uniform Consensus with General Omission Failures
Accepted by the journal "Computational Intelligence and Neuroscience"
null
10.1155/2022/9544059
null
cs.GT cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Generally, system failures, such as crash failures, Byzantine failures and so on, are considered as common reasons for the inconsistencies of distributed consensus and have been extensively studied. In fact, strategic manipulations by rational agents do not be ignored for reaching consensus in distributed system. In ...
[ { "created": "Tue, 16 Aug 2022 13:26:08 GMT", "version": "v1" } ]
2022-09-07
[ [ "Zhang", "Yansong", "" ], [ "Shen", "Bo", "" ], [ "Zhao", "Yingsi", "" ] ]
Generally, system failures, such as crash failures, Byzantine failures and so on, are considered as common reasons for the inconsistencies of distributed consensus and have been extensively studied. In fact, strategic manipulations by rational agents do not be ignored for reaching consensus in distributed system. In th...
1904.13338
Eduard Kamburjan
Eduard Kamburjan
Behavioral Program Logic and LAGC Semantics without Continuations (Technical Report)
null
null
null
null
cs.LO cs.PL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present Behavioral Program Logic (BPL), a dynamic logic for trace properties that incorporates concepts from behavioral types and allows reasoning about non-functional properties within a sequent calculus. BPL uses behavioral modalities [s |- {\tau} ], to verify statements s against behavioral specifications {\tau...
[ { "created": "Tue, 30 Apr 2019 16:09:06 GMT", "version": "v1" } ]
2019-05-01
[ [ "Kamburjan", "Eduard", "" ] ]
We present Behavioral Program Logic (BPL), a dynamic logic for trace properties that incorporates concepts from behavioral types and allows reasoning about non-functional properties within a sequent calculus. BPL uses behavioral modalities [s |- {\tau} ], to verify statements s against behavioral specifications {\tau}....
2110.04148
Matthew Guzdial
Kristen K. Yu, Matthew Guzdial and Nathan R. Sturtevant
The Definition-Context-Purpose Paradigm and Other Insights from Industry Professionals About the Definition of a Quest
8 pages, 2 figures, AIIDE 2021
Proceedings of the 17th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 2021 (AIIDE-21)
null
null
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Among academic communities there is no single agreed upon definition of a quest. The industry perspective on this topic is also largely unknown. Thus, thee purpose of this paper is to gain an understanding of the definition of a quest from industry professionals to better inform the academic community. We interviewed...
[ { "created": "Thu, 7 Oct 2021 05:35:23 GMT", "version": "v1" } ]
2021-10-11
[ [ "Yu", "Kristen K.", "" ], [ "Guzdial", "Matthew", "" ], [ "Sturtevant", "Nathan R.", "" ] ]
Among academic communities there is no single agreed upon definition of a quest. The industry perspective on this topic is also largely unknown. Thus, thee purpose of this paper is to gain an understanding of the definition of a quest from industry professionals to better inform the academic community. We interviewed f...
2308.08431
Aishwarya Venkataramanan
Aishwarya Venkataramanan and Martin Laviale and C\'edric Pradalier
Integrating Visual and Semantic Similarity Using Hierarchies for Image Retrieval
Accepted in ICVS 2023
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Most of the research in content-based image retrieval (CBIR) focus on developing robust feature representations that can effectively retrieve instances from a database of images that are visually similar to a query. However, the retrieved images sometimes contain results that are not semantically related to the query...
[ { "created": "Wed, 16 Aug 2023 15:23:14 GMT", "version": "v1" } ]
2023-08-17
[ [ "Venkataramanan", "Aishwarya", "" ], [ "Laviale", "Martin", "" ], [ "Pradalier", "Cédric", "" ] ]
Most of the research in content-based image retrieval (CBIR) focus on developing robust feature representations that can effectively retrieve instances from a database of images that are visually similar to a query. However, the retrieved images sometimes contain results that are not semantically related to the query. ...
2311.04694
Lukas Gienapp
Lukas Gienapp, Harrisen Scells, Niklas Deckers, Janek Bevendorff, Shuai Wang, Johannes Kiesel, Shahbaz Syed, Maik Fr\"obe, Guido Zuccon, Benno Stein, Matthias Hagen, Martin Potthast
Evaluating Generative Ad Hoc Information Retrieval
14 pages, 6 figures, 1 table. Published at SIGIR'24 perspective paper track
null
10.1145/3626772.3657849
null
cs.IR cs.CL
http://creativecommons.org/licenses/by/4.0/
Recent advances in large language models have enabled the development of viable generative retrieval systems. Instead of a traditional document ranking, generative retrieval systems often directly return a grounded generated text as a response to a query. Quantifying the utility of the textual responses is essential ...
[ { "created": "Wed, 8 Nov 2023 14:05:00 GMT", "version": "v1" }, { "created": "Thu, 2 May 2024 08:50:42 GMT", "version": "v2" }, { "created": "Wed, 22 May 2024 10:33:56 GMT", "version": "v3" } ]
2024-05-24
[ [ "Gienapp", "Lukas", "" ], [ "Scells", "Harrisen", "" ], [ "Deckers", "Niklas", "" ], [ "Bevendorff", "Janek", "" ], [ "Wang", "Shuai", "" ], [ "Kiesel", "Johannes", "" ], [ "Syed", "Shahbaz", "" ], [ ...
Recent advances in large language models have enabled the development of viable generative retrieval systems. Instead of a traditional document ranking, generative retrieval systems often directly return a grounded generated text as a response to a query. Quantifying the utility of the textual responses is essential fo...
2103.11821
Joonas Sova
J\"uri Lember, Joonas Sova
Regenerativity of Viterbi process for pairwise Markov models
arXiv admin note: substantial text overlap with arXiv:1708.03799
Journal of Theoretical Probability volume 34 (2021)
10.1007/s10959-020-01022-z
null
cs.IT math.IT math.ST stat.ML stat.TH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
For hidden Markov models one of the most popular estimates of the hidden chain is the Viterbi path -- the path maximising the posterior probability. We consider a more general setting, called the pairwise Markov model (PMM), where the joint process consisting of finite-state hidden process and observation process is ...
[ { "created": "Mon, 15 Mar 2021 15:01:29 GMT", "version": "v1" } ]
2021-03-23
[ [ "Lember", "Jüri", "" ], [ "Sova", "Joonas", "" ] ]
For hidden Markov models one of the most popular estimates of the hidden chain is the Viterbi path -- the path maximising the posterior probability. We consider a more general setting, called the pairwise Markov model (PMM), where the joint process consisting of finite-state hidden process and observation process is as...
2205.14660
Jun Wang
Changyu Hou, Jun Wang, Yixuan Qiao, Peng Jiang, Peng Gao, Guotong Xie, Qizhi Lin, Xiaopeng Wang, Xiandi Jiang, Benqi Wang, Qifeng Xiao
SFE-AI at SemEval-2022 Task 11: Low-Resource Named Entity Recognition using Large Pre-trained Language Models
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Large scale pre-training models have been widely used in named entity recognition (NER) tasks. However, model ensemble through parameter averaging or voting can not give full play to the differentiation advantages of different models, especially in the open domain. This paper describes our NER system in the SemEval 2...
[ { "created": "Sun, 29 May 2022 13:40:14 GMT", "version": "v1" } ]
2022-05-31
[ [ "Hou", "Changyu", "" ], [ "Wang", "Jun", "" ], [ "Qiao", "Yixuan", "" ], [ "Jiang", "Peng", "" ], [ "Gao", "Peng", "" ], [ "Xie", "Guotong", "" ], [ "Lin", "Qizhi", "" ], [ "Wang", "Xiaopeng", ...
Large scale pre-training models have been widely used in named entity recognition (NER) tasks. However, model ensemble through parameter averaging or voting can not give full play to the differentiation advantages of different models, especially in the open domain. This paper describes our NER system in the SemEval 202...
2310.13664
Eliseo Bao Souto
Eliseo Bao Souto, Anxo P\'erez and Javier Parapar
Explainable Depression Symptom Detection in Social Media
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Users of social platforms often perceive these sites as supportive spaces to post about their mental health issues. Those conversations contain important traces about individuals' health risks. Recently, researchers have exploited this online information to construct mental health detection models, which aim to ident...
[ { "created": "Fri, 20 Oct 2023 17:05:27 GMT", "version": "v1" }, { "created": "Mon, 23 Oct 2023 08:31:50 GMT", "version": "v2" } ]
2023-10-24
[ [ "Souto", "Eliseo Bao", "" ], [ "Pérez", "Anxo", "" ], [ "Parapar", "Javier", "" ] ]
Users of social platforms often perceive these sites as supportive spaces to post about their mental health issues. Those conversations contain important traces about individuals' health risks. Recently, researchers have exploited this online information to construct mental health detection models, which aim to identif...
1810.00781
Yujiao Cheng
Yujiao Cheng, Weiye Zhao, Changliu Liu, and Masayoshi Tomizuka
Human Motion Prediction using Semi-adaptable Neural Networks
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Human motion prediction is an important component to facilitate human robot interaction. Robots need to accurately predict human's future movement in order to safely plan its own motion trajectories and efficiently collaborate with humans. Many recent approaches predict human's movement using deep learning methods, s...
[ { "created": "Mon, 1 Oct 2018 16:01:10 GMT", "version": "v1" }, { "created": "Tue, 17 Sep 2019 22:08:07 GMT", "version": "v2" } ]
2019-09-19
[ [ "Cheng", "Yujiao", "" ], [ "Zhao", "Weiye", "" ], [ "Liu", "Changliu", "" ], [ "Tomizuka", "Masayoshi", "" ] ]
Human motion prediction is an important component to facilitate human robot interaction. Robots need to accurately predict human's future movement in order to safely plan its own motion trajectories and efficiently collaborate with humans. Many recent approaches predict human's movement using deep learning methods, suc...
2309.06274
Alexander Fauck
Alexander Kleinsorge, Stefan Kupper, Alexander Fauck, Felix Rothe
ELRA: Exponential learning rate adaption gradient descent optimization method
9 pages, 11 figures
null
null
null
cs.LG math.OC
http://creativecommons.org/licenses/by-nc-sa/4.0/
We present a novel, fast (exponential rate adaption), ab initio (hyper-parameter-free) gradient based optimizer algorithm. The main idea of the method is to adapt the learning rate $\alpha$ by situational awareness, mainly striving for orthogonal neighboring gradients. The method has a high success and fast convergen...
[ { "created": "Tue, 12 Sep 2023 14:36:13 GMT", "version": "v1" } ]
2023-09-13
[ [ "Kleinsorge", "Alexander", "" ], [ "Kupper", "Stefan", "" ], [ "Fauck", "Alexander", "" ], [ "Rothe", "Felix", "" ] ]
We present a novel, fast (exponential rate adaption), ab initio (hyper-parameter-free) gradient based optimizer algorithm. The main idea of the method is to adapt the learning rate $\alpha$ by situational awareness, mainly striving for orthogonal neighboring gradients. The method has a high success and fast convergence...
1002.0270
Serge Samper
Pierre-Antoine Adragna (SYMME), Maurice Pillet (SYMME), Fabien Formosa (SYMME), Serge Samper (SYMME)
Inertial tolerancing and capability indices in an assembly production
null
Revue Internationale d Ingenierie Numerique 2, 1-2 (2006) 71-88
null
null
cs.OH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Traditional tolerancing considers the conformity of a batch when the batch satisfies the specifications. The characteristic is considered for itself and not according to its incidence in the assembly. Inertial tolerancing proposes another alternative of tolerancing in order to guarantee the final assembly characteris...
[ { "created": "Mon, 1 Feb 2010 15:10:56 GMT", "version": "v1" } ]
2010-02-02
[ [ "Adragna", "Pierre-Antoine", "", "SYMME" ], [ "Pillet", "Maurice", "", "SYMME" ], [ "Formosa", "Fabien", "", "SYMME" ], [ "Samper", "Serge", "", "SYMME" ] ]
Traditional tolerancing considers the conformity of a batch when the batch satisfies the specifications. The characteristic is considered for itself and not according to its incidence in the assembly. Inertial tolerancing proposes another alternative of tolerancing in order to guarantee the final assembly characteristi...
1803.01400
Andreas R\"uckl\'e
Andreas R\"uckl\'e, Steffen Eger, Maxime Peyrard, Iryna Gurevych
Concatenated Power Mean Word Embeddings as Universal Cross-Lingual Sentence Representations
Experiments/plots added: Normalization + Figure 1 (dimensionality vs. performance)
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Average word embeddings are a common baseline for more sophisticated sentence embedding techniques. However, they typically fall short of the performances of more complex models such as InferSent. Here, we generalize the concept of average word embeddings to power mean word embeddings. We show that the concatenation ...
[ { "created": "Sun, 4 Mar 2018 18:42:05 GMT", "version": "v1" }, { "created": "Wed, 12 Sep 2018 14:08:34 GMT", "version": "v2" } ]
2018-09-13
[ [ "Rücklé", "Andreas", "" ], [ "Eger", "Steffen", "" ], [ "Peyrard", "Maxime", "" ], [ "Gurevych", "Iryna", "" ] ]
Average word embeddings are a common baseline for more sophisticated sentence embedding techniques. However, they typically fall short of the performances of more complex models such as InferSent. Here, we generalize the concept of average word embeddings to power mean word embeddings. We show that the concatenation of...
1604.02097
Bo Jiang
Bo Jiang, Daniel R. Figueiredo, Bruno Ribeiro, Don Towsley
On the Duration and Intensity of Competitions in Nonlinear P\'olya Urn Processes with Fitness
null
null
null
null
cs.PF math.PR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cumulative advantage (CA) refers to the notion that accumulated resources foster the accumulation of further resources in competitions, a phenomenon that has been empirically observed in various contexts. The oldest and arguably simplest mathematical model that embodies this general principle is the P\'olya urn proce...
[ { "created": "Wed, 6 Apr 2016 00:35:18 GMT", "version": "v1" }, { "created": "Wed, 13 Apr 2016 15:00:48 GMT", "version": "v2" }, { "created": "Fri, 7 Apr 2017 19:49:58 GMT", "version": "v3" } ]
2017-04-11
[ [ "Jiang", "Bo", "" ], [ "Figueiredo", "Daniel R.", "" ], [ "Ribeiro", "Bruno", "" ], [ "Towsley", "Don", "" ] ]
Cumulative advantage (CA) refers to the notion that accumulated resources foster the accumulation of further resources in competitions, a phenomenon that has been empirically observed in various contexts. The oldest and arguably simplest mathematical model that embodies this general principle is the P\'olya urn process...
2308.07054
James Price
James Price, Colm Connaughton
Distinguishing Risk Preferences using Repeated Gambles
null
null
null
null
cs.AI math.PR
http://creativecommons.org/licenses/by/4.0/
Sequences of repeated gambles provide an experimental tool to characterize the risk preferences of humans or artificial decision-making agents. The difficulty of this inference depends on factors including the details of the gambles offered and the number of iterations of the game played. In this paper we explore in ...
[ { "created": "Mon, 14 Aug 2023 10:27:58 GMT", "version": "v1" } ]
2023-08-15
[ [ "Price", "James", "" ], [ "Connaughton", "Colm", "" ] ]
Sequences of repeated gambles provide an experimental tool to characterize the risk preferences of humans or artificial decision-making agents. The difficulty of this inference depends on factors including the details of the gambles offered and the number of iterations of the game played. In this paper we explore in de...
1911.07346
Haichao Yu
Haichao Yu, Haoxiang Li, Honghui Shi, Thomas S. Huang, Gang Hua
Any-Precision Deep Neural Networks
AAAI 2021
null
null
null
cs.LG cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present any-precision deep neural networks (DNNs), which are trained with a new method that allows the learned DNNs to be flexible in numerical precision during inference. The same model in runtime can be flexibly and directly set to different bit-widths, by truncating the least significant bits, to support dynami...
[ { "created": "Sun, 17 Nov 2019 21:35:32 GMT", "version": "v1" }, { "created": "Fri, 15 Jan 2021 08:13:10 GMT", "version": "v2" } ]
2021-01-18
[ [ "Yu", "Haichao", "" ], [ "Li", "Haoxiang", "" ], [ "Shi", "Honghui", "" ], [ "Huang", "Thomas S.", "" ], [ "Hua", "Gang", "" ] ]
We present any-precision deep neural networks (DNNs), which are trained with a new method that allows the learned DNNs to be flexible in numerical precision during inference. The same model in runtime can be flexibly and directly set to different bit-widths, by truncating the least significant bits, to support dynamic ...
2206.03886
Aseem Srivastava
Aseem Srivastava, Tharun Suresh, Sarah Peregrine (Grin) Lord, Md. Shad Akhtar, Tanmoy Chakraborty
Counseling Summarization using Mental Health Knowledge Guided Utterance Filtering
Full paper accepted at KDD 2022 -- ADS Track
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
The psychotherapy intervention technique is a multifaceted conversation between a therapist and a patient. Unlike general clinical discussions, psychotherapy's core components (viz. symptoms) are hard to distinguish, thus becoming a complex problem to summarize later. A structured counseling conversation may contain ...
[ { "created": "Wed, 8 Jun 2022 13:38:47 GMT", "version": "v1" } ]
2022-06-09
[ [ "Srivastava", "Aseem", "", "Grin" ], [ "Suresh", "Tharun", "", "Grin" ], [ "Peregrine", "Sarah", "", "Grin" ], [ "Lord", "", "" ], [ "Akhtar", "Md. Shad", "" ], [ "Chakraborty", "Tanmoy", "" ] ]
The psychotherapy intervention technique is a multifaceted conversation between a therapist and a patient. Unlike general clinical discussions, psychotherapy's core components (viz. symptoms) are hard to distinguish, thus becoming a complex problem to summarize later. A structured counseling conversation may contain di...
1201.3976
Souvik Sengupta
Souvik Sengupta, Sandipan Sahu, Ranjan Dasgupta
Construction of Learning Path Using Ant Colony Optimization from a Frequent Pattern Graph
null
null
null
null
cs.OH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In an e-Learning system a learner may come across multiple unknown terms, which are generally hyperlinked, while reading a text definition or theory on any topic. It becomes even harder when one tries to understand those unknown terms through further such links and they again find some new terms that have new links. ...
[ { "created": "Thu, 19 Jan 2012 06:09:53 GMT", "version": "v1" } ]
2012-01-20
[ [ "Sengupta", "Souvik", "" ], [ "Sahu", "Sandipan", "" ], [ "Dasgupta", "Ranjan", "" ] ]
In an e-Learning system a learner may come across multiple unknown terms, which are generally hyperlinked, while reading a text definition or theory on any topic. It becomes even harder when one tries to understand those unknown terms through further such links and they again find some new terms that have new links. As...
2406.12034
Junmo Kang
Junmo Kang, Leonid Karlinsky, Hongyin Luo, Zhen Wang, Jacob Hansen, James Glass, David Cox, Rameswar Panda, Rogerio Feris, Alan Ritter
Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts
null
null
null
null
cs.CL cs.LG
http://creativecommons.org/licenses/by-sa/4.0/
We present Self-MoE, an approach that transforms a monolithic LLM into a compositional, modular system of self-specialized experts, named MiXSE (MiXture of Self-specialized Experts). Our approach leverages self-specialization, which constructs expert modules using self-generated synthetic data, each equipped with a s...
[ { "created": "Mon, 17 Jun 2024 19:06:54 GMT", "version": "v1" } ]
2024-06-19
[ [ "Kang", "Junmo", "" ], [ "Karlinsky", "Leonid", "" ], [ "Luo", "Hongyin", "" ], [ "Wang", "Zhen", "" ], [ "Hansen", "Jacob", "" ], [ "Glass", "James", "" ], [ "Cox", "David", "" ], [ "Panda", "R...
We present Self-MoE, an approach that transforms a monolithic LLM into a compositional, modular system of self-specialized experts, named MiXSE (MiXture of Self-specialized Experts). Our approach leverages self-specialization, which constructs expert modules using self-generated synthetic data, each equipped with a sha...
1910.06228
Tommaso Bianchi
Andrea Celli, Alberto Marchesi, Tommaso Bianchi, Nicola Gatti
Learning to Correlate in Multi-Player General-Sum Sequential Games
null
null
null
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the context of multi-player, general-sum games, there is an increasing interest in solution concepts modeling some form of communication among players, since they can lead to socially better outcomes with respect to Nash equilibria, and may be reached through learning dynamics in a decentralized fashion. In this p...
[ { "created": "Mon, 14 Oct 2019 15:55:33 GMT", "version": "v1" } ]
2019-10-15
[ [ "Celli", "Andrea", "" ], [ "Marchesi", "Alberto", "" ], [ "Bianchi", "Tommaso", "" ], [ "Gatti", "Nicola", "" ] ]
In the context of multi-player, general-sum games, there is an increasing interest in solution concepts modeling some form of communication among players, since they can lead to socially better outcomes with respect to Nash equilibria, and may be reached through learning dynamics in a decentralized fashion. In this pap...