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2112.10194
Dima Damen
Will Price, Carl Vondrick, Dima Damen
UnweaveNet: Unweaving Activity Stories
Accepted at IEEE/CVF Computer Vision and Pattern Recognition (CVPR) 2022
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Our lives can be seen as a complex weaving of activities; we switch from one activity to another, to maximise our achievements or in reaction to demands placed upon us. Observing a video of unscripted daily activities, we parse the video into its constituent activity threads through a process we call unweaving. To ac...
[ { "created": "Sun, 19 Dec 2021 17:07:37 GMT", "version": "v1" }, { "created": "Mon, 4 Apr 2022 11:33:49 GMT", "version": "v2" } ]
2022-04-05
[ [ "Price", "Will", "" ], [ "Vondrick", "Carl", "" ], [ "Damen", "Dima", "" ] ]
Our lives can be seen as a complex weaving of activities; we switch from one activity to another, to maximise our achievements or in reaction to demands placed upon us. Observing a video of unscripted daily activities, we parse the video into its constituent activity threads through a process we call unweaving. To acco...
1010.2993
Omur Ozel
Jing Yang, Omur Ozel, Sennur Ulukus
Broadcasting with an Energy Harvesting Rechargeable Transmitter
Submitted to IEEE Transactions on Wireless Communications, October 2010
null
10.1109/TWC.2011.120911.101813
null
cs.IT cs.NI math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we investigate the transmission completion time minimization problem in a two-user additive white Gaussian noise (AWGN) broadcast channel, where the transmitter is able to harvest energy from the nature, using a rechargeable battery. The harvested energy is modeled to arrive at the transmitter randomly...
[ { "created": "Thu, 14 Oct 2010 17:58:12 GMT", "version": "v1" } ]
2016-11-15
[ [ "Yang", "Jing", "" ], [ "Ozel", "Omur", "" ], [ "Ulukus", "Sennur", "" ] ]
In this paper, we investigate the transmission completion time minimization problem in a two-user additive white Gaussian noise (AWGN) broadcast channel, where the transmitter is able to harvest energy from the nature, using a rechargeable battery. The harvested energy is modeled to arrive at the transmitter randomly d...
2212.00423
Kim Bjerge
Kim Bjerge, Carsten Eie Frigaard and Henrik Karstoft
Motion Informed Object Detection of Small Insects in Time-lapse Camera Recordings
10 pages, 6 figures
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by-nc-nd/4.0/
Insects as pollinators play a crucial role in ecosystem management and world food production. However, insect populations are declining, calling for efficient methods of insect monitoring. Existing methods analyze video or time-lapse images of insects in nature, but the analysis is challenging since insects are small...
[ { "created": "Thu, 1 Dec 2022 10:54:06 GMT", "version": "v1" }, { "created": "Thu, 29 Jun 2023 15:01:00 GMT", "version": "v2" } ]
2023-06-30
[ [ "Bjerge", "Kim", "" ], [ "Frigaard", "Carsten Eie", "" ], [ "Karstoft", "Henrik", "" ] ]
Insects as pollinators play a crucial role in ecosystem management and world food production. However, insect populations are declining, calling for efficient methods of insect monitoring. Existing methods analyze video or time-lapse images of insects in nature, but the analysis is challenging since insects are small o...
2406.11245
Qiong Wu
Kangwei Qi, Qiong Wu, Pingyi Fan, Nan Cheng, Wen Chen, Jiangzhou Wang and Khaled B. Letaief
Deep-Reinforcement-Learning-Based AoI-Aware Resource Allocation for RIS-Aided IoV Networks
This paper has been submitted to IEEE Journal. The source code has been released at https://github.com/qiongwu86/RIS-RB-AoI-V2X-DRL.git
null
null
null
cs.LG cs.DC cs.NI eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Reconfigurable Intelligent Surface (RIS) is a pivotal technology in communication, offering an alternative path that significantly enhances the link quality in wireless communication environments. In this paper, we propose a RIS-assisted internet of vehicles (IoV) network, considering the vehicle-to-everything (V2X) ...
[ { "created": "Mon, 17 Jun 2024 06:16:07 GMT", "version": "v1" } ]
2024-06-18
[ [ "Qi", "Kangwei", "" ], [ "Wu", "Qiong", "" ], [ "Fan", "Pingyi", "" ], [ "Cheng", "Nan", "" ], [ "Chen", "Wen", "" ], [ "Wang", "Jiangzhou", "" ], [ "Letaief", "Khaled B.", "" ] ]
Reconfigurable Intelligent Surface (RIS) is a pivotal technology in communication, offering an alternative path that significantly enhances the link quality in wireless communication environments. In this paper, we propose a RIS-assisted internet of vehicles (IoV) network, considering the vehicle-to-everything (V2X) co...
1610.08167
EPTCS
Vladimir Klebanov (KIT), Alexander Weigl (KIT), J\"org Weisbarth
Sound Probabilistic #SAT with Projection
In Proceedings QAPL'16, arXiv:1610.07696
EPTCS 227, 2016, pp. 15-29
10.4204/EPTCS.227.2
null
cs.LO cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present an improved method for a sound probabilistic estimation of the model count of a boolean formula under projection. The problem solved can be used to encode a variety of quantitative program analyses, such as concerning security of resource consumption. We implement the technique and discuss its application ...
[ { "created": "Wed, 26 Oct 2016 05:00:04 GMT", "version": "v1" } ]
2016-10-27
[ [ "Klebanov", "Vladimir", "", "KIT" ], [ "Weigl", "Alexander", "", "KIT" ], [ "Weisbarth", "Jörg", "" ] ]
We present an improved method for a sound probabilistic estimation of the model count of a boolean formula under projection. The problem solved can be used to encode a variety of quantitative program analyses, such as concerning security of resource consumption. We implement the technique and discuss its application to...
1309.2399
Pavel Klav\'ik
Steven Chaplick, Radoslav Fulek, Pavel Klav\'ik
Extending Partial Representations of Circle Graphs
null
null
null
null
cs.DM math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The partial representation extension problem is a recently introduced generalization of the recognition problem. A circle graph is an intersection graph of chords of a circle. We study the partial representation extension problem for circle graphs, where the input consists of a graph $G$ and a partial representation ...
[ { "created": "Tue, 10 Sep 2013 07:50:41 GMT", "version": "v1" }, { "created": "Sat, 30 Sep 2017 20:27:30 GMT", "version": "v2" } ]
2017-10-03
[ [ "Chaplick", "Steven", "" ], [ "Fulek", "Radoslav", "" ], [ "Klavík", "Pavel", "" ] ]
The partial representation extension problem is a recently introduced generalization of the recognition problem. A circle graph is an intersection graph of chords of a circle. We study the partial representation extension problem for circle graphs, where the input consists of a graph $G$ and a partial representation $\...
2305.16174
Claudio Battiloro Mr
Claudio Battiloro, Indro Spinelli, Lev Telyatnikov, Michael Bronstein, Simone Scardapane, Paolo Di Lorenzo
From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module
Under review. 17 pages, 5 figures
null
null
null
cs.LG cs.AI cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Latent Graph Inference (LGI) relaxed the reliance of Graph Neural Networks (GNNs) on a given graph topology by dynamically learning it. However, most of LGI methods assume to have a (noisy, incomplete, improvable, ...) input graph to rewire and can solely learn regular graph topologies. In the wake of the success of ...
[ { "created": "Thu, 25 May 2023 15:33:19 GMT", "version": "v1" }, { "created": "Thu, 3 Aug 2023 13:46:09 GMT", "version": "v2" } ]
2023-08-04
[ [ "Battiloro", "Claudio", "" ], [ "Spinelli", "Indro", "" ], [ "Telyatnikov", "Lev", "" ], [ "Bronstein", "Michael", "" ], [ "Scardapane", "Simone", "" ], [ "Di Lorenzo", "Paolo", "" ] ]
Latent Graph Inference (LGI) relaxed the reliance of Graph Neural Networks (GNNs) on a given graph topology by dynamically learning it. However, most of LGI methods assume to have a (noisy, incomplete, improvable, ...) input graph to rewire and can solely learn regular graph topologies. In the wake of the success of To...
2002.01642
Osman Tursun
Osman Tursun, Simon Denman, Sridha Sridharan and Clinton Fookes
Learning Test-time Augmentation for Content-based Image Retrieval
null
null
10.1016/j.cviu.2022.103494
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Off-the-shelf convolutional neural network features achieve outstanding results in many image retrieval tasks. However, their invariance to target data is pre-defined by the network architecture and training data. Existing image retrieval approaches require fine-tuning or modification of pre-trained networks to adapt...
[ { "created": "Wed, 5 Feb 2020 05:08:41 GMT", "version": "v1" }, { "created": "Fri, 18 Dec 2020 07:54:06 GMT", "version": "v2" }, { "created": "Mon, 8 Feb 2021 06:32:56 GMT", "version": "v3" }, { "created": "Thu, 12 Aug 2021 06:05:48 GMT", "version": "v4" }, { "cre...
2022-07-26
[ [ "Tursun", "Osman", "" ], [ "Denman", "Simon", "" ], [ "Sridharan", "Sridha", "" ], [ "Fookes", "Clinton", "" ] ]
Off-the-shelf convolutional neural network features achieve outstanding results in many image retrieval tasks. However, their invariance to target data is pre-defined by the network architecture and training data. Existing image retrieval approaches require fine-tuning or modification of pre-trained networks to adapt t...
2302.00894
Nankai Lin
Xiaotian Lin, Nankai Lin, Yingwen Fu, Ziyu Yang and Shengyi Jiang
How to choose "Good" Samples for Text Data Augmentation
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep learning-based text classification models need abundant labeled data to obtain competitive performance. Unfortunately, annotating large-size corpus is time-consuming and laborious. To tackle this, multiple researches try to use data augmentation to expand the corpus size. However, data augmentation may potential...
[ { "created": "Thu, 2 Feb 2023 06:01:50 GMT", "version": "v1" } ]
2023-02-03
[ [ "Lin", "Xiaotian", "" ], [ "Lin", "Nankai", "" ], [ "Fu", "Yingwen", "" ], [ "Yang", "Ziyu", "" ], [ "Jiang", "Shengyi", "" ] ]
Deep learning-based text classification models need abundant labeled data to obtain competitive performance. Unfortunately, annotating large-size corpus is time-consuming and laborious. To tackle this, multiple researches try to use data augmentation to expand the corpus size. However, data augmentation may potentially...
2208.04632
EPTCS
Luc Edixhoven (Open University (Heerlen) and CWI (Amsterdam), Netherlands), Sung-Shik Jongmans (Open University (Heerlen) and CWI (Amsterdam), Netherlands), Jos\'e Proen\c{c}a (CISTER, ISEP, Polytechnic Institute of Porto, Portugal), Guillermina Cledou (HASLab, INESC TEC and University of Minho, Portugal)
Branching Pomsets for Choreographies
In Proceedings ICE 2022, arXiv:2208.04086
EPTCS 365, 2022, pp. 37-52
10.4204/EPTCS.365.3
null
cs.PL cs.LO
http://creativecommons.org/licenses/by/4.0/
Choreographic languages describe possible sequences of interactions among a set of agents. Typical models are based on languages or automata over sending and receiving actions. Pomsets provide a more compact alternative by using a partial order over these actions and by not making explicit the possible interleaving o...
[ { "created": "Tue, 9 Aug 2022 09:53:35 GMT", "version": "v1" } ]
2022-08-10
[ [ "Edixhoven", "Luc", "", "Open University" ], [ "Jongmans", "Sung-Shik", "", "Open University" ], [ "Proença", "José", "", "CISTER, ISEP, Polytechnic\n Institute of Porto, Portugal" ], [ "Cledou", "Guillermina", "", "HASLab, INESC TEC and...
Choreographic languages describe possible sequences of interactions among a set of agents. Typical models are based on languages or automata over sending and receiving actions. Pomsets provide a more compact alternative by using a partial order over these actions and by not making explicit the possible interleaving of ...
2407.11549
Yin Jou Huang
Yin Jou Huang and Rafik Hadfi
How Personality Traits Influence Negotiation Outcomes? A Simulation based on Large Language Models
13 pages, 4 figures
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by-nc-sa/4.0/
Psychological evidence reveals the influence of personality traits on decision-making. For instance, agreeableness is generally associated with positive outcomes in negotiations, whereas neuroticism is often linked to less favorable outcomes. This paper introduces a simulation framework centered on Large Language Mod...
[ { "created": "Tue, 16 Jul 2024 09:52:51 GMT", "version": "v1" } ]
2024-07-17
[ [ "Huang", "Yin Jou", "" ], [ "Hadfi", "Rafik", "" ] ]
Psychological evidence reveals the influence of personality traits on decision-making. For instance, agreeableness is generally associated with positive outcomes in negotiations, whereas neuroticism is often linked to less favorable outcomes. This paper introduces a simulation framework centered on Large Language Model...
2405.01144
Niousha Nazemi
Niousha Nazemi, Omid Tavallaie, Shuaijun Chen, Albert Y. Zomaya, Ralph Holz
Boosting Communication Efficiency of Federated Learning's Secure Aggregation
2 pages, 4 figures, The 54th Annual IEEE/IFIP International Conference on Dependable Systems and Networks
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Federated Learning (FL) is a decentralized machine learning approach where client devices train models locally and send them to a server that performs aggregation to generate a global model. FL is vulnerable to model inversion attacks, where the server can infer sensitive client data from trained models. Google's Sec...
[ { "created": "Thu, 2 May 2024 10:00:16 GMT", "version": "v1" } ]
2024-05-03
[ [ "Nazemi", "Niousha", "" ], [ "Tavallaie", "Omid", "" ], [ "Chen", "Shuaijun", "" ], [ "Zomaya", "Albert Y.", "" ], [ "Holz", "Ralph", "" ] ]
Federated Learning (FL) is a decentralized machine learning approach where client devices train models locally and send them to a server that performs aggregation to generate a global model. FL is vulnerable to model inversion attacks, where the server can infer sensitive client data from trained models. Google's Secur...
1604.02714
Krasimir Yordzhev
Krasimir Yordzhev
Canonical binary matrices related to bipartite graphs
null
null
null
null
cs.DM math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The current paper is dedicated to the problem of finding the number of mutually non isomorphic bipartite graphs of the type $g=\langle R_g ,C_g ,E_g \rangle$ at given $n=|R_g |$ and $m=|C_g |$, where $R_g$ and $C_g$ are the two disjoint parts of the vertices of the graphs $g$, and $E_g$ is the set of edges, $Eg \subs...
[ { "created": "Sun, 10 Apr 2016 16:51:48 GMT", "version": "v1" } ]
2016-04-12
[ [ "Yordzhev", "Krasimir", "" ] ]
The current paper is dedicated to the problem of finding the number of mutually non isomorphic bipartite graphs of the type $g=\langle R_g ,C_g ,E_g \rangle$ at given $n=|R_g |$ and $m=|C_g |$, where $R_g$ and $C_g$ are the two disjoint parts of the vertices of the graphs $g$, and $E_g$ is the set of edges, $Eg \subset...
2307.00527
Zhong Li
Zhong Li, Jiayang Shi, Matthijs van Leeuwen
Graph Neural Networks based Log Anomaly Detection and Explanation
Technical Report (A short version was accepted by ICSE'24 poster track)
null
null
null
cs.SE cs.AI cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
Event logs are widely used to record the status of high-tech systems, making log anomaly detection important for monitoring those systems. Most existing log anomaly detection methods take a log event count matrix or log event sequences as input, exploiting quantitative and/or sequential relationships between log even...
[ { "created": "Sun, 2 Jul 2023 09:38:43 GMT", "version": "v1" }, { "created": "Fri, 13 Oct 2023 08:58:34 GMT", "version": "v2" }, { "created": "Wed, 24 Jan 2024 10:48:54 GMT", "version": "v3" } ]
2024-01-25
[ [ "Li", "Zhong", "" ], [ "Shi", "Jiayang", "" ], [ "van Leeuwen", "Matthijs", "" ] ]
Event logs are widely used to record the status of high-tech systems, making log anomaly detection important for monitoring those systems. Most existing log anomaly detection methods take a log event count matrix or log event sequences as input, exploiting quantitative and/or sequential relationships between log events...
2110.12425
Jiashuo Liu
Jiashuo Liu, Zheyuan Hu, Peng Cui, Bo Li, Zheyan Shen
Kernelized Heterogeneous Risk Minimization
35th Conference on Neural Information Processing Systems (NeurIPS 2021), Sydney, Australia. arXiv admin note: text overlap with arXiv:2105.03818
null
null
17
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The ability to generalize under distributional shifts is essential to reliable machine learning, while models optimized with empirical risk minimization usually fail on non-$i.i.d$ testing data. Recently, invariant learning methods for out-of-distribution (OOD) generalization propose to find causally invariant relati...
[ { "created": "Sun, 24 Oct 2021 12:26:50 GMT", "version": "v1" } ]
2021-10-26
[ [ "Liu", "Jiashuo", "" ], [ "Hu", "Zheyuan", "" ], [ "Cui", "Peng", "" ], [ "Li", "Bo", "" ], [ "Shen", "Zheyan", "" ] ]
The ability to generalize under distributional shifts is essential to reliable machine learning, while models optimized with empirical risk minimization usually fail on non-$i.i.d$ testing data. Recently, invariant learning methods for out-of-distribution (OOD) generalization propose to find causally invariant relation...
2306.06578
Weizhe Chen
Weizhe Chen and Lantao Liu
Long-Term Autonomous Ocean Monitoring with Streaming Samples
Proceedings of OCEANS 2019, SEATTLE
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
In the autonomous ocean monitoring task, the sampling robot moves in the environment and accumulates data continuously. The widely adopted spatial modeling method - standard Gaussian process (GP) regression - becomes inadequate in processing the growing sensing data of a large size. To overcome the computational chal...
[ { "created": "Sun, 11 Jun 2023 03:59:26 GMT", "version": "v1" } ]
2023-06-13
[ [ "Chen", "Weizhe", "" ], [ "Liu", "Lantao", "" ] ]
In the autonomous ocean monitoring task, the sampling robot moves in the environment and accumulates data continuously. The widely adopted spatial modeling method - standard Gaussian process (GP) regression - becomes inadequate in processing the growing sensing data of a large size. To overcome the computational challe...
2406.10450
Haohao Qu
Haohao Qu, Wenqi Fan, Zihuai Zhao, Qing Li
TokenRec: Learning to Tokenize ID for LLM-based Generative Recommendation
null
null
null
null
cs.IR cs.AI cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
There is a growing interest in utilizing large-scale language models (LLMs) to advance next-generation Recommender Systems (RecSys), driven by their outstanding language understanding and in-context learning capabilities. In this scenario, tokenizing (i.e., indexing) users and items becomes essential for ensuring a s...
[ { "created": "Sat, 15 Jun 2024 00:07:44 GMT", "version": "v1" } ]
2024-06-18
[ [ "Qu", "Haohao", "" ], [ "Fan", "Wenqi", "" ], [ "Zhao", "Zihuai", "" ], [ "Li", "Qing", "" ] ]
There is a growing interest in utilizing large-scale language models (LLMs) to advance next-generation Recommender Systems (RecSys), driven by their outstanding language understanding and in-context learning capabilities. In this scenario, tokenizing (i.e., indexing) users and items becomes essential for ensuring a sea...
2004.14107
He Wang
Feixiang He, Yuanhang Xiang, Xi Zhao, He Wang
Informative Scene Decomposition for Crowd Analysis, Comparison and Simulation Guidance
accepted in SIGGRAPH 2020
null
null
null
cs.GR cs.CV cs.LG cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Crowd simulation is a central topic in several fields including graphics. To achieve high-fidelity simulations, data has been increasingly relied upon for analysis and simulation guidance. However, the information in real-world data is often noisy, mixed and unstructured, making it difficult for effective analysis, t...
[ { "created": "Wed, 29 Apr 2020 12:03:32 GMT", "version": "v1" } ]
2020-04-30
[ [ "He", "Feixiang", "" ], [ "Xiang", "Yuanhang", "" ], [ "Zhao", "Xi", "" ], [ "Wang", "He", "" ] ]
Crowd simulation is a central topic in several fields including graphics. To achieve high-fidelity simulations, data has been increasingly relied upon for analysis and simulation guidance. However, the information in real-world data is often noisy, mixed and unstructured, making it difficult for effective analysis, the...
2011.06922
Yoav Shalev
Yoav Shalev, Lior Wolf
Image Animation with Perturbed Masks
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
We present a novel approach for image-animation of a source image by a driving video, both depicting the same type of object. We do not assume the existence of pose models and our method is able to animate arbitrary objects without the knowledge of the object's structure. Furthermore, both, the driving video and the ...
[ { "created": "Fri, 13 Nov 2020 14:17:17 GMT", "version": "v1" }, { "created": "Wed, 18 Nov 2020 19:23:52 GMT", "version": "v2" }, { "created": "Tue, 29 Mar 2022 09:30:26 GMT", "version": "v3" } ]
2022-03-30
[ [ "Shalev", "Yoav", "" ], [ "Wolf", "Lior", "" ] ]
We present a novel approach for image-animation of a source image by a driving video, both depicting the same type of object. We do not assume the existence of pose models and our method is able to animate arbitrary objects without the knowledge of the object's structure. Furthermore, both, the driving video and the so...
2208.04980
Christopher Perez
Christopher Perez, Sayar Karmakar
An NLP-Assisted Bayesian Time Series Analysis for Prevalence of Twitter Cyberbullying During the COVID-19 Pandemic
22 pages, 15 figures
null
null
null
cs.SI cs.LG stat.AP
http://creativecommons.org/licenses/by/4.0/
COVID-19 has brought about many changes in social dynamics. Stay-at-home orders and disruptions in school teaching can influence bullying behavior in-person and online, both of which leading to negative outcomes in victims. To study cyberbullying specifically, 1 million tweets containing keywords associated with abus...
[ { "created": "Sat, 23 Jul 2022 15:24:07 GMT", "version": "v1" }, { "created": "Wed, 1 Mar 2023 01:02:23 GMT", "version": "v2" } ]
2023-03-02
[ [ "Perez", "Christopher", "" ], [ "Karmakar", "Sayar", "" ] ]
COVID-19 has brought about many changes in social dynamics. Stay-at-home orders and disruptions in school teaching can influence bullying behavior in-person and online, both of which leading to negative outcomes in victims. To study cyberbullying specifically, 1 million tweets containing keywords associated with abuse ...
2306.07075
John Nay
John J. Nay, David Karamardian, Sarah B. Lawsky, Wenting Tao, Meghana Bhat, Raghav Jain, Aaron Travis Lee, Jonathan H. Choi, Jungo Kasai
Large Language Models as Tax Attorneys: A Case Study in Legal Capabilities Emergence
null
null
null
null
cs.CL cs.AI cs.CY
http://creativecommons.org/licenses/by/4.0/
Better understanding of Large Language Models' (LLMs) legal analysis abilities can contribute to improving the efficiency of legal services, governing artificial intelligence, and leveraging LLMs to identify inconsistencies in law. This paper explores LLM capabilities in applying tax law. We choose this area of law b...
[ { "created": "Mon, 12 Jun 2023 12:40:48 GMT", "version": "v1" } ]
2023-06-13
[ [ "Nay", "John J.", "" ], [ "Karamardian", "David", "" ], [ "Lawsky", "Sarah B.", "" ], [ "Tao", "Wenting", "" ], [ "Bhat", "Meghana", "" ], [ "Jain", "Raghav", "" ], [ "Lee", "Aaron Travis", "" ], [ ...
Better understanding of Large Language Models' (LLMs) legal analysis abilities can contribute to improving the efficiency of legal services, governing artificial intelligence, and leveraging LLMs to identify inconsistencies in law. This paper explores LLM capabilities in applying tax law. We choose this area of law bec...
1911.10038
Matej Ul\v{c}ar
Matej Ul\v{c}ar, Kristiina Vaik, Jessica Lindstr\"om, Milda Dailid\.enait\.e, Marko Robnik-\v{S}ikonja
Multilingual Culture-Independent Word Analogy Datasets
7 pages, LREC2020 conference
Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), pages 4074-4080
null
null
cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
In text processing, deep neural networks mostly use word embeddings as an input. Embeddings have to ensure that relations between words are reflected through distances in a high-dimensional numeric space. To compare the quality of different text embeddings, typically, we use benchmark datasets. We present a collectio...
[ { "created": "Fri, 22 Nov 2019 13:39:06 GMT", "version": "v1" }, { "created": "Fri, 27 Mar 2020 15:32:16 GMT", "version": "v2" } ]
2022-06-01
[ [ "Ulčar", "Matej", "" ], [ "Vaik", "Kristiina", "" ], [ "Lindström", "Jessica", "" ], [ "Dailidėnaitė", "Milda", "" ], [ "Robnik-Šikonja", "Marko", "" ] ]
In text processing, deep neural networks mostly use word embeddings as an input. Embeddings have to ensure that relations between words are reflected through distances in a high-dimensional numeric space. To compare the quality of different text embeddings, typically, we use benchmark datasets. We present a collection ...
2001.06452
Jingxuan Huang
Jingxuan Huang, Zesong Fei, Congzhe Cao, and Ming Xiao
Design and Analysis of Online Fountain Codes for Intermediate Performance
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
For the benefit of improved intermediate performance, recently online fountain codes attract much research attention. However, there is a trade-off between the intermediate performance and the full recovery overhead for online fountain codes, which prevents them to be improved simultaneously. We analyze this trade-of...
[ { "created": "Fri, 17 Jan 2020 17:52:55 GMT", "version": "v1" } ]
2020-01-20
[ [ "Huang", "Jingxuan", "" ], [ "Fei", "Zesong", "" ], [ "Cao", "Congzhe", "" ], [ "Xiao", "Ming", "" ] ]
For the benefit of improved intermediate performance, recently online fountain codes attract much research attention. However, there is a trade-off between the intermediate performance and the full recovery overhead for online fountain codes, which prevents them to be improved simultaneously. We analyze this trade-off,...
1905.13662
Francesco Locatello
Francesco Locatello, Gabriele Abbati, Tom Rainforth, Stefan Bauer, Bernhard Sch\"olkopf, Olivier Bachem
On the Fairness of Disentangled Representations
null
NeurIPS 2019
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently there has been a significant interest in learning disentangled representations, as they promise increased interpretability, generalization to unseen scenarios and faster learning on downstream tasks. In this paper, we investigate the usefulness of different notions of disentanglement for improving the fairne...
[ { "created": "Fri, 31 May 2019 15:03:12 GMT", "version": "v1" }, { "created": "Tue, 29 Oct 2019 10:56:08 GMT", "version": "v2" } ]
2019-10-30
[ [ "Locatello", "Francesco", "" ], [ "Abbati", "Gabriele", "" ], [ "Rainforth", "Tom", "" ], [ "Bauer", "Stefan", "" ], [ "Schölkopf", "Bernhard", "" ], [ "Bachem", "Olivier", "" ] ]
Recently there has been a significant interest in learning disentangled representations, as they promise increased interpretability, generalization to unseen scenarios and faster learning on downstream tasks. In this paper, we investigate the usefulness of different notions of disentanglement for improving the fairness...
2303.13076
Xiaoshi Wu
Xiaoshi Wu, Feng Zhu, Rui Zhao, Hongsheng Li
CORA: Adapting CLIP for Open-Vocabulary Detection with Region Prompting and Anchor Pre-Matching
11 pages, 4 figures. Accepted by CVPR 2023
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by/4.0/
Open-vocabulary detection (OVD) is an object detection task aiming at detecting objects from novel categories beyond the base categories on which the detector is trained. Recent OVD methods rely on large-scale visual-language pre-trained models, such as CLIP, for recognizing novel objects. We identify the two core ob...
[ { "created": "Thu, 23 Mar 2023 07:13:57 GMT", "version": "v1" } ]
2023-03-24
[ [ "Wu", "Xiaoshi", "" ], [ "Zhu", "Feng", "" ], [ "Zhao", "Rui", "" ], [ "Li", "Hongsheng", "" ] ]
Open-vocabulary detection (OVD) is an object detection task aiming at detecting objects from novel categories beyond the base categories on which the detector is trained. Recent OVD methods rely on large-scale visual-language pre-trained models, such as CLIP, for recognizing novel objects. We identify the two core obst...
1904.07965
Fabrizio Sebastiani
Andrea Esuli, Alejandro Moreo, Fabrizio Sebastiani
Cross-Lingual Sentiment Quantification
Identical to previous version, but for the abstract, which is now identical to the one in the published version
Final version published in IEEE Intelligent Systems 35(3):106-114, 2020
10.1109/MIS.2020.2979203
null
cs.LG cs.IR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
\emph{Sentiment Quantification} (i.e., the task of estimating the relative frequency of sentiment-related classes -- such as \textsf{Positive} and \textsf{Negative} -- in a set of unlabelled documents) is an important topic in sentiment analysis, as the study of sentiment-related quantities and trends across a popula...
[ { "created": "Tue, 16 Apr 2019 20:32:02 GMT", "version": "v1" }, { "created": "Tue, 7 Jul 2020 13:50:58 GMT", "version": "v2" } ]
2021-09-22
[ [ "Esuli", "Andrea", "" ], [ "Moreo", "Alejandro", "" ], [ "Sebastiani", "Fabrizio", "" ] ]
\emph{Sentiment Quantification} (i.e., the task of estimating the relative frequency of sentiment-related classes -- such as \textsf{Positive} and \textsf{Negative} -- in a set of unlabelled documents) is an important topic in sentiment analysis, as the study of sentiment-related quantities and trends across a populati...
1511.06468
Di Wang
Di Wang, Michael Mahoney, Nishanth Mohan, Satish Rao
Faster Parallel Solver for Positive Linear Programs via Dynamically-Bucketed Selective Coordinate Descent
null
null
null
null
cs.DS cs.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We provide improved parallel approximation algorithms for the important class of packing and covering linear programs. In particular, we present new parallel $\epsilon$-approximate packing and covering solvers which run in $\tilde{O}(1/\epsilon^2)$ expected time, i.e., in expectation they take $\tilde{O}(1/\epsilon^2...
[ { "created": "Fri, 20 Nov 2015 01:10:13 GMT", "version": "v1" } ]
2015-11-23
[ [ "Wang", "Di", "" ], [ "Mahoney", "Michael", "" ], [ "Mohan", "Nishanth", "" ], [ "Rao", "Satish", "" ] ]
We provide improved parallel approximation algorithms for the important class of packing and covering linear programs. In particular, we present new parallel $\epsilon$-approximate packing and covering solvers which run in $\tilde{O}(1/\epsilon^2)$ expected time, i.e., in expectation they take $\tilde{O}(1/\epsilon^2)$...
2006.07228
Tao Sun
Mohammad Rasouli, Tao Sun, Ram Rajagopal
FedGAN: Federated Generative Adversarial Networks for Distributed Data
23 pages, 10 figures
null
null
null
cs.LG cs.CV cs.MA stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose Federated Generative Adversarial Network (FedGAN) for training a GAN across distributed sources of non-independent-and-identically-distributed data sources subject to communication and privacy constraints. Our algorithm uses local generators and discriminators which are periodically synced via an intermedi...
[ { "created": "Fri, 12 Jun 2020 14:36:43 GMT", "version": "v1" }, { "created": "Mon, 15 Jun 2020 06:38:12 GMT", "version": "v2" } ]
2020-06-16
[ [ "Rasouli", "Mohammad", "" ], [ "Sun", "Tao", "" ], [ "Rajagopal", "Ram", "" ] ]
We propose Federated Generative Adversarial Network (FedGAN) for training a GAN across distributed sources of non-independent-and-identically-distributed data sources subject to communication and privacy constraints. Our algorithm uses local generators and discriminators which are periodically synced via an intermediar...
1410.6142
Mark Riedl
Mark O. Riedl
The Lovelace 2.0 Test of Artificial Creativity and Intelligence
2 pages
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Observing that the creation of certain types of artistic artifacts necessitate intelligence, we present the Lovelace 2.0 Test of creativity as an alternative to the Turing Test as a means of determining whether an agent is intelligent. The Lovelace 2.0 Test builds off prior tests of creativity and additionally provid...
[ { "created": "Wed, 22 Oct 2014 18:59:31 GMT", "version": "v1" }, { "created": "Thu, 23 Oct 2014 15:09:53 GMT", "version": "v2" }, { "created": "Mon, 22 Dec 2014 03:24:06 GMT", "version": "v3" } ]
2014-12-23
[ [ "Riedl", "Mark O.", "" ] ]
Observing that the creation of certain types of artistic artifacts necessitate intelligence, we present the Lovelace 2.0 Test of creativity as an alternative to the Turing Test as a means of determining whether an agent is intelligent. The Lovelace 2.0 Test builds off prior tests of creativity and additionally provides...
2312.02445
Jiayi Liao
Jiayi Liao, Sihang Li, Zhengyi Yang, Jiancan Wu, Yancheng Yuan, Xiang Wang, Xiangnan He
LLaRA: Large Language-Recommendation Assistant
11 pages, 5 figures
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sequential recommendation aims to predict users' next interaction with items based on their past engagement sequence. Recently, the advent of Large Language Models (LLMs) has sparked interest in leveraging them for sequential recommendation, viewing it as language modeling. Previous studies represent items within LLM...
[ { "created": "Tue, 5 Dec 2023 02:53:46 GMT", "version": "v1" }, { "created": "Sun, 31 Dec 2023 05:09:01 GMT", "version": "v2" }, { "created": "Tue, 9 Apr 2024 09:53:04 GMT", "version": "v3" }, { "created": "Sat, 4 May 2024 10:44:33 GMT", "version": "v4" } ]
2024-05-07
[ [ "Liao", "Jiayi", "" ], [ "Li", "Sihang", "" ], [ "Yang", "Zhengyi", "" ], [ "Wu", "Jiancan", "" ], [ "Yuan", "Yancheng", "" ], [ "Wang", "Xiang", "" ], [ "He", "Xiangnan", "" ] ]
Sequential recommendation aims to predict users' next interaction with items based on their past engagement sequence. Recently, the advent of Large Language Models (LLMs) has sparked interest in leveraging them for sequential recommendation, viewing it as language modeling. Previous studies represent items within LLMs'...
2203.16954
Wenlin Dai
Wenlin Dai, Changhe Song, Xiang Li, Zhiyong Wu, Huashan Pan, Xiulin Li, Helen Meng
An End-to-end Chinese Text Normalization Model based on Rule-guided Flat-Lattice Transformer
Accepted by ICASSP 2022
null
null
null
cs.CL cs.SD eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Text normalization, defined as a procedure transforming non standard words to spoken-form words, is crucial to the intelligibility of synthesized speech in text-to-speech system. Rule-based methods without considering context can not eliminate ambiguation, whereas sequence-to-sequence neural network based methods suf...
[ { "created": "Thu, 31 Mar 2022 11:19:53 GMT", "version": "v1" } ]
2022-04-01
[ [ "Dai", "Wenlin", "" ], [ "Song", "Changhe", "" ], [ "Li", "Xiang", "" ], [ "Wu", "Zhiyong", "" ], [ "Pan", "Huashan", "" ], [ "Li", "Xiulin", "" ], [ "Meng", "Helen", "" ] ]
Text normalization, defined as a procedure transforming non standard words to spoken-form words, is crucial to the intelligibility of synthesized speech in text-to-speech system. Rule-based methods without considering context can not eliminate ambiguation, whereas sequence-to-sequence neural network based methods suffe...
2307.05827
Rohan Saha
Arif Shahriar, Rohan Saha, Denilson Barbosa
Relational Extraction on Wikipedia Tables using Convolutional and Memory Networks
null
null
null
null
cs.CL cs.AI cs.IR cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
Relation extraction (RE) is the task of extracting relations between entities in text. Most RE methods extract relations from free-form running text and leave out other rich data sources, such as tables. We explore RE from the perspective of applying neural methods on tabularly organized data. We introduce a new mode...
[ { "created": "Tue, 11 Jul 2023 22:36:47 GMT", "version": "v1" } ]
2023-07-13
[ [ "Shahriar", "Arif", "" ], [ "Saha", "Rohan", "" ], [ "Barbosa", "Denilson", "" ] ]
Relation extraction (RE) is the task of extracting relations between entities in text. Most RE methods extract relations from free-form running text and leave out other rich data sources, such as tables. We explore RE from the perspective of applying neural methods on tabularly organized data. We introduce a new model ...
2403.16265
Zhuoyi Peng
Zhuoyi Peng, Yi Yang
Connecting the Dots: Inferring Patent Phrase Similarity with Retrieved Phrase Graphs
Findings of NAACL 2024
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the patent phrase similarity inference task, which measures the semantic similarity between two patent phrases. As patent documents employ legal and highly technical language, existing semantic textual similarity methods that use localized contextual information do not perform satisfactorily in inferring pat...
[ { "created": "Sun, 24 Mar 2024 18:59:38 GMT", "version": "v1" } ]
2024-03-26
[ [ "Peng", "Zhuoyi", "" ], [ "Yang", "Yi", "" ] ]
We study the patent phrase similarity inference task, which measures the semantic similarity between two patent phrases. As patent documents employ legal and highly technical language, existing semantic textual similarity methods that use localized contextual information do not perform satisfactorily in inferring paten...
2210.12373
Caesar Wu
Caesar Wu, Kotagiri Ramamohanarao, Rui Zhang, Pascal Bouvry
Strategic Decisions Survey, Taxonomy, and Future Directions from Artificial Intelligence Perspective
null
null
null
null
cs.AI
http://creativecommons.org/licenses/by-sa/4.0/
Strategic Decision-Making is always challenging because it is inherently uncertain, ambiguous, risky, and complex. It is the art of possibility. We develop a systematic taxonomy of decision-making frames that consists of 6 bases, 18 categorical, and 54 frames. We aim to lay out the computational foundation that is po...
[ { "created": "Sat, 22 Oct 2022 07:01:10 GMT", "version": "v1" } ]
2022-10-25
[ [ "Wu", "Caesar", "" ], [ "Ramamohanarao", "Kotagiri", "" ], [ "Zhang", "Rui", "" ], [ "Bouvry", "Pascal", "" ] ]
Strategic Decision-Making is always challenging because it is inherently uncertain, ambiguous, risky, and complex. It is the art of possibility. We develop a systematic taxonomy of decision-making frames that consists of 6 bases, 18 categorical, and 54 frames. We aim to lay out the computational foundation that is poss...
2103.11642
Matthew R Behrend
Matthew R. Behrend and Sean M. Robinson
A Batch Normalization Classifier for Domain Adaptation
null
null
null
null
cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
Adapting a model to perform well on unforeseen data outside its training set is a common problem that continues to motivate new approaches. We demonstrate that application of batch normalization in the output layer, prior to softmax activation, results in improved generalization across visual data domains in a refine...
[ { "created": "Mon, 22 Mar 2021 08:03:44 GMT", "version": "v1" } ]
2021-03-23
[ [ "Behrend", "Matthew R.", "" ], [ "Robinson", "Sean M.", "" ] ]
Adapting a model to perform well on unforeseen data outside its training set is a common problem that continues to motivate new approaches. We demonstrate that application of batch normalization in the output layer, prior to softmax activation, results in improved generalization across visual data domains in a refined ...
2301.04299
Maxwell Standen
Maxwell Standen, Junae Kim, Claudia Szabo
SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning
null
null
null
null
cs.LG cs.AI cs.CR
http://creativecommons.org/licenses/by-nc-sa/4.0/
Multi-Agent Reinforcement Learning (MARL) is vulnerable to Adversarial Machine Learning (AML) attacks and needs adequate defences before it can be used in real world applications. We have conducted a survey into the use of execution-time AML attacks against MARL and the defences against those attacks. We surveyed rel...
[ { "created": "Wed, 11 Jan 2023 04:25:00 GMT", "version": "v1" } ]
2023-01-12
[ [ "Standen", "Maxwell", "" ], [ "Kim", "Junae", "" ], [ "Szabo", "Claudia", "" ] ]
Multi-Agent Reinforcement Learning (MARL) is vulnerable to Adversarial Machine Learning (AML) attacks and needs adequate defences before it can be used in real world applications. We have conducted a survey into the use of execution-time AML attacks against MARL and the defences against those attacks. We surveyed relat...
1909.12104
Blai Bonet
Blai Bonet and Hector Geffner
Action Selection for MDPs: Anytime AO* vs. UCT
Proceedings AAAI-12
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the presence of non-admissible heuristics, A* and other best-first algorithms can be converted into anytime optimal algorithms over OR graphs, by simply continuing the search after the first solution is found. The same trick, however, does not work for best-first algorithms over AND/OR graphs, that must be able to...
[ { "created": "Thu, 26 Sep 2019 13:51:26 GMT", "version": "v1" } ]
2019-09-27
[ [ "Bonet", "Blai", "" ], [ "Geffner", "Hector", "" ] ]
In the presence of non-admissible heuristics, A* and other best-first algorithms can be converted into anytime optimal algorithms over OR graphs, by simply continuing the search after the first solution is found. The same trick, however, does not work for best-first algorithms over AND/OR graphs, that must be able to e...
2402.12130
Piotr Dudek
Piotr Dudek
Factor Machine: Mixed-signal Architecture for Fine-Grained Graph-Based Computing
An essay in contribution to the Festschrift for Professor Steve Furber, Manchester, 12 January 2024
null
null
null
cs.AR
http://creativecommons.org/licenses/by-nc-nd/4.0/
This paper proposes the design and implementation strategy of a novel computing architecture, the Factor Machine. The work is a step towards a general-purpose parallel system operating in a non-sequential manner, exploiting processing/memory co-integration and replacing the traditional Turing/von Neumann model of a c...
[ { "created": "Mon, 19 Feb 2024 13:26:42 GMT", "version": "v1" }, { "created": "Tue, 20 Feb 2024 03:53:35 GMT", "version": "v2" } ]
2024-02-21
[ [ "Dudek", "Piotr", "" ] ]
This paper proposes the design and implementation strategy of a novel computing architecture, the Factor Machine. The work is a step towards a general-purpose parallel system operating in a non-sequential manner, exploiting processing/memory co-integration and replacing the traditional Turing/von Neumann model of a com...
1604.04137
Lin Zhang
Lin Zhang, Menglong Ye, Petros Giataganas, Michael Hughes and Guang-Zhong Yang
Autonomous Scanning for Endomicroscopic Mosaicing and 3D Fusion
In submission at International Conference on Robotics and Automation(ICRA) 2017
null
10.1109/ICRA.2017.7989412
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Robotic-assisted Minimally Invasive Surgery (RMIS) can benefit from the automation of common, repetitive or well-defined but ergonomically difficult tasks. One such task is the scanning of a pick-up endomicroscopy probe over a complex, undulating tissue surface in order to enhance the effective field-of-view through ...
[ { "created": "Thu, 14 Apr 2016 12:50:03 GMT", "version": "v1" }, { "created": "Fri, 22 Apr 2016 21:07:54 GMT", "version": "v2" }, { "created": "Fri, 21 Oct 2016 08:55:21 GMT", "version": "v3" } ]
2018-03-05
[ [ "Zhang", "Lin", "" ], [ "Ye", "Menglong", "" ], [ "Giataganas", "Petros", "" ], [ "Hughes", "Michael", "" ], [ "Yang", "Guang-Zhong", "" ] ]
Robotic-assisted Minimally Invasive Surgery (RMIS) can benefit from the automation of common, repetitive or well-defined but ergonomically difficult tasks. One such task is the scanning of a pick-up endomicroscopy probe over a complex, undulating tissue surface in order to enhance the effective field-of-view through vi...
2111.06278
Vladimir Gurvich
Vladimir Gurvich
On Nash-solvability of finite $n$-person deterministic graphical games; Catch 22
4 pages
null
null
null
cs.GT math.CO
http://creativecommons.org/licenses/by/4.0/
We consider finite $n$-person deterministic graphical (DG) games. These games are modelled by finite directed graphs (digraphs) $G$ which may have directed cycles and, hence, infinite plays. Yet, it is assumed that all these plays are equivalent and form a single outcome $c$, while the terminal vertices $V_T = \{a_1,...
[ { "created": "Thu, 11 Nov 2021 15:37:51 GMT", "version": "v1" } ]
2021-11-12
[ [ "Gurvich", "Vladimir", "" ] ]
We consider finite $n$-person deterministic graphical (DG) games. These games are modelled by finite directed graphs (digraphs) $G$ which may have directed cycles and, hence, infinite plays. Yet, it is assumed that all these plays are equivalent and form a single outcome $c$, while the terminal vertices $V_T = \{a_1, \...
0803.4241
Sebastien Verel
Maroun Bercachi (I3S), Philippe Collard (I3S), Manuel Clergue (I3S), S\'ebastien Verel (I3S)
Evolving Dynamic Change and Exchange of Genotype Encoding in Genetic Algorithms for Difficult Optimization Problems
null
Dans Proceedings of the IEEE Congress on Evolutionary Computation CEC2007 - IEEE Congress on Evolutionary Computation CEC2007, singapore : Singapour (2007)
null
null
cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The application of genetic algorithms (GAs) to many optimization problems in organizations often results in good performance and high quality solutions. For successful and efficient use of GAs, it is not enough to simply apply simple GAs (SGAs). In addition, it is necessary to find a proper representation for the pro...
[ { "created": "Sat, 29 Mar 2008 07:51:18 GMT", "version": "v1" } ]
2008-12-18
[ [ "Bercachi", "Maroun", "", "I3S" ], [ "Collard", "Philippe", "", "I3S" ], [ "Clergue", "Manuel", "", "I3S" ], [ "Verel", "Sébastien", "", "I3S" ] ]
The application of genetic algorithms (GAs) to many optimization problems in organizations often results in good performance and high quality solutions. For successful and efficient use of GAs, it is not enough to simply apply simple GAs (SGAs). In addition, it is necessary to find a proper representation for the probl...
2107.04711
Jan Smeddinck
Rosanna Bellini, Alexander Wilson, Jan David Smeddinck
Fragments of the Past: Curating Peer Support with Perpetrators of Domestic Violence
null
null
10.1145/3411764.3445611
null
cs.HC cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
There is growing evidence that digital peer-support networks can have a positive influence on behaviour change and wellbeing outcomes for people who harm themselves and others. However, making and sustaining such networks are subject to ethical and pragmatic challenges, particularly for perpetrators of domestic viole...
[ { "created": "Fri, 9 Jul 2021 22:57:43 GMT", "version": "v1" } ]
2021-07-13
[ [ "Bellini", "Rosanna", "" ], [ "Wilson", "Alexander", "" ], [ "Smeddinck", "Jan David", "" ] ]
There is growing evidence that digital peer-support networks can have a positive influence on behaviour change and wellbeing outcomes for people who harm themselves and others. However, making and sustaining such networks are subject to ethical and pragmatic challenges, particularly for perpetrators of domestic violenc...
2111.00600
Nur Lan
Nur Lan, Michal Geyer, Emmanuel Chemla, Roni Katzir
Minimum Description Length Recurrent Neural Networks
15 pages
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We train neural networks to optimize a Minimum Description Length score, i.e., to balance between the complexity of the network and its accuracy at a task. We show that networks optimizing this objective function master tasks involving memory challenges and go beyond context-free languages. These learners master lang...
[ { "created": "Sun, 31 Oct 2021 21:43:31 GMT", "version": "v1" }, { "created": "Fri, 25 Mar 2022 16:38:35 GMT", "version": "v2" }, { "created": "Wed, 30 Mar 2022 13:09:34 GMT", "version": "v3" }, { "created": "Thu, 31 Mar 2022 10:50:33 GMT", "version": "v4" } ]
2022-04-01
[ [ "Lan", "Nur", "" ], [ "Geyer", "Michal", "" ], [ "Chemla", "Emmanuel", "" ], [ "Katzir", "Roni", "" ] ]
We train neural networks to optimize a Minimum Description Length score, i.e., to balance between the complexity of the network and its accuracy at a task. We show that networks optimizing this objective function master tasks involving memory challenges and go beyond context-free languages. These learners master langua...
2312.03289
Seugnju Cho
Seungju Cho, Hongsin Lee, Changick Kim
Class Incremental Learning for Adversarial Robustness
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Adversarial training integrates adversarial examples during model training to enhance robustness. However, its application in fixed dataset settings differs from real-world dynamics, where data accumulates incrementally. In this study, we investigate Adversarially Robust Class Incremental Learning (ARCIL), a method t...
[ { "created": "Wed, 6 Dec 2023 04:38:02 GMT", "version": "v1" }, { "created": "Thu, 7 Dec 2023 04:21:33 GMT", "version": "v2" } ]
2023-12-08
[ [ "Cho", "Seungju", "" ], [ "Lee", "Hongsin", "" ], [ "Kim", "Changick", "" ] ]
Adversarial training integrates adversarial examples during model training to enhance robustness. However, its application in fixed dataset settings differs from real-world dynamics, where data accumulates incrementally. In this study, we investigate Adversarially Robust Class Incremental Learning (ARCIL), a method tha...
2407.16898
Rub\'en Ruiz-Torrubiano
Andreas Krystallidis and Rub\'en Ruiz-Torrubiano
Introducing Individuality into Students' High School Timetables
null
null
null
null
cs.CY
http://creativecommons.org/licenses/by-sa/4.0/
In a perfect world, each high school student could pursue their interests through a personalized timetable that supports their strengths, weaknesses, and curiosities. While recent research has shown that school systems are evolving to support those developments by strengthening modularity in their curricula, there is...
[ { "created": "Wed, 19 Jun 2024 13:02:44 GMT", "version": "v1" } ]
2024-07-25
[ [ "Krystallidis", "Andreas", "" ], [ "Ruiz-Torrubiano", "Rubén", "" ] ]
In a perfect world, each high school student could pursue their interests through a personalized timetable that supports their strengths, weaknesses, and curiosities. While recent research has shown that school systems are evolving to support those developments by strengthening modularity in their curricula, there is o...
1908.00524
Michelle Valente
Michelle Valente, Cyril Joly and Arnaud de La Fortelle
Deep Sensor Fusion for Real-Time Odometry Estimation
arXiv admin note: substantial text overlap with arXiv:1902.08536
null
null
null
cs.RO cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cameras and 2D laser scanners, in combination, are able to provide low-cost, light-weight and accurate solutions, which make their fusion well-suited for many robot navigation tasks. However, correct data fusion depends on precise calibration of the rigid body transform between the sensors. In this paper we present t...
[ { "created": "Wed, 31 Jul 2019 15:29:15 GMT", "version": "v1" } ]
2019-08-02
[ [ "Valente", "Michelle", "" ], [ "Joly", "Cyril", "" ], [ "de La Fortelle", "Arnaud", "" ] ]
Cameras and 2D laser scanners, in combination, are able to provide low-cost, light-weight and accurate solutions, which make their fusion well-suited for many robot navigation tasks. However, correct data fusion depends on precise calibration of the rigid body transform between the sensors. In this paper we present the...
1102.2789
Johannes Mittmann
Malte Beecken, Johannes Mittmann and Nitin Saxena
Algebraic Independence and Blackbox Identity Testing
32 pages, preliminary version
null
null
null
cs.CC math.AC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Algebraic independence is an advanced notion in commutative algebra that generalizes independence of linear polynomials to higher degree. Polynomials {f_1, ..., f_m} \subset \F[x_1, ..., x_n] are called algebraically independent if there is no non-zero polynomial F such that F(f_1, ..., f_m) = 0. The transcendence de...
[ { "created": "Mon, 14 Feb 2011 15:00:16 GMT", "version": "v1" } ]
2011-02-15
[ [ "Beecken", "Malte", "" ], [ "Mittmann", "Johannes", "" ], [ "Saxena", "Nitin", "" ] ]
Algebraic independence is an advanced notion in commutative algebra that generalizes independence of linear polynomials to higher degree. Polynomials {f_1, ..., f_m} \subset \F[x_1, ..., x_n] are called algebraically independent if there is no non-zero polynomial F such that F(f_1, ..., f_m) = 0. The transcendence degr...
2211.11958
Piji Li
Xuan Sheng, Zhaoyang Han, Piji Li, Xiangmao Chang
A Survey on Backdoor Attack and Defense in Natural Language Processing
12 pages, QRS2022
null
null
null
cs.CL cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep learning is becoming increasingly popular in real-life applications, especially in natural language processing (NLP). Users often choose training outsourcing or adopt third-party data and models due to data and computation resources being limited. In such a situation, training data and models are exposed to the ...
[ { "created": "Tue, 22 Nov 2022 02:35:12 GMT", "version": "v1" } ]
2022-11-23
[ [ "Sheng", "Xuan", "" ], [ "Han", "Zhaoyang", "" ], [ "Li", "Piji", "" ], [ "Chang", "Xiangmao", "" ] ]
Deep learning is becoming increasingly popular in real-life applications, especially in natural language processing (NLP). Users often choose training outsourcing or adopt third-party data and models due to data and computation resources being limited. In such a situation, training data and models are exposed to the pu...
1511.07545
Hailin Shi
Hailin Shi and Xiangyu Zhu and Shengcai Liao and Zhen Lei and Yang Yang and Stan Z. Li
Constrained Deep Metric Learning for Person Re-identification
11 pages, 16 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Person re-identification aims to re-identify the probe image from a given set of images under different camera views. It is challenging due to large variations of pose, illumination, occlusion and camera view. Since the convolutional neural networks (CNN) have excellent capability of feature extraction, certain deep ...
[ { "created": "Tue, 24 Nov 2015 02:46:35 GMT", "version": "v1" } ]
2015-11-25
[ [ "Shi", "Hailin", "" ], [ "Zhu", "Xiangyu", "" ], [ "Liao", "Shengcai", "" ], [ "Lei", "Zhen", "" ], [ "Yang", "Yang", "" ], [ "Li", "Stan Z.", "" ] ]
Person re-identification aims to re-identify the probe image from a given set of images under different camera views. It is challenging due to large variations of pose, illumination, occlusion and camera view. Since the convolutional neural networks (CNN) have excellent capability of feature extraction, certain deep le...
2305.19798
Francesco Tonin
Yingyi Chen, Qinghua Tao, Francesco Tonin, Johan A.K. Suykens
Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation
NeurIPS 2023. We provide a primal-dual representation for the asymmetric self-attention in transformer that allows to avoid explicit computation of the kernel matrix
null
null
null
cs.LG cs.AI cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
Recently, a new line of works has emerged to understand and improve self-attention in Transformers by treating it as a kernel machine. However, existing works apply the methods for symmetric kernels to the asymmetric self-attention, resulting in a nontrivial gap between the analytical understanding and numerical impl...
[ { "created": "Wed, 31 May 2023 12:38:24 GMT", "version": "v1" }, { "created": "Tue, 5 Dec 2023 09:26:05 GMT", "version": "v2" } ]
2023-12-06
[ [ "Chen", "Yingyi", "" ], [ "Tao", "Qinghua", "" ], [ "Tonin", "Francesco", "" ], [ "Suykens", "Johan A. K.", "" ] ]
Recently, a new line of works has emerged to understand and improve self-attention in Transformers by treating it as a kernel machine. However, existing works apply the methods for symmetric kernels to the asymmetric self-attention, resulting in a nontrivial gap between the analytical understanding and numerical implem...
2311.11652
Sha Wang
Sha Wang, Yuchen Li, Hanhua Xiao, Lambert Deng, Yanfei Dong
Web News Timeline Generation with Extended Task Prompting
4 pages
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
The creation of news timeline is essential for a comprehensive and contextual understanding of events as they unfold over time. This approach aids in discerning patterns and trends that might be obscured when news is viewed in isolation. By organizing news in a chronological sequence, it becomes easier to track the d...
[ { "created": "Mon, 20 Nov 2023 10:38:22 GMT", "version": "v1" } ]
2023-11-21
[ [ "Wang", "Sha", "" ], [ "Li", "Yuchen", "" ], [ "Xiao", "Hanhua", "" ], [ "Deng", "Lambert", "" ], [ "Dong", "Yanfei", "" ] ]
The creation of news timeline is essential for a comprehensive and contextual understanding of events as they unfold over time. This approach aids in discerning patterns and trends that might be obscured when news is viewed in isolation. By organizing news in a chronological sequence, it becomes easier to track the dev...
2305.17733
Hao Yang
Hao Yang, Jinming Zhao, Gholamreza Haffari, Ehsan Shareghi
Investigating Pre-trained Audio Encoders in the Low-Resource Condition
INTERSPEECH 2023
null
null
null
cs.CL cs.SD eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Pre-trained speech encoders have been central to pushing state-of-the-art results across various speech understanding and generation tasks. Nonetheless, the capabilities of these encoders in low-resource settings are yet to be thoroughly explored. To address this, we conduct a comprehensive set of experiments using a...
[ { "created": "Sun, 28 May 2023 14:15:19 GMT", "version": "v1" } ]
2023-05-30
[ [ "Yang", "Hao", "" ], [ "Zhao", "Jinming", "" ], [ "Haffari", "Gholamreza", "" ], [ "Shareghi", "Ehsan", "" ] ]
Pre-trained speech encoders have been central to pushing state-of-the-art results across various speech understanding and generation tasks. Nonetheless, the capabilities of these encoders in low-resource settings are yet to be thoroughly explored. To address this, we conduct a comprehensive set of experiments using a r...
2006.08731
Johannes Vass
Johannes Vass, Marie-Louise Lackner, Nysret Musliu
Exact and Metaheuristic Approaches for the Production Leveling Problem
Instance set is published under https://dbai.tuwien.ac.at/staff/jvass/production-leveling/
null
null
null
cs.AI cs.CC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we introduce a new problem in the field of production planning which we call the Production Leveling Problem. The task is to assign orders to production periods such that the load in each period and on each production resource is balanced, capacity limits are not exceeded and the orders' priorities are ...
[ { "created": "Mon, 15 Jun 2020 20:04:59 GMT", "version": "v1" } ]
2020-06-17
[ [ "Vass", "Johannes", "" ], [ "Lackner", "Marie-Louise", "" ], [ "Musliu", "Nysret", "" ] ]
In this paper we introduce a new problem in the field of production planning which we call the Production Leveling Problem. The task is to assign orders to production periods such that the load in each period and on each production resource is balanced, capacity limits are not exceeded and the orders' priorities are ta...
1102.2915
Filippo Utro
Filippo Utro
Algorithms for Internal Validation Clustering Measures in the Post Genomic Era
null
PhD Thesis, University of Palermo, Italy, 2011
null
null
cs.DS q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Inferring cluster structure in microarray datasets is a fundamental task for the -omic sciences. A fundamental question in Statistics, Data Analysis and Classification, is the prediction of the number of clusters in a dataset, usually established via internal validation measures. Despite the wealth of internal measur...
[ { "created": "Mon, 14 Feb 2011 22:13:47 GMT", "version": "v1" } ]
2011-02-16
[ [ "Utro", "Filippo", "" ] ]
Inferring cluster structure in microarray datasets is a fundamental task for the -omic sciences. A fundamental question in Statistics, Data Analysis and Classification, is the prediction of the number of clusters in a dataset, usually established via internal validation measures. Despite the wealth of internal measures...
2006.04058
Thoudam Doren Singh
Alok Singh, Thoudam Doren Singh and Sivaji Bandyopadhyay
NITS-VC System for VATEX Video Captioning Challenge 2020
Workshop on Language & Vision with applications to Video Understanding (LVVU 2020) - In conjunction with CVPR 2020
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Video captioning is process of summarising the content, event and action of the video into a short textual form which can be helpful in many research areas such as video guided machine translation, video sentiment analysis and providing aid to needy individual. In this paper, a system description of the framework use...
[ { "created": "Sun, 7 Jun 2020 06:39:56 GMT", "version": "v1" }, { "created": "Fri, 25 Sep 2020 14:05:13 GMT", "version": "v2" } ]
2020-09-28
[ [ "Singh", "Alok", "" ], [ "Singh", "Thoudam Doren", "" ], [ "Bandyopadhyay", "Sivaji", "" ] ]
Video captioning is process of summarising the content, event and action of the video into a short textual form which can be helpful in many research areas such as video guided machine translation, video sentiment analysis and providing aid to needy individual. In this paper, a system description of the framework used ...
2110.01295
Ruben Kruiper
Ruben Kruiper, Ioannis Konstas, Alasdair Gray, Farhad Sadeghineko, Richard Watson and Bimal Kumar
SPaR.txt, a cheap Shallow Parsing approach for Regulatory texts
To be published in the NLLP workshop at EMNLP 2021, 9 pages (15 including reference and appendices). For the ScotReg corpus, SPaR.txt dataset and code see: http://github.com/rubenkruiper/SPaR.txt
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Automated Compliance Checking (ACC) systems aim to semantically parse building regulations to a set of rules. However, semantic parsing is known to be hard and requires large amounts of training data. The complexity of creating such training data has led to research that focuses on small sub-tasks, such as shallow pa...
[ { "created": "Mon, 4 Oct 2021 10:00:22 GMT", "version": "v1" } ]
2021-10-05
[ [ "Kruiper", "Ruben", "" ], [ "Konstas", "Ioannis", "" ], [ "Gray", "Alasdair", "" ], [ "Sadeghineko", "Farhad", "" ], [ "Watson", "Richard", "" ], [ "Kumar", "Bimal", "" ] ]
Automated Compliance Checking (ACC) systems aim to semantically parse building regulations to a set of rules. However, semantic parsing is known to be hard and requires large amounts of training data. The complexity of creating such training data has led to research that focuses on small sub-tasks, such as shallow pars...
1908.09970
Raef Bassily
Raef Bassily, Vitaly Feldman, Kunal Talwar, Abhradeep Thakurta
Private Stochastic Convex Optimization with Optimal Rates
null
null
null
null
cs.LG cs.CR cs.DS stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study differentially private (DP) algorithms for stochastic convex optimization (SCO). In this problem the goal is to approximately minimize the population loss given i.i.d. samples from a distribution over convex and Lipschitz loss functions. A long line of existing work on private convex optimization focuses on ...
[ { "created": "Tue, 27 Aug 2019 00:50:27 GMT", "version": "v1" } ]
2019-08-28
[ [ "Bassily", "Raef", "" ], [ "Feldman", "Vitaly", "" ], [ "Talwar", "Kunal", "" ], [ "Thakurta", "Abhradeep", "" ] ]
We study differentially private (DP) algorithms for stochastic convex optimization (SCO). In this problem the goal is to approximately minimize the population loss given i.i.d. samples from a distribution over convex and Lipschitz loss functions. A long line of existing work on private convex optimization focuses on th...
2404.12335
Nick Feng
Nick Feng, Lina Marsso, S. Getir Yaman, Isobel Standen, Yesugen Baatartogtokh, Reem Ayad, Vict\'oria Oldemburgo de Mello, Bev Townsend, Hanne Bartels, Ana Cavalcanti, Radu Calinescu, Marsha Chechik
Normative Requirements Operationalization with Large Language Models
null
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Normative non-functional requirements specify constraints that a system must observe in order to avoid violations of social, legal, ethical, empathetic, and cultural norms. As these requirements are typically defined by non-technical system stakeholders with different expertise and priorities (ethicists, lawyers, soc...
[ { "created": "Thu, 18 Apr 2024 17:01:34 GMT", "version": "v1" }, { "created": "Wed, 29 May 2024 01:19:52 GMT", "version": "v2" } ]
2024-05-30
[ [ "Feng", "Nick", "" ], [ "Marsso", "Lina", "" ], [ "Yaman", "S. Getir", "" ], [ "Standen", "Isobel", "" ], [ "Baatartogtokh", "Yesugen", "" ], [ "Ayad", "Reem", "" ], [ "de Mello", "Victória Oldemburgo", "" ...
Normative non-functional requirements specify constraints that a system must observe in order to avoid violations of social, legal, ethical, empathetic, and cultural norms. As these requirements are typically defined by non-technical system stakeholders with different expertise and priorities (ethicists, lawyers, socia...
2103.05174
Pavan Samtani
Pavan Samtani, Francisco Leiva, Javier Ruiz-del-Solar
Learning to Play Soccer From Scratch: Sample-Efficient Emergent Coordination through Curriculum-Learning and Competition
null
null
null
null
cs.LG cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work proposes a scheme that allows learning complex multi-agent behaviors in a sample efficient manner, applied to 2v2 soccer. The problem is formulated as a Markov game, and solved using deep reinforcement learning. We propose a basic multi-agent extension of TD3 for learning the policy of each player, in a dec...
[ { "created": "Tue, 9 Mar 2021 01:57:16 GMT", "version": "v1" } ]
2021-03-10
[ [ "Samtani", "Pavan", "" ], [ "Leiva", "Francisco", "" ], [ "Ruiz-del-Solar", "Javier", "" ] ]
This work proposes a scheme that allows learning complex multi-agent behaviors in a sample efficient manner, applied to 2v2 soccer. The problem is formulated as a Markov game, and solved using deep reinforcement learning. We propose a basic multi-agent extension of TD3 for learning the policy of each player, in a decen...
2003.06112
Linh Ngo
Ngo Van Linh, Tran Xuan Bach and Khoat Than
A Graph Convolutional Topic Model for Short and Noisy Text Streams
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Learning hidden topics from data streams has become absolutely necessary but posed challenging problems such as concept drift as well as short and noisy data. Using prior knowledge to enrich a topic model is one of potential solutions to cope with these challenges. Prior knowledge that is derived from human knowledge...
[ { "created": "Fri, 13 Mar 2020 05:09:00 GMT", "version": "v1" }, { "created": "Tue, 17 Mar 2020 06:43:33 GMT", "version": "v2" }, { "created": "Sat, 6 Feb 2021 03:51:01 GMT", "version": "v3" }, { "created": "Fri, 24 Dec 2021 02:26:38 GMT", "version": "v4" } ]
2021-12-28
[ [ "Van Linh", "Ngo", "" ], [ "Bach", "Tran Xuan", "" ], [ "Than", "Khoat", "" ] ]
Learning hidden topics from data streams has become absolutely necessary but posed challenging problems such as concept drift as well as short and noisy data. Using prior knowledge to enrich a topic model is one of potential solutions to cope with these challenges. Prior knowledge that is derived from human knowledge (...
2111.02964
Rohan Chandra
Rohan Chandra, Aniket Bera, Dinesh Manocha
Using Graph-Theoretic Machine Learning to Predict Human Driver Behavior
null
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
Studies have shown that autonomous vehicles (AVs) behave conservatively in a traffic environment composed of human drivers and do not adapt to local conditions and socio-cultural norms. It is known that socially aware AVs can be designed if there exists a mechanism to understand the behaviors of human drivers. We pre...
[ { "created": "Thu, 4 Nov 2021 15:57:10 GMT", "version": "v1" } ]
2021-11-05
[ [ "Chandra", "Rohan", "" ], [ "Bera", "Aniket", "" ], [ "Manocha", "Dinesh", "" ] ]
Studies have shown that autonomous vehicles (AVs) behave conservatively in a traffic environment composed of human drivers and do not adapt to local conditions and socio-cultural norms. It is known that socially aware AVs can be designed if there exists a mechanism to understand the behaviors of human drivers. We prese...
2403.01487
Haogeng Liu
Haogeng Liu, Quanzeng You, Xiaotian Han, Yiqi Wang, Bohan Zhai, Yongfei Liu, Yunzhe Tao, Huaibo Huang, Ran He, Hongxia Yang
InfiMM-HD: A Leap Forward in High-Resolution Multimodal Understanding
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Multimodal Large Language Models (MLLMs) have experienced significant advancements recently. Nevertheless, challenges persist in the accurate recognition and comprehension of intricate details within high-resolution images. Despite being indispensable for the development of robust MLLMs, this area remains underinvest...
[ { "created": "Sun, 3 Mar 2024 11:39:41 GMT", "version": "v1" } ]
2024-03-05
[ [ "Liu", "Haogeng", "" ], [ "You", "Quanzeng", "" ], [ "Han", "Xiaotian", "" ], [ "Wang", "Yiqi", "" ], [ "Zhai", "Bohan", "" ], [ "Liu", "Yongfei", "" ], [ "Tao", "Yunzhe", "" ], [ "Huang", "Huai...
Multimodal Large Language Models (MLLMs) have experienced significant advancements recently. Nevertheless, challenges persist in the accurate recognition and comprehension of intricate details within high-resolution images. Despite being indispensable for the development of robust MLLMs, this area remains underinvestig...
2406.00773
Jincheng Zhong
Jincheng Zhong, Xingzhuo Guo, Jiaxiang Dong, Mingsheng Long
Diffusion Tuning: Transferring Diffusion Models via Chain of Forgetting
null
null
null
null
cs.LG cs.CV
http://creativecommons.org/licenses/by/4.0/
Diffusion models have significantly advanced the field of generative modeling. However, training a diffusion model is computationally expensive, creating a pressing need to adapt off-the-shelf diffusion models for downstream generation tasks. Current fine-tuning methods focus on parameter-efficient transfer learning ...
[ { "created": "Sun, 2 Jun 2024 15:20:59 GMT", "version": "v1" }, { "created": "Thu, 6 Jun 2024 10:08:22 GMT", "version": "v2" } ]
2024-06-07
[ [ "Zhong", "Jincheng", "" ], [ "Guo", "Xingzhuo", "" ], [ "Dong", "Jiaxiang", "" ], [ "Long", "Mingsheng", "" ] ]
Diffusion models have significantly advanced the field of generative modeling. However, training a diffusion model is computationally expensive, creating a pressing need to adapt off-the-shelf diffusion models for downstream generation tasks. Current fine-tuning methods focus on parameter-efficient transfer learning bu...
1804.08902
Ran Ben Basat
Ran Ben Basat, Maayan Goldstein, Itai Segall
Learning Software Constraints via Installation Attempts
null
null
null
null
cs.SE cs.CR cs.DS cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Modern software systems are expected to be secure and contain all the latest features, even when new versions of software are released multiple times an hour. Each system may include many interacting packages. The problem of installing multiple dependent packages has been extensively studied in the past, yielding som...
[ { "created": "Tue, 24 Apr 2018 08:49:00 GMT", "version": "v1" }, { "created": "Wed, 14 Nov 2018 16:13:19 GMT", "version": "v2" } ]
2018-11-15
[ [ "Basat", "Ran Ben", "" ], [ "Goldstein", "Maayan", "" ], [ "Segall", "Itai", "" ] ]
Modern software systems are expected to be secure and contain all the latest features, even when new versions of software are released multiple times an hour. Each system may include many interacting packages. The problem of installing multiple dependent packages has been extensively studied in the past, yielding some ...
1603.05800
Zhiyun Lu
Zhiyun Lu, Dong Guo, Alireza Bagheri Garakani, Kuan Liu, Avner May, Aurelien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha
A Comparison between Deep Neural Nets and Kernel Acoustic Models for Speech Recognition
arXiv admin note: text overlap with arXiv:1411.4000
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study large-scale kernel methods for acoustic modeling and compare to DNNs on performance metrics related to both acoustic modeling and recognition. Measuring perplexity and frame-level classification accuracy, kernel-based acoustic models are as effective as their DNN counterparts. However, on token-error-rates D...
[ { "created": "Fri, 18 Mar 2016 09:16:01 GMT", "version": "v1" } ]
2016-03-21
[ [ "Lu", "Zhiyun", "" ], [ "Guo", "Dong", "" ], [ "Garakani", "Alireza Bagheri", "" ], [ "Liu", "Kuan", "" ], [ "May", "Avner", "" ], [ "Bellet", "Aurelien", "" ], [ "Fan", "Linxi", "" ], [ "Collins", ...
We study large-scale kernel methods for acoustic modeling and compare to DNNs on performance metrics related to both acoustic modeling and recognition. Measuring perplexity and frame-level classification accuracy, kernel-based acoustic models are as effective as their DNN counterparts. However, on token-error-rates DNN...
1209.5430
Spyros Sioutas SS
Spyros Sioutas, Alexandros Panaretos, Ioannis Karydis, Dimitrios Tsoumakos, Giannis Tzimas and Dimitrios Tsolis
SART: Speeding up Query Processing in Sensor Networks with an Autonomous Range Tree Structure
11 pages, 23 figures, 5 algorithms or operations
ACM Applied Computing Review (ACR), Vol. 12, No.3, 2012, pp.60-74
null
null
cs.DC cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of constructing efficient P2P overlays for sensornets providing "Energy-Level Application and Services". The method presented in \cite{SOPXM09} presents a novel P2P overlay for Energy Level discovery in a sensornet. However, this solution is not dynamic, since requires periodical restructuring...
[ { "created": "Mon, 24 Sep 2012 21:24:36 GMT", "version": "v1" } ]
2012-09-26
[ [ "Sioutas", "Spyros", "" ], [ "Panaretos", "Alexandros", "" ], [ "Karydis", "Ioannis", "" ], [ "Tsoumakos", "Dimitrios", "" ], [ "Tzimas", "Giannis", "" ], [ "Tsolis", "Dimitrios", "" ] ]
We consider the problem of constructing efficient P2P overlays for sensornets providing "Energy-Level Application and Services". The method presented in \cite{SOPXM09} presents a novel P2P overlay for Energy Level discovery in a sensornet. However, this solution is not dynamic, since requires periodical restructuring. ...
2306.03090
Rose Wang
Rose E. Wang, Dorottya Demszky
Is ChatGPT a Good Teacher Coach? Measuring Zero-Shot Performance For Scoring and Providing Actionable Insights on Classroom Instruction
In the Proceedings of Innovative Use of NLP for Building Educational Applications 2023; The code and model outputs are open-sourced here: https://github.com/rosewang2008/zero-shot-teacher-feedback
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Coaching, which involves classroom observation and expert feedback, is a widespread and fundamental part of teacher training. However, the majority of teachers do not have access to consistent, high quality coaching due to limited resources and access to expertise. We explore whether generative AI could become a cost...
[ { "created": "Mon, 5 Jun 2023 17:59:21 GMT", "version": "v1" } ]
2023-06-06
[ [ "Wang", "Rose E.", "" ], [ "Demszky", "Dorottya", "" ] ]
Coaching, which involves classroom observation and expert feedback, is a widespread and fundamental part of teacher training. However, the majority of teachers do not have access to consistent, high quality coaching due to limited resources and access to expertise. We explore whether generative AI could become a cost-e...
1811.02657
Tan Nguyen
Tan Nguyen, Nhat Ho, Ankit Patel, Anima Anandkumar, Michael I. Jordan, Richard G. Baraniuk
A Bayesian Perspective of Convolutional Neural Networks through a Deconvolutional Generative Model
Keywords: neural nets, generative models, semi-supervised learning, cross-entropy, statistical guarantees 80 pages, 7 figures, 8 tables
null
null
null
cs.CV cs.AI cs.LG cs.NE stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Inspired by the success of Convolutional Neural Networks (CNNs) for supervised prediction in images, we design the Deconvolutional Generative Model (DGM), a new probabilistic generative model whose inference calculations correspond to those in a given CNN architecture. The DGM uses a CNN to design the prior distribut...
[ { "created": "Thu, 1 Nov 2018 01:27:37 GMT", "version": "v1" }, { "created": "Mon, 9 Dec 2019 10:21:21 GMT", "version": "v2" } ]
2019-12-10
[ [ "Nguyen", "Tan", "" ], [ "Ho", "Nhat", "" ], [ "Patel", "Ankit", "" ], [ "Anandkumar", "Anima", "" ], [ "Jordan", "Michael I.", "" ], [ "Baraniuk", "Richard G.", "" ] ]
Inspired by the success of Convolutional Neural Networks (CNNs) for supervised prediction in images, we design the Deconvolutional Generative Model (DGM), a new probabilistic generative model whose inference calculations correspond to those in a given CNN architecture. The DGM uses a CNN to design the prior distributio...
2102.11263
Kripasindhu Sarkar
Kripasindhu Sarkar and Vladislav Golyanik and Lingjie Liu and Christian Theobalt
Style and Pose Control for Image Synthesis of Humans from a Single Monocular View
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Photo-realistic re-rendering of a human from a single image with explicit control over body pose, shape and appearance enables a wide range of applications, such as human appearance transfer, virtual try-on, motion imitation, and novel view synthesis. While significant progress has been made in this direction using l...
[ { "created": "Mon, 22 Feb 2021 18:50:47 GMT", "version": "v1" } ]
2021-02-23
[ [ "Sarkar", "Kripasindhu", "" ], [ "Golyanik", "Vladislav", "" ], [ "Liu", "Lingjie", "" ], [ "Theobalt", "Christian", "" ] ]
Photo-realistic re-rendering of a human from a single image with explicit control over body pose, shape and appearance enables a wide range of applications, such as human appearance transfer, virtual try-on, motion imitation, and novel view synthesis. While significant progress has been made in this direction using lea...
2210.17471
Kenneth Mayer
Kenneth MacSporran Mayer, Laura Cottatellucci, Robert Schober
Optimal Antenna Placement for Two-Antenna Near-Field Wireless Power Transfer
7 pages, 3 figures, six page version of this paper has been submitted to IEEE ICC 2023
null
10.1109/ICC45041.2023.10278773
null
cs.IT eess.SP math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Current trends in communication system design precipitate a change in the operating regime from the traditional far-field to the radiating near-field (Fresnel) region. We investigate the optimal transmit antenna placement for a multiple-input single-output (MISO) wireless power transfer (WPT) system designed for a th...
[ { "created": "Mon, 31 Oct 2022 16:56:33 GMT", "version": "v1" } ]
2023-11-06
[ [ "Mayer", "Kenneth MacSporran", "" ], [ "Cottatellucci", "Laura", "" ], [ "Schober", "Robert", "" ] ]
Current trends in communication system design precipitate a change in the operating regime from the traditional far-field to the radiating near-field (Fresnel) region. We investigate the optimal transmit antenna placement for a multiple-input single-output (MISO) wireless power transfer (WPT) system designed for a thre...
2304.12512
Michael Sandborn
Henry Gilbert, Michael Sandborn, Douglas C. Schmidt, Jesse Spencer-Smith, Jules White
Semantic Compression With Large Language Models
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The rise of large language models (LLMs) is revolutionizing information retrieval, question answering, summarization, and code generation tasks. However, in addition to confidently presenting factually inaccurate information at times (known as "hallucinations"), LLMs are also inherently limited by the number of input...
[ { "created": "Tue, 25 Apr 2023 01:47:05 GMT", "version": "v1" } ]
2023-04-26
[ [ "Gilbert", "Henry", "" ], [ "Sandborn", "Michael", "" ], [ "Schmidt", "Douglas C.", "" ], [ "Spencer-Smith", "Jesse", "" ], [ "White", "Jules", "" ] ]
The rise of large language models (LLMs) is revolutionizing information retrieval, question answering, summarization, and code generation tasks. However, in addition to confidently presenting factually inaccurate information at times (known as "hallucinations"), LLMs are also inherently limited by the number of input a...
2008.11995
Amelie Royer
Amelie Royer and Christoph H. Lampert
A Flexible Selection Scheme for Minimum-Effort Transfer Learning
WACV 2020
null
10.1109/WACV45572.2020.9093635
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Fine-tuning is a popular way of exploiting knowledge contained in a pre-trained convolutional network for a new visual recognition task. However, the orthogonal setting of transferring knowledge from a pretrained network to a visually different yet semantically close source is rarely considered: This commonly happens...
[ { "created": "Thu, 27 Aug 2020 08:57:30 GMT", "version": "v1" } ]
2020-08-28
[ [ "Royer", "Amelie", "" ], [ "Lampert", "Christoph H.", "" ] ]
Fine-tuning is a popular way of exploiting knowledge contained in a pre-trained convolutional network for a new visual recognition task. However, the orthogonal setting of transferring knowledge from a pretrained network to a visually different yet semantically close source is rarely considered: This commonly happens w...
1706.03102
Solon Barocas
Solon Barocas, Elizabeth Bradley, Vasant Honavar, and Foster Provost
Big Data, Data Science, and Civil Rights
A Computing Community Consortium (CCC) white paper, 8 pages
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Advances in data analytics bring with them civil rights implications. Data-driven and algorithmic decision making increasingly determine how businesses target advertisements to consumers, how police departments monitor individuals or groups, how banks decide who gets a loan and who does not, how employers hire, how c...
[ { "created": "Fri, 9 Jun 2017 19:45:28 GMT", "version": "v1" } ]
2017-06-13
[ [ "Barocas", "Solon", "" ], [ "Bradley", "Elizabeth", "" ], [ "Honavar", "Vasant", "" ], [ "Provost", "Foster", "" ] ]
Advances in data analytics bring with them civil rights implications. Data-driven and algorithmic decision making increasingly determine how businesses target advertisements to consumers, how police departments monitor individuals or groups, how banks decide who gets a loan and who does not, how employers hire, how col...
2101.06286
M. Mehdi Afsar
M. Mehdi Afsar, Trafford Crump, Behrouz Far
Reinforcement learning based recommender systems: A survey
To appear in ACM Computing Surveys
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recommender systems (RSs) have become an inseparable part of our everyday lives. They help us find our favorite items to purchase, our friends on social networks, and our favorite movies to watch. Traditionally, the recommendation problem was considered to be a classification or prediction problem, but it is now wide...
[ { "created": "Fri, 15 Jan 2021 19:42:10 GMT", "version": "v1" }, { "created": "Wed, 8 Jun 2022 05:25:37 GMT", "version": "v2" } ]
2022-06-09
[ [ "Afsar", "M. Mehdi", "" ], [ "Crump", "Trafford", "" ], [ "Far", "Behrouz", "" ] ]
Recommender systems (RSs) have become an inseparable part of our everyday lives. They help us find our favorite items to purchase, our friends on social networks, and our favorite movies to watch. Traditionally, the recommendation problem was considered to be a classification or prediction problem, but it is now widely...
1911.03310
Jind\v{r}ich Libovick\'y
Jind\v{r}ich Libovick\'y and Rudolf Rosa and Alexander Fraser
How Language-Neutral is Multilingual BERT?
6 pages, 3 figures
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multilingual BERT (mBERT) provides sentence representations for 104 languages, which are useful for many multi-lingual tasks. Previous work probed the cross-linguality of mBERT using zero-shot transfer learning on morphological and syntactic tasks. We instead focus on the semantic properties of mBERT. We show that mB...
[ { "created": "Fri, 8 Nov 2019 15:12:36 GMT", "version": "v1" } ]
2019-11-11
[ [ "Libovický", "Jindřich", "" ], [ "Rosa", "Rudolf", "" ], [ "Fraser", "Alexander", "" ] ]
Multilingual BERT (mBERT) provides sentence representations for 104 languages, which are useful for many multi-lingual tasks. Previous work probed the cross-linguality of mBERT using zero-shot transfer learning on morphological and syntactic tasks. We instead focus on the semantic properties of mBERT. We show that mBER...
1905.08348
Wenjie Xiong
Wenjie Xiong and Jakub Szefer
Leaking Information Through Cache LRU States
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Least-Recently Used cache replacement policy and its variants are widely deployed in modern processors. This paper shows for the first time in detail that the LRU states of caches can be used to leak information: any access to a cache by a sender will modify the LRU state, and the receiver is able to observe this...
[ { "created": "Mon, 20 May 2019 21:11:13 GMT", "version": "v1" }, { "created": "Fri, 3 Jan 2020 04:15:48 GMT", "version": "v2" } ]
2020-01-06
[ [ "Xiong", "Wenjie", "" ], [ "Szefer", "Jakub", "" ] ]
The Least-Recently Used cache replacement policy and its variants are widely deployed in modern processors. This paper shows for the first time in detail that the LRU states of caches can be used to leak information: any access to a cache by a sender will modify the LRU state, and the receiver is able to observe this t...
2407.16990
Liang Mi
Weijun Wang, Liang Mi, Shaowei Cen, Haipeng Dai, Yuanchun Li, Xiaoming Fu, Yunxin Liu
Region-based Content Enhancement for Efficient Video Analytics at the Edge
null
null
null
null
cs.NI
http://creativecommons.org/licenses/by/4.0/
Video analytics is widespread in various applications serving our society. Recent advances of content enhancement in video analytics offer significant benefits for the bandwidth saving and accuracy improvement. However, existing content-enhanced video analytics systems are excessively computationally expensive and pr...
[ { "created": "Wed, 24 Jul 2024 04:17:32 GMT", "version": "v1" } ]
2024-07-25
[ [ "Wang", "Weijun", "" ], [ "Mi", "Liang", "" ], [ "Cen", "Shaowei", "" ], [ "Dai", "Haipeng", "" ], [ "Li", "Yuanchun", "" ], [ "Fu", "Xiaoming", "" ], [ "Liu", "Yunxin", "" ] ]
Video analytics is widespread in various applications serving our society. Recent advances of content enhancement in video analytics offer significant benefits for the bandwidth saving and accuracy improvement. However, existing content-enhanced video analytics systems are excessively computationally expensive and prov...
1709.01148
Yizhe Zhu
Mohamed Elhoseiny, Yizhe Zhu, Han Zhang, Ahmed Elgammal
Link the head to the "beak": Zero Shot Learning from Noisy Text Description at Part Precision
Accepted by CVPR'17
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we study learning visual classifiers from unstructured text descriptions at part precision with no training images. We propose a learning framework that is able to connect text terms to its relevant parts and suppress connections to non-visual text terms without any part-text annotations. For instance,...
[ { "created": "Mon, 4 Sep 2017 20:36:14 GMT", "version": "v1" } ]
2017-09-06
[ [ "Elhoseiny", "Mohamed", "" ], [ "Zhu", "Yizhe", "" ], [ "Zhang", "Han", "" ], [ "Elgammal", "Ahmed", "" ] ]
In this paper, we study learning visual classifiers from unstructured text descriptions at part precision with no training images. We propose a learning framework that is able to connect text terms to its relevant parts and suppress connections to non-visual text terms without any part-text annotations. For instance, t...
1511.03690
David Harwath
David Harwath and James Glass
Deep Multimodal Semantic Embeddings for Speech and Images
null
null
null
null
cs.CV cs.AI cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we present a model which takes as input a corpus of images with relevant spoken captions and finds a correspondence between the two modalities. We employ a pair of convolutional neural networks to model visual objects and speech signals at the word level, and tie the networks together with an embedding...
[ { "created": "Wed, 11 Nov 2015 21:30:10 GMT", "version": "v1" } ]
2015-11-13
[ [ "Harwath", "David", "" ], [ "Glass", "James", "" ] ]
In this paper, we present a model which takes as input a corpus of images with relevant spoken captions and finds a correspondence between the two modalities. We employ a pair of convolutional neural networks to model visual objects and speech signals at the word level, and tie the networks together with an embedding a...
2207.14659
Gonzalo Jes\'us Paz Delgado
G.J. Paz-Delgado, C.J. P\'erez-del-Pulgar, M. Azkarate, F. Kirchner and A. Garc\'ia-Cerezo
Multi-stage warm started optimal motion planning for over-actuated mobile platforms
null
null
10.1007/s11370-023-00461-x
null
cs.RO cs.SY eess.SY
http://creativecommons.org/licenses/by/4.0/
This work presents a computationally lightweight motion planner for over-actuated platforms. For this purpose, a general state-space model for mobile platforms with several kinematic chains is defined, which considers non-linearities and constraints. The proposed motion planner is based on a sequential multi-stage ap...
[ { "created": "Fri, 29 Jul 2022 13:05:45 GMT", "version": "v1" } ]
2023-04-26
[ [ "Paz-Delgado", "G. J.", "" ], [ "Pérez-del-Pulgar", "C. J.", "" ], [ "Azkarate", "M.", "" ], [ "Kirchner", "F.", "" ], [ "García-Cerezo", "A.", "" ] ]
This work presents a computationally lightweight motion planner for over-actuated platforms. For this purpose, a general state-space model for mobile platforms with several kinematic chains is defined, which considers non-linearities and constraints. The proposed motion planner is based on a sequential multi-stage appr...
1910.07883
Matthias Niedermaier
Matthias Niedermaier and Florian Fischer and Alexander von Bodisco
PropFuzz -- An IT-Security Fuzzing Framework for Proprietary ICS Protocols
2017 International Conference on Applied Electronics (AE)
null
10.23919/AE.2017.8053600
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Programmable Logic Controllers are used for smart homes, in production processes or to control critical infrastructures. Modern industrial devices in the control level are often communicating over proprietary protocols on top of TCP/IP with each other and SCADA systems. The networks in which the controllers operate a...
[ { "created": "Thu, 17 Oct 2019 13:20:10 GMT", "version": "v1" } ]
2019-10-18
[ [ "Niedermaier", "Matthias", "" ], [ "Fischer", "Florian", "" ], [ "von Bodisco", "Alexander", "" ] ]
Programmable Logic Controllers are used for smart homes, in production processes or to control critical infrastructures. Modern industrial devices in the control level are often communicating over proprietary protocols on top of TCP/IP with each other and SCADA systems. The networks in which the controllers operate are...
2405.14307
Weigang Lu
Weigang Lu, Ziyu Guan, Wei Zhao, and Yaming Yang
AdaGMLP: AdaBoosting GNN-to-MLP Knowledge Distillation
Accepted by KDD 2024
KDD 2024
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Graph Neural Networks (GNNs) have revolutionized graph-based machine learning, but their heavy computational demands pose challenges for latency-sensitive edge devices in practical industrial applications. In response, a new wave of methods, collectively known as GNN-to-MLP Knowledge Distillation, has emerged. They a...
[ { "created": "Thu, 23 May 2024 08:28:44 GMT", "version": "v1" } ]
2024-05-24
[ [ "Lu", "Weigang", "" ], [ "Guan", "Ziyu", "" ], [ "Zhao", "Wei", "" ], [ "Yang", "Yaming", "" ] ]
Graph Neural Networks (GNNs) have revolutionized graph-based machine learning, but their heavy computational demands pose challenges for latency-sensitive edge devices in practical industrial applications. In response, a new wave of methods, collectively known as GNN-to-MLP Knowledge Distillation, has emerged. They aim...
1401.6022
Rishab Nithyanand
Xiang Cai, Rishab Nithyanand, and Rob Johnson
New Approaches to Website Fingerprinting Defenses
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Website fingerprinting attacks enable an adversary to infer which website a victim is visiting, even if the victim uses an encrypting proxy, such as Tor. Previous work has shown that all proposed defenses against website fingerprinting attacks are ineffective. This paper advances the study of website fingerprinting...
[ { "created": "Thu, 23 Jan 2014 15:55:20 GMT", "version": "v1" } ]
2014-01-24
[ [ "Cai", "Xiang", "" ], [ "Nithyanand", "Rishab", "" ], [ "Johnson", "Rob", "" ] ]
Website fingerprinting attacks enable an adversary to infer which website a victim is visiting, even if the victim uses an encrypting proxy, such as Tor. Previous work has shown that all proposed defenses against website fingerprinting attacks are ineffective. This paper advances the study of website fingerprinting att...
2205.02919
Camilo Sarmiento
Camilo Sarmiento, Gauvain Bourgne, Katsumi Inoue, Daniele Cavalli, Jean-Gabriel Ganascia
Action Languages Based Actual Causality for Computational Ethics: a Sound and Complete Implementation in ASP
22 pages, 7 figures
null
null
null
cs.AI
http://creativecommons.org/licenses/by-sa/4.0/
Although moral responsibility is not circumscribed by causality, they are both closely intermixed. Furthermore, rationally understanding the evolution of the physical world is inherently linked with the idea of causality. Thus, the decision-making applications based on automated planning inevitably have to deal with ...
[ { "created": "Thu, 5 May 2022 21:00:59 GMT", "version": "v1" }, { "created": "Wed, 24 May 2023 12:43:13 GMT", "version": "v2" } ]
2023-05-25
[ [ "Sarmiento", "Camilo", "" ], [ "Bourgne", "Gauvain", "" ], [ "Inoue", "Katsumi", "" ], [ "Cavalli", "Daniele", "" ], [ "Ganascia", "Jean-Gabriel", "" ] ]
Although moral responsibility is not circumscribed by causality, they are both closely intermixed. Furthermore, rationally understanding the evolution of the physical world is inherently linked with the idea of causality. Thus, the decision-making applications based on automated planning inevitably have to deal with ca...
2207.08605
Subhankar Roy
Subhankar Roy, Mingxuan Liu, Zhun Zhong, Nicu Sebe, Elisa Ricci
Class-incremental Novel Class Discovery
ECCV 2022
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
We study the new task of class-incremental Novel Class Discovery (class-iNCD), which refers to the problem of discovering novel categories in an unlabelled data set by leveraging a pre-trained model that has been trained on a labelled data set containing disjoint yet related categories. Apart from discovering novel c...
[ { "created": "Mon, 18 Jul 2022 13:49:27 GMT", "version": "v1" } ]
2022-07-19
[ [ "Roy", "Subhankar", "" ], [ "Liu", "Mingxuan", "" ], [ "Zhong", "Zhun", "" ], [ "Sebe", "Nicu", "" ], [ "Ricci", "Elisa", "" ] ]
We study the new task of class-incremental Novel Class Discovery (class-iNCD), which refers to the problem of discovering novel categories in an unlabelled data set by leveraging a pre-trained model that has been trained on a labelled data set containing disjoint yet related categories. Apart from discovering novel cla...
1710.04582
Eleni Vasilaki D.Phil.
Eleni Vasilaki
Is Epicurus the father of Reinforcement Learning?
4 pages
null
null
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Epicurean Philosophy is commonly thought as simplistic and hedonistic. Here I discuss how this is a misconception and explore its link to Reinforcement Learning. Based on the letters of Epicurus, I construct an objective function for hedonism which turns out to be equivalent of the Reinforcement Learning objectiv...
[ { "created": "Thu, 12 Oct 2017 16:07:18 GMT", "version": "v1" } ]
2017-10-13
[ [ "Vasilaki", "Eleni", "" ] ]
The Epicurean Philosophy is commonly thought as simplistic and hedonistic. Here I discuss how this is a misconception and explore its link to Reinforcement Learning. Based on the letters of Epicurus, I construct an objective function for hedonism which turns out to be equivalent of the Reinforcement Learning objective ...
2208.05065
Yuzhu Sun
Yuzhu Sun, Mien Van, Stephen McIlvanna, Sean McLoone and Dariusz Ceglarek
Fixed-time Integral Sliding Mode Control for Admittance Control of a Robot Manipulator
null
null
null
null
cs.RO cs.SY eess.SY
http://creativecommons.org/licenses/by/4.0/
This paper proposes a novel fixed-time integral sliding mode controller for admittance control to enhance physical human-robot collaboration. The proposed method combines the benefits of compliance to external forces of admittance control and high robustness to uncertainties of integral sliding mode control (ISMC), s...
[ { "created": "Tue, 9 Aug 2022 22:47:19 GMT", "version": "v1" } ]
2022-08-11
[ [ "Sun", "Yuzhu", "" ], [ "Van", "Mien", "" ], [ "McIlvanna", "Stephen", "" ], [ "McLoone", "Sean", "" ], [ "Ceglarek", "Dariusz", "" ] ]
This paper proposes a novel fixed-time integral sliding mode controller for admittance control to enhance physical human-robot collaboration. The proposed method combines the benefits of compliance to external forces of admittance control and high robustness to uncertainties of integral sliding mode control (ISMC), suc...
1910.12056
Zhijie Wu
Chunjin Song, Zhijie Wu, Yang Zhou, Minglun Gong, Hui Huang
ETNet: Error Transition Network for Arbitrary Style Transfer
Accepted by NeurIPS 2019
null
null
null
cs.CV cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Numerous valuable efforts have been devoted to achieving arbitrary style transfer since the seminal work of Gatys et al. However, existing state-of-the-art approaches often generate insufficiently stylized results under challenging cases. We believe a fundamental reason is that these approaches try to generate the st...
[ { "created": "Sat, 26 Oct 2019 12:49:00 GMT", "version": "v1" }, { "created": "Tue, 29 Oct 2019 17:04:01 GMT", "version": "v2" } ]
2019-10-30
[ [ "Song", "Chunjin", "" ], [ "Wu", "Zhijie", "" ], [ "Zhou", "Yang", "" ], [ "Gong", "Minglun", "" ], [ "Huang", "Hui", "" ] ]
Numerous valuable efforts have been devoted to achieving arbitrary style transfer since the seminal work of Gatys et al. However, existing state-of-the-art approaches often generate insufficiently stylized results under challenging cases. We believe a fundamental reason is that these approaches try to generate the styl...
2307.00134
Giuseppe Alessio D'Inverno
Giuseppe Alessio D'Inverno and Simone Brugiapaglia and Mirco Ravanelli
Generalization Limits of Graph Neural Networks in Identity Effects Learning
13 pages, 10 figures
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Graph Neural Networks (GNNs) have emerged as a powerful tool for data-driven learning on various graph domains. They are usually based on a message-passing mechanism and have gained increasing popularity for their intuitive formulation, which is closely linked to the Weisfeiler-Lehman (WL) test for graph isomorphism ...
[ { "created": "Fri, 30 Jun 2023 20:56:38 GMT", "version": "v1" }, { "created": "Mon, 30 Oct 2023 17:57:48 GMT", "version": "v2" }, { "created": "Tue, 31 Oct 2023 23:20:31 GMT", "version": "v3" } ]
2023-11-02
[ [ "D'Inverno", "Giuseppe Alessio", "" ], [ "Brugiapaglia", "Simone", "" ], [ "Ravanelli", "Mirco", "" ] ]
Graph Neural Networks (GNNs) have emerged as a powerful tool for data-driven learning on various graph domains. They are usually based on a message-passing mechanism and have gained increasing popularity for their intuitive formulation, which is closely linked to the Weisfeiler-Lehman (WL) test for graph isomorphism to...
1810.12266
Adam Lopez
Ieva Vasiljeva, Sorcha Gilroy, Adam Lopez
The problem with probabilistic DAG automata for semantic graphs
To appear in NAACL-HLT 2019
null
null
null
cs.FL cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Semantic representations in the form of directed acyclic graphs (DAGs) have been introduced in recent years, and to model them, we need probabilistic models of DAGs. One model that has attracted some attention is the DAG automaton, but it has not been studied as a probabilistic model. We show that some DAG automata c...
[ { "created": "Mon, 29 Oct 2018 17:24:57 GMT", "version": "v1" }, { "created": "Sat, 6 Apr 2019 14:41:39 GMT", "version": "v2" } ]
2019-04-09
[ [ "Vasiljeva", "Ieva", "" ], [ "Gilroy", "Sorcha", "" ], [ "Lopez", "Adam", "" ] ]
Semantic representations in the form of directed acyclic graphs (DAGs) have been introduced in recent years, and to model them, we need probabilistic models of DAGs. One model that has attracted some attention is the DAG automaton, but it has not been studied as a probabilistic model. We show that some DAG automata can...
2405.17713
Micah Carroll
Micah Carroll, Davis Foote, Anand Siththaranjan, Stuart Russell, Anca Dragan
AI Alignment with Changing and Influenceable Reward Functions
Accepted to ICML 2024
null
null
null
cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Existing AI alignment approaches assume that preferences are static, which is unrealistic: our preferences change, and may even be influenced by our interactions with AI systems themselves. To clarify the consequences of incorrectly assuming static preferences, we introduce Dynamic Reward Markov Decision Processes (D...
[ { "created": "Tue, 28 May 2024 00:08:46 GMT", "version": "v1" } ]
2024-05-29
[ [ "Carroll", "Micah", "" ], [ "Foote", "Davis", "" ], [ "Siththaranjan", "Anand", "" ], [ "Russell", "Stuart", "" ], [ "Dragan", "Anca", "" ] ]
Existing AI alignment approaches assume that preferences are static, which is unrealistic: our preferences change, and may even be influenced by our interactions with AI systems themselves. To clarify the consequences of incorrectly assuming static preferences, we introduce Dynamic Reward Markov Decision Processes (DR-...
1901.10795
Mohammadreza Mousaei
Heather Jones, Siri Maley, Kenji Yonekawa, Mohammadreza Mousaei, J. David Yesso, David Kohanbash, William Whittaker
Automated Analysis, Reporting, and Archiving for Robotic Nondestructive Assay of Holdup Deposits
null
null
null
null
cs.RO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
To decommission deactivated gaseous diffusion enrichment facilities, miles of contaminated pipe must be measured. The current method requires thousands of manual measurements, repeated manual data transcription, and months of manual analysis. The Pipe Crawling Activity Measurement System (PCAMS), developed by Carnegi...
[ { "created": "Tue, 29 Jan 2019 15:46:24 GMT", "version": "v1" } ]
2019-02-27
[ [ "Jones", "Heather", "" ], [ "Maley", "Siri", "" ], [ "Yonekawa", "Kenji", "" ], [ "Mousaei", "Mohammadreza", "" ], [ "Yesso", "J. David", "" ], [ "Kohanbash", "David", "" ], [ "Whittaker", "William", "" ]...
To decommission deactivated gaseous diffusion enrichment facilities, miles of contaminated pipe must be measured. The current method requires thousands of manual measurements, repeated manual data transcription, and months of manual analysis. The Pipe Crawling Activity Measurement System (PCAMS), developed by Carnegie ...
2312.09249
Xinyue Wei
Ruoxi Shi, Xinyue Wei, Cheng Wang, Hao Su
ZeroRF: Fast Sparse View 360{\deg} Reconstruction with Zero Pretraining
Project page: https://sarahweiii.github.io/zerorf/
null
null
null
cs.CV cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present ZeroRF, a novel per-scene optimization method addressing the challenge of sparse view 360{\deg} reconstruction in neural field representations. Current breakthroughs like Neural Radiance Fields (NeRF) have demonstrated high-fidelity image synthesis but struggle with sparse input views. Existing methods, su...
[ { "created": "Thu, 14 Dec 2023 18:59:32 GMT", "version": "v1" } ]
2023-12-15
[ [ "Shi", "Ruoxi", "" ], [ "Wei", "Xinyue", "" ], [ "Wang", "Cheng", "" ], [ "Su", "Hao", "" ] ]
We present ZeroRF, a novel per-scene optimization method addressing the challenge of sparse view 360{\deg} reconstruction in neural field representations. Current breakthroughs like Neural Radiance Fields (NeRF) have demonstrated high-fidelity image synthesis but struggle with sparse input views. Existing methods, such...
0710.4685
EDA Publishing Association
C. Bolchini, F. Salice, D. Sciuto, L. Pomante
Reliable System Specification for Self-Checking Data-Paths
Submitted on behalf of EDAA (http://www.edaa.com/)
Dans Design, Automation and Test in Europe - DATE'05, Munich : Allemagne (2005)
null
null
cs.AR
null
The design of reliable circuits has received a lot of attention in the past, leading to the definition of several design techniques introducing fault detection and fault tolerance properties in systems for critical applications/environments. Such design methodologies tackled the problem at different abstraction level...
[ { "created": "Thu, 25 Oct 2007 09:08:39 GMT", "version": "v1" } ]
2011-11-09
[ [ "Bolchini", "C.", "" ], [ "Salice", "F.", "" ], [ "Sciuto", "D.", "" ], [ "Pomante", "L.", "" ] ]
The design of reliable circuits has received a lot of attention in the past, leading to the definition of several design techniques introducing fault detection and fault tolerance properties in systems for critical applications/environments. Such design methodologies tackled the problem at different abstraction levels,...
2008.10192
Radoslav Fulek
Alon Efrat, Radoslav Fulek, Stephen Kobourov, Csaba D. T\'oth
Polygons with Prescribed Angles in 2D and 3D
15 pages, 9 figures, a new section about self-intersecting realizations in 3D
null
null
null
cs.CG cs.DM math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the construction of a polygon $P$ with $n$ vertices whose turning angles at the vertices are given by a sequence $A=(\alpha_0,\ldots, \alpha_{n-1})$, $\alpha_i\in (-\pi,\pi)$, for $i\in\{0,\ldots, n-1\}$. The problem of realizing $A$ by a polygon can be seen as that of constructing a straight-line drawing...
[ { "created": "Mon, 24 Aug 2020 05:19:06 GMT", "version": "v1" }, { "created": "Sun, 1 Nov 2020 16:51:06 GMT", "version": "v2" } ]
2020-11-03
[ [ "Efrat", "Alon", "" ], [ "Fulek", "Radoslav", "" ], [ "Kobourov", "Stephen", "" ], [ "Tóth", "Csaba D.", "" ] ]
We consider the construction of a polygon $P$ with $n$ vertices whose turning angles at the vertices are given by a sequence $A=(\alpha_0,\ldots, \alpha_{n-1})$, $\alpha_i\in (-\pi,\pi)$, for $i\in\{0,\ldots, n-1\}$. The problem of realizing $A$ by a polygon can be seen as that of constructing a straight-line drawing o...
2302.11843
K. J. Kevin Feng
K. J. Kevin Feng and David W. McDonald
Addressing UX Practitioners' Challenges in Designing ML Applications: an Interactive Machine Learning Approach
null
null
10.1145/3581641.3584064
null
cs.HC
http://creativecommons.org/licenses/by/4.0/
UX practitioners face novel challenges when designing user interfaces for machine learning (ML)-enabled applications. Interactive ML paradigms, like AutoML and interactive machine teaching, lower the barrier for non-expert end users to create, understand, and use ML models, but their application to UX practice is lar...
[ { "created": "Thu, 23 Feb 2023 08:18:41 GMT", "version": "v1" } ]
2023-02-24
[ [ "Feng", "K. J. Kevin", "" ], [ "McDonald", "David W.", "" ] ]
UX practitioners face novel challenges when designing user interfaces for machine learning (ML)-enabled applications. Interactive ML paradigms, like AutoML and interactive machine teaching, lower the barrier for non-expert end users to create, understand, and use ML models, but their application to UX practice is large...
2106.05568
Julie Gerlings
Julie Gerlings, Millie S{\o}ndergaard Jensen and Arisa Shollo
Explainable AI, but explainable to whom?
Book chapter for AI in Healthcare
null
10.1007/978-3-030-83620-7_7
null
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Advances in AI technologies have resulted in superior levels of AI-based model performance. However, this has also led to a greater degree of model complexity, resulting in 'black box' models. In response to the AI black box problem, the field of explainable AI (xAI) has emerged with the aim of providing explanations...
[ { "created": "Thu, 10 Jun 2021 07:47:33 GMT", "version": "v1" }, { "created": "Mon, 24 Oct 2022 11:20:06 GMT", "version": "v2" } ]
2022-10-25
[ [ "Gerlings", "Julie", "" ], [ "Jensen", "Millie Søndergaard", "" ], [ "Shollo", "Arisa", "" ] ]
Advances in AI technologies have resulted in superior levels of AI-based model performance. However, this has also led to a greater degree of model complexity, resulting in 'black box' models. In response to the AI black box problem, the field of explainable AI (xAI) has emerged with the aim of providing explanations c...
2308.02568
Juan Manuel Rodriguez
Juan Manuel Rodriguez and Antonela Tommasel
Weighted Multi-Level Feature Factorization for App ads CTR and installation prediction
null
null
null
null
cs.IR cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
This paper provides an overview of the approach we used as team ISISTANITOS for the ACM RecSys Challenge 2023. The competition was organized by ShareChat, and involved predicting the probability of a user clicking an app ad and/or installing an app, to improve deep funnel optimization and a special focus on user priv...
[ { "created": "Thu, 3 Aug 2023 08:56:24 GMT", "version": "v1" } ]
2023-08-08
[ [ "Rodriguez", "Juan Manuel", "" ], [ "Tommasel", "Antonela", "" ] ]
This paper provides an overview of the approach we used as team ISISTANITOS for the ACM RecSys Challenge 2023. The competition was organized by ShareChat, and involved predicting the probability of a user clicking an app ad and/or installing an app, to improve deep funnel optimization and a special focus on user privac...
2209.13464
Zhijian Ou
Hong Liu, Hao Peng, Zhijian Ou, Juanzi Li, Yi Huang and Junlan Feng
Information Extraction and Human-Robot Dialogue towards Real-life Tasks: A Baseline Study with the MobileCS Dataset
Accepted by EMNLP 2022 SereTOD Workshop
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, there have merged a class of task-oriented dialogue (TOD) datasets collected through Wizard-of-Oz simulated games. However, the Wizard-of-Oz data are in fact simulated data and thus are fundamentally different from real-life conversations, which are more noisy and casual. Recently, the SereTOD challenge is ...
[ { "created": "Tue, 27 Sep 2022 15:30:43 GMT", "version": "v1" }, { "created": "Tue, 18 Oct 2022 06:15:28 GMT", "version": "v2" } ]
2022-10-19
[ [ "Liu", "Hong", "" ], [ "Peng", "Hao", "" ], [ "Ou", "Zhijian", "" ], [ "Li", "Juanzi", "" ], [ "Huang", "Yi", "" ], [ "Feng", "Junlan", "" ] ]
Recently, there have merged a class of task-oriented dialogue (TOD) datasets collected through Wizard-of-Oz simulated games. However, the Wizard-of-Oz data are in fact simulated data and thus are fundamentally different from real-life conversations, which are more noisy and casual. Recently, the SereTOD challenge is or...
1705.06691
Suleiman Yerima
Mohammed K. Alzaylaee, Suleiman Y. Yerima, Sakir Sezer
Improving Dynamic Analysis of Android Apps Using Hybrid Test Input Generation
International Conference On Cyber Security And Protection Of Digital Services (Cyber Security 2017)
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Android OS has become the most popular mobile operating system leading to a significant increase in the spread of Android malware. Consequently, several static and dynamic analysis systems have been developed to detect Android malware. With dynamic analysis, efficient test input generation is needed in order to t...
[ { "created": "Thu, 18 May 2017 16:48:20 GMT", "version": "v1" } ]
2017-05-19
[ [ "Alzaylaee", "Mohammed K.", "" ], [ "Yerima", "Suleiman Y.", "" ], [ "Sezer", "Sakir", "" ] ]
The Android OS has become the most popular mobile operating system leading to a significant increase in the spread of Android malware. Consequently, several static and dynamic analysis systems have been developed to detect Android malware. With dynamic analysis, efficient test input generation is needed in order to tri...