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2302.02345
Botong Zhu
Botong Zhu and Huobin Tan
VuLASTE: Long Sequence Model with Abstract Syntax Tree Embedding for vulnerability Detection
null
null
null
null
cs.SE cs.AI
http://creativecommons.org/licenses/by-sa/4.0/
In this paper, we build a model named VuLASTE, which regards vulnerability detection as a special text classification task. To solve the vocabulary explosion problem, VuLASTE uses a byte level BPE algorithm from natural language processing. In VuLASTE, a new AST path embedding is added to represent source code nestin...
[ { "created": "Sun, 5 Feb 2023 09:17:02 GMT", "version": "v1" } ]
2023-02-07
[ [ "Zhu", "Botong", "" ], [ "Tan", "Huobin", "" ] ]
In this paper, we build a model named VuLASTE, which regards vulnerability detection as a special text classification task. To solve the vocabulary explosion problem, VuLASTE uses a byte level BPE algorithm from natural language processing. In VuLASTE, a new AST path embedding is added to represent source code nesting ...
2009.07717
Sara Ahmed
Sara Atito Ali Ahmed, Berrin Yanikoglu
Relative Attribute Classification with Deep Rank SVM
null
null
10.1007/978-3-030-68790-8_51
null
cs.CV cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Relative attributes indicate the strength of a particular attribute between image pairs. We introduce a deep Siamese network with rank SVM loss function, called Deep Rank SVM (DRSVM), in order to decide which one of a pair of images has a stronger presence of a specific attribute. The network is trained in an end-to-...
[ { "created": "Wed, 9 Sep 2020 09:21:39 GMT", "version": "v1" } ]
2021-11-16
[ [ "Ahmed", "Sara Atito Ali", "" ], [ "Yanikoglu", "Berrin", "" ] ]
Relative attributes indicate the strength of a particular attribute between image pairs. We introduce a deep Siamese network with rank SVM loss function, called Deep Rank SVM (DRSVM), in order to decide which one of a pair of images has a stronger presence of a specific attribute. The network is trained in an end-to-en...
1609.09541
H\'ector P\'erez L\'opez-Portillo
P\'erez L\'opez-Portillo, H\'ector, V\'azquez Gonz\'alez, Edgar Ren\'e, Romero Hidalgo, Jorge Alberto
Knowledge management metrics for Public Organizations: A literature review-based proposal
conference proceedings
null
10.13140/RG.2.2.24281.11368/1
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Knowledge Management (KM) is a relatively new phenomenon that appears in the field of Public Sector Organizations (PSO) bringing new paradigms of organizational management, challenges, risks and opportunities for its implementation, development and evaluation. KM can be seen as a systematic and deliberate effort to c...
[ { "created": "Thu, 29 Sep 2016 22:36:04 GMT", "version": "v1" } ]
2016-10-03
[ [ "López-Portillo", "Pérez", "" ], [ "Héctor", "", "" ], [ "González", "Vázquez", "" ], [ "René", "Edgar", "" ], [ "Hidalgo", "Romero", "" ], [ "Alberto", "Jorge", "" ] ]
Knowledge Management (KM) is a relatively new phenomenon that appears in the field of Public Sector Organizations (PSO) bringing new paradigms of organizational management, challenges, risks and opportunities for its implementation, development and evaluation. KM can be seen as a systematic and deliberate effort to coo...
2404.15971
Xin Zhang
Xin Zhang, Wenwen Liu
Boosting Architectural Generation via Prompts: Report
Brief report of Achitectural prompts
null
null
null
cs.HC
http://creativecommons.org/licenses/by/4.0/
In the realm of AI architectural design, the importance of prompts is becoming increasingly prominent. With advancements in artificial intelligence and large-scale model technology, more design tasks are being delegated to machine learning algorithms. This necessitates a method for designers to guide algorithms in pr...
[ { "created": "Wed, 24 Apr 2024 16:44:25 GMT", "version": "v1" } ]
2024-04-25
[ [ "Zhang", "Xin", "" ], [ "Liu", "Wenwen", "" ] ]
In the realm of AI architectural design, the importance of prompts is becoming increasingly prominent. With advancements in artificial intelligence and large-scale model technology, more design tasks are being delegated to machine learning algorithms. This necessitates a method for designers to guide algorithms in prod...
1806.10174
Emilia Apostolova PhD
Tony Wang, Tom Velez, Emilia Apostolova, Tim Tschampel, Thuy L. Ngo, Joy Hardison
Semantically Enhanced Dynamic Bayesian Network for Detecting Sepsis Mortality Risk in ICU Patients with Infection
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Although timely sepsis diagnosis and prompt interventions in Intensive Care Unit (ICU) patients are associated with reduced mortality, early clinical recognition is frequently impeded by non-specific signs of infection and failure to detect signs of sepsis-induced organ dysfunction in a constellation of dynamically c...
[ { "created": "Tue, 26 Jun 2018 19:09:19 GMT", "version": "v1" } ]
2018-06-28
[ [ "Wang", "Tony", "" ], [ "Velez", "Tom", "" ], [ "Apostolova", "Emilia", "" ], [ "Tschampel", "Tim", "" ], [ "Ngo", "Thuy L.", "" ], [ "Hardison", "Joy", "" ] ]
Although timely sepsis diagnosis and prompt interventions in Intensive Care Unit (ICU) patients are associated with reduced mortality, early clinical recognition is frequently impeded by non-specific signs of infection and failure to detect signs of sepsis-induced organ dysfunction in a constellation of dynamically cha...
2301.03128
Aria Nosratinia
Heping Wan, Anders Host-Madsen, Aria Nosratinia
Compress-and-Forward via Multilevel Coding and Trellis Coded Quantization
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Compress-forward (CF) relays can improve communication rates even when the relay cannot decode the source signal. Efficient implementation of CF is a topic of contemporary interest, in part because of its potential impact on wireless technologies such as cloud-RAN. There exists a gap between the performance of CF imp...
[ { "created": "Mon, 9 Jan 2023 00:33:56 GMT", "version": "v1" } ]
2023-01-10
[ [ "Wan", "Heping", "" ], [ "Host-Madsen", "Anders", "" ], [ "Nosratinia", "Aria", "" ] ]
Compress-forward (CF) relays can improve communication rates even when the relay cannot decode the source signal. Efficient implementation of CF is a topic of contemporary interest, in part because of its potential impact on wireless technologies such as cloud-RAN. There exists a gap between the performance of CF imple...
2404.19154
Ning An
Ning An, Lei Hei, Yong Jiang, Weiping Meng, Jingjing Hu, Boran Huang, Feiliang Ren
RTF: Region-based Table Filling Method for Relational Triple Extraction
Rejected by EMNLP 2023
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Relational triple extraction is crucial work for the automatic construction of knowledge graphs. Existing methods only construct shallow representations from a token or token pair-level. However, previous works ignore local spatial dependencies of relational triples, resulting in a weakness of entity pair boundary de...
[ { "created": "Mon, 29 Apr 2024 23:36:38 GMT", "version": "v1" }, { "created": "Thu, 13 Jun 2024 16:26:15 GMT", "version": "v2" } ]
2024-06-14
[ [ "An", "Ning", "" ], [ "Hei", "Lei", "" ], [ "Jiang", "Yong", "" ], [ "Meng", "Weiping", "" ], [ "Hu", "Jingjing", "" ], [ "Huang", "Boran", "" ], [ "Ren", "Feiliang", "" ] ]
Relational triple extraction is crucial work for the automatic construction of knowledge graphs. Existing methods only construct shallow representations from a token or token pair-level. However, previous works ignore local spatial dependencies of relational triples, resulting in a weakness of entity pair boundary dete...
2305.08063
Jingbo Liu
Jingbo Liu
From Soft-Minoration to Information-Constrained Optimal Transport and Spiked Tensor Models
ISIT 2023
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Let $P_Z$ be a given distribution on $\mathbb{R}^n$. For any $y\in\mathbb{R}^n$, we may interpret $\rho(y):=\ln\mathbb{E}[e^{\left<y,Z\right>}]$ as a soft-max of $\left<y,Z\right>$. We explore lower bounds on $\mathbb{E}[\rho(Y)]$ in terms of the minimum mutual information $I(Z,\bar{Z})$ over $P_{Z\bar{Z}}$ which is ...
[ { "created": "Sun, 14 May 2023 04:20:04 GMT", "version": "v1" } ]
2023-05-16
[ [ "Liu", "Jingbo", "" ] ]
Let $P_Z$ be a given distribution on $\mathbb{R}^n$. For any $y\in\mathbb{R}^n$, we may interpret $\rho(y):=\ln\mathbb{E}[e^{\left<y,Z\right>}]$ as a soft-max of $\left<y,Z\right>$. We explore lower bounds on $\mathbb{E}[\rho(Y)]$ in terms of the minimum mutual information $I(Z,\bar{Z})$ over $P_{Z\bar{Z}}$ which is a ...
1610.09530
Ying Cui
Chengjun Guo, Ying Cui, Derrick Wing Kwan Ng and Zhi Liu
Multi-Quality Multicast Beamforming based on Scalable Video Coding
30 pages, submitted to GLOBECOM 2017 and TCOM
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we consider multi-quality multicast beamforming of a video stream from a multi-antenna base station (BS) to multiple single-antenna users receiving different qualities of the same video stream, via scalable video coding (SVC). Leveraging the layered structure of SVC and exploiting superposition coding ...
[ { "created": "Sat, 29 Oct 2016 15:27:08 GMT", "version": "v1" }, { "created": "Sat, 15 Jul 2017 00:47:31 GMT", "version": "v2" } ]
2017-07-18
[ [ "Guo", "Chengjun", "" ], [ "Cui", "Ying", "" ], [ "Ng", "Derrick Wing Kwan", "" ], [ "Liu", "Zhi", "" ] ]
In this paper, we consider multi-quality multicast beamforming of a video stream from a multi-antenna base station (BS) to multiple single-antenna users receiving different qualities of the same video stream, via scalable video coding (SVC). Leveraging the layered structure of SVC and exploiting superposition coding (S...
1910.07169
Lanlan Liu
Lanlan Liu, Michael Muelly, Jia Deng, Tomas Pfister, Li-Jia Li
Generative Modeling for Small-Data Object Detection
Published in ICCV 2019
null
null
null
cs.CV cs.LG eess.IV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper explores object detection in the small data regime, where only a limited number of annotated bounding boxes are available due to data rarity and annotation expense. This is a common challenge today with machine learning being applied to many new tasks where obtaining training data is more challenging, e.g....
[ { "created": "Wed, 16 Oct 2019 04:57:25 GMT", "version": "v1" } ]
2019-10-17
[ [ "Liu", "Lanlan", "" ], [ "Muelly", "Michael", "" ], [ "Deng", "Jia", "" ], [ "Pfister", "Tomas", "" ], [ "Li", "Li-Jia", "" ] ]
This paper explores object detection in the small data regime, where only a limited number of annotated bounding boxes are available due to data rarity and annotation expense. This is a common challenge today with machine learning being applied to many new tasks where obtaining training data is more challenging, e.g. i...
1905.08022
Caifa Zhou
Caifa Zhou and Andreas Wieser
An iterative scheme for feature based positioning using a weighted dissimilarity measure
18 pages, 9 figures, and 1 table
null
null
null
cs.LG stat.AP stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose an iterative scheme for feature-based positioning using a new weighted dissimilarity measure with the goal of reducing the impact of large errors among the measured or modeled features. The weights are computed from the location-dependent standard deviations of the features and stored as part of the refere...
[ { "created": "Mon, 20 May 2019 12:12:38 GMT", "version": "v1" }, { "created": "Thu, 30 May 2019 14:56:24 GMT", "version": "v2" } ]
2019-05-31
[ [ "Zhou", "Caifa", "" ], [ "Wieser", "Andreas", "" ] ]
We propose an iterative scheme for feature-based positioning using a new weighted dissimilarity measure with the goal of reducing the impact of large errors among the measured or modeled features. The weights are computed from the location-dependent standard deviations of the features and stored as part of the referenc...
1409.5317
Scott MacLean
Scott MacLean and George Labahn
A Bayesian model for recognizing handwritten mathematical expressions
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recognizing handwritten mathematics is a challenging classification problem, requiring simultaneous identification of all the symbols comprising an input as well as the complex two-dimensional relationships between symbols and subexpressions. Because of the ambiguity present in handwritten input, it is often unrealis...
[ { "created": "Thu, 18 Sep 2014 14:45:24 GMT", "version": "v1" } ]
2014-09-19
[ [ "MacLean", "Scott", "" ], [ "Labahn", "George", "" ] ]
Recognizing handwritten mathematics is a challenging classification problem, requiring simultaneous identification of all the symbols comprising an input as well as the complex two-dimensional relationships between symbols and subexpressions. Because of the ambiguity present in handwritten input, it is often unrealisti...
1405.3311
Ugo Dal Lago
Beniamino Accattoli, Ugo Dal Lago
Beta Reduction is Invariant, Indeed (Long Version)
29 pages
null
null
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Slot and van Emde Boas' weak invariance thesis states that reasonable machines can simulate each other within a polynomially overhead in time. Is $\lambda$-calculus a reasonable machine? Is there a way to measure the computational complexity of a $\lambda$-term? This paper presents the first complete positive answer ...
[ { "created": "Tue, 13 May 2014 21:23:58 GMT", "version": "v1" } ]
2014-05-15
[ [ "Accattoli", "Beniamino", "" ], [ "Lago", "Ugo Dal", "" ] ]
Slot and van Emde Boas' weak invariance thesis states that reasonable machines can simulate each other within a polynomially overhead in time. Is $\lambda$-calculus a reasonable machine? Is there a way to measure the computational complexity of a $\lambda$-term? This paper presents the first complete positive answer to...
1709.01710
Marina Ljubenovi\'c
Marina Ljubenovi\'c and M\'ario A. T. Figueiredo
Blind image deblurring using class-adapted image priors
5 pages
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Blind image deblurring (BID) is an ill-posed inverse problem, usually addressed by imposing prior knowledge on the (unknown) image and on the blurring filter. Most of the work on BID has focused on natural images, using image priors based on statistical properties of generic natural images. However, in many applicati...
[ { "created": "Wed, 6 Sep 2017 08:20:10 GMT", "version": "v1" } ]
2017-09-07
[ [ "Ljubenović", "Marina", "" ], [ "Figueiredo", "Mário A. T.", "" ] ]
Blind image deblurring (BID) is an ill-posed inverse problem, usually addressed by imposing prior knowledge on the (unknown) image and on the blurring filter. Most of the work on BID has focused on natural images, using image priors based on statistical properties of generic natural images. However, in many application...
2203.11092
Hang Dong
Hang Dong, Mat\'u\v{s} Falis, William Whiteley, Beatrice Alex, Joshua Matterson, Shaoxiong Ji, Jiaoyan Chen, Honghan Wu
Automated Clinical Coding: What, Why, and Where We Are?
accepted for npj Digital Medicine
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Clinical coding is the task of transforming medical information in a patient's health records into structured codes so that they can be used for statistical analysis. This is a cognitive and time-consuming task that follows a standard process in order to achieve a high level of consistency. Clinical coding could pote...
[ { "created": "Mon, 21 Mar 2022 16:17:38 GMT", "version": "v1" }, { "created": "Wed, 31 Aug 2022 13:58:00 GMT", "version": "v2" }, { "created": "Sun, 9 Oct 2022 14:18:20 GMT", "version": "v3" } ]
2022-10-11
[ [ "Dong", "Hang", "" ], [ "Falis", "Matúš", "" ], [ "Whiteley", "William", "" ], [ "Alex", "Beatrice", "" ], [ "Matterson", "Joshua", "" ], [ "Ji", "Shaoxiong", "" ], [ "Chen", "Jiaoyan", "" ], [ "Wu"...
Clinical coding is the task of transforming medical information in a patient's health records into structured codes so that they can be used for statistical analysis. This is a cognitive and time-consuming task that follows a standard process in order to achieve a high level of consistency. Clinical coding could potent...
2203.15425
Radek O\v{s}lej\v{s}ek
Martin Macak and Radek Oslejsek and Barbora Buhnova
Process Mining Analysis of Puzzle-Based Cybersecurity Training
null
null
10.1145/3502718.3524819
null
cs.CR cs.IR
http://creativecommons.org/licenses/by/4.0/
The hands-on cybersecurity training quality is crucial to mitigate cyber threats and attacks effectively. However, practical cybersecurity training is strongly process-oriented, making the post-training analysis very difficult. This paper presents process-mining methods applied to the learning analytics workflow. We ...
[ { "created": "Tue, 29 Mar 2022 10:45:05 GMT", "version": "v1" } ]
2022-03-30
[ [ "Macak", "Martin", "" ], [ "Oslejsek", "Radek", "" ], [ "Buhnova", "Barbora", "" ] ]
The hands-on cybersecurity training quality is crucial to mitigate cyber threats and attacks effectively. However, practical cybersecurity training is strongly process-oriented, making the post-training analysis very difficult. This paper presents process-mining methods applied to the learning analytics workflow. We in...
1710.10453
Avi Caciularu
Mor Cohen, Avi Caciularu, Idan Rejwan, Jonathan Berant
Inducing Regular Grammars Using Recurrent Neural Networks
Accepted to L&R 2018 workshop, ICML & IJCAI
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Grammar induction is the task of learning a grammar from a set of examples. Recently, neural networks have been shown to be powerful learning machines that can identify patterns in streams of data. In this work we investigate their effectiveness in inducing a regular grammar from data, without any assumptions about t...
[ { "created": "Sat, 28 Oct 2017 12:00:09 GMT", "version": "v1" }, { "created": "Tue, 26 Jun 2018 14:27:47 GMT", "version": "v2" } ]
2018-06-27
[ [ "Cohen", "Mor", "" ], [ "Caciularu", "Avi", "" ], [ "Rejwan", "Idan", "" ], [ "Berant", "Jonathan", "" ] ]
Grammar induction is the task of learning a grammar from a set of examples. Recently, neural networks have been shown to be powerful learning machines that can identify patterns in streams of data. In this work we investigate their effectiveness in inducing a regular grammar from data, without any assumptions about the...
1906.00114
Tom\'a\v{s} Musil
Tom\'a\v{s} Musil
Examining Structure of Word Embeddings with PCA
12 pages, 6 figures, accepted to The 22th International Conference of Text, Speech and Dialogue (TSD2019) in Ljubljana
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we compare structure of Czech word embeddings for English-Czech neural machine translation (NMT), word2vec and sentiment analysis. We show that although it is possible to successfully predict part of speech (POS) tags from word embeddings of word2vec and various translation models, not all of the embedd...
[ { "created": "Fri, 31 May 2019 22:47:56 GMT", "version": "v1" } ]
2019-06-04
[ [ "Musil", "Tomáš", "" ] ]
In this paper we compare structure of Czech word embeddings for English-Czech neural machine translation (NMT), word2vec and sentiment analysis. We show that although it is possible to successfully predict part of speech (POS) tags from word embeddings of word2vec and various translation models, not all of the embeddin...
2009.12215
Chengwen Xing
Chengwen Xing, Shuai Wang, Sheng Chen, Shaodan Ma, H. Vincent Poor, Lajos Hanzo
Matrix-Monotonic Optimization Part II: Multi-Variable Optimization
Final version published in IEEE Transactions on Signal Processing. arXiv admin note: substantial text overlap with arXiv:1810.11244
null
10.1109/TSP.2020.3037495
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In contrast to Part I of this treatise [1] that focuses on the optimization problems associated with single matrix variables, in this paper, we investigate the application of the matrix-monotonic optimization framework in the optimization problems associated with multiple matrix variables. It is revealed that matrix-...
[ { "created": "Thu, 24 Sep 2020 02:04:03 GMT", "version": "v1" } ]
2021-02-24
[ [ "Xing", "Chengwen", "" ], [ "Wang", "Shuai", "" ], [ "Chen", "Sheng", "" ], [ "Ma", "Shaodan", "" ], [ "Poor", "H. Vincent", "" ], [ "Hanzo", "Lajos", "" ] ]
In contrast to Part I of this treatise [1] that focuses on the optimization problems associated with single matrix variables, in this paper, we investigate the application of the matrix-monotonic optimization framework in the optimization problems associated with multiple matrix variables. It is revealed that matrix-mo...
2206.06518
Vandad Davoodnia
Vandad Davoodnia, Saeed Ghorbani, Ali Etemad
Estimating Pose from Pressure Data for Smart Beds with Deep Image-based Pose Estimators
The version of record of this article, first published in Applied Intelligence, is available online at Publisher's website https://doi.org/10.1007/s10489-021-02418-y. arXiv admin note: substantial text overlap with arXiv:1908.08919
Applied Intelligence (2021): 1-15
10.1007/s10489-021-02418-y
1573-7497
cs.CV
http://creativecommons.org/licenses/by/4.0/
In-bed pose estimation has shown value in fields such as hospital patient monitoring, sleep studies, and smart homes. In this paper, we explore different strategies for detecting body pose from highly ambiguous pressure data, with the aid of pre-existing pose estimators. We examine the performance of pre-trained pose...
[ { "created": "Mon, 13 Jun 2022 23:29:28 GMT", "version": "v1" } ]
2022-06-15
[ [ "Davoodnia", "Vandad", "" ], [ "Ghorbani", "Saeed", "" ], [ "Etemad", "Ali", "" ] ]
In-bed pose estimation has shown value in fields such as hospital patient monitoring, sleep studies, and smart homes. In this paper, we explore different strategies for detecting body pose from highly ambiguous pressure data, with the aid of pre-existing pose estimators. We examine the performance of pre-trained pose e...
2306.04261
Fardad Vakilipoor
Fardad Vakilipoor, Luca Barletta, Stefano Bregni, and Maurizio Magarini
Achievable Rate Analysis in Molecular Channels with Reset-Counting Fully Absorbing Receivers
Submitted to IEEE Global Communications Conference, December 2023, Kuala Lumpur, Malaysia
null
null
null
cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
In this paper, we investigate the achievable rate of a diffusive Molecular Communication (MC) channel with fully absorbing receiver, which counts particles absorbed along each symbol interval and resets the counter at every interval (reset-counting). The MC channel is affected by a memory effect and thus inter-symbol...
[ { "created": "Wed, 7 Jun 2023 08:59:39 GMT", "version": "v1" } ]
2023-06-08
[ [ "Vakilipoor", "Fardad", "" ], [ "Barletta", "Luca", "" ], [ "Bregni", "Stefano", "" ], [ "Magarini", "Maurizio", "" ] ]
In this paper, we investigate the achievable rate of a diffusive Molecular Communication (MC) channel with fully absorbing receiver, which counts particles absorbed along each symbol interval and resets the counter at every interval (reset-counting). The MC channel is affected by a memory effect and thus inter-symbol i...
2105.13287
Dung Nguyen
Dung Nguyen and Anil Vullikanti
Differentially Private Densest Subgraph Detection
Accepted by ICML 2021
null
null
null
cs.DS cs.AI cs.CR cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
Densest subgraph detection is a fundamental graph mining problem, with a large number of applications. There has been a lot of work on efficient algorithms for finding the densest subgraph in massive networks. However, in many domains, the network is private, and returning a densest subgraph can reveal information ab...
[ { "created": "Thu, 27 May 2021 16:36:03 GMT", "version": "v1" }, { "created": "Fri, 18 Jun 2021 17:33:02 GMT", "version": "v2" } ]
2024-06-05
[ [ "Nguyen", "Dung", "" ], [ "Vullikanti", "Anil", "" ] ]
Densest subgraph detection is a fundamental graph mining problem, with a large number of applications. There has been a lot of work on efficient algorithms for finding the densest subgraph in massive networks. However, in many domains, the network is private, and returning a densest subgraph can reveal information abou...
1709.03787
Balazs Vedres
Balazs Vedres
Forbidden triads and Creative Success in Jazz: The Miles Davis Factor
null
Applied Network Science (2017) 2:31
10.1007/s41109-017-0051-2
null
cs.SI nlin.AO stat.AP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This article argues for the importance of forbidden triads - open triads with high-weight edges - in predicting success in creative fields. Forbidden triads had been treated as a residual category beyond closed and open triads, yet I argue that these structures provide opportunities to combine socially evolved styles...
[ { "created": "Tue, 12 Sep 2017 11:28:25 GMT", "version": "v1" } ]
2017-10-06
[ [ "Vedres", "Balazs", "" ] ]
This article argues for the importance of forbidden triads - open triads with high-weight edges - in predicting success in creative fields. Forbidden triads had been treated as a residual category beyond closed and open triads, yet I argue that these structures provide opportunities to combine socially evolved styles i...
1804.07675
Christian H\"ager
Shen Li, Christian H\"ager, Nil Garcia, Henk Wymeersch
Achievable Information Rates for Nonlinear Fiber Communication via End-to-end Autoencoder Learning
3 pages, 4 figures, fixed typos, revised layout
null
null
null
cs.IT math.IT stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Machine learning is used to compute achievable information rates (AIRs) for a simplified fiber channel. The approach jointly optimizes the input distribution (constellation shaping) and the auxiliary channel distribution to compute AIRs without explicit channel knowledge in an end-to-end fashion.
[ { "created": "Fri, 20 Apr 2018 15:30:06 GMT", "version": "v1" }, { "created": "Mon, 17 Sep 2018 08:58:55 GMT", "version": "v2" } ]
2018-09-18
[ [ "Li", "Shen", "" ], [ "Häger", "Christian", "" ], [ "Garcia", "Nil", "" ], [ "Wymeersch", "Henk", "" ] ]
Machine learning is used to compute achievable information rates (AIRs) for a simplified fiber channel. The approach jointly optimizes the input distribution (constellation shaping) and the auxiliary channel distribution to compute AIRs without explicit channel knowledge in an end-to-end fashion.
2205.14458
Longzhen Yang
Longzhen Yang, Yihang Liu, Yitao Peng, Lianghua He
Variational Transformer: A Framework Beyond the Trade-off between Accuracy and Diversity for Image Captioning
null
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Accuracy and Diversity are two essential metrizable manifestations in generating natural and semantically correct captions. Many efforts have been made to enhance one of them with another decayed due to the trade-off gap. In this work, we will show that the inferior standard of accuracy draws from human annotations (...
[ { "created": "Sat, 28 May 2022 15:29:14 GMT", "version": "v1" }, { "created": "Wed, 21 Sep 2022 12:21:58 GMT", "version": "v2" } ]
2022-09-22
[ [ "Yang", "Longzhen", "" ], [ "Liu", "Yihang", "" ], [ "Peng", "Yitao", "" ], [ "He", "Lianghua", "" ] ]
Accuracy and Diversity are two essential metrizable manifestations in generating natural and semantically correct captions. Many efforts have been made to enhance one of them with another decayed due to the trade-off gap. In this work, we will show that the inferior standard of accuracy draws from human annotations (le...
2103.06125
Lucas N. Ferreira
Lucas N. Ferreira, Jim Whitehead
Learning to Generate Music With Sentiment
International Society for Music Information Retrieval (2019)
null
null
null
cs.LG cs.IR cs.SD eess.AS
http://creativecommons.org/licenses/by/4.0/
Deep Learning models have shown very promising results in automatically composing polyphonic music pieces. However, it is very hard to control such models in order to guide the compositions towards a desired goal. We are interested in controlling a model to automatically generate music with a given sentiment. This pa...
[ { "created": "Tue, 9 Mar 2021 03:16:52 GMT", "version": "v1" } ]
2021-03-11
[ [ "Ferreira", "Lucas N.", "" ], [ "Whitehead", "Jim", "" ] ]
Deep Learning models have shown very promising results in automatically composing polyphonic music pieces. However, it is very hard to control such models in order to guide the compositions towards a desired goal. We are interested in controlling a model to automatically generate music with a given sentiment. This pape...
2202.04067
Yedid Hoshen
Yedid Hoshen
Time Series Anomaly Detection by Cumulative Radon Features
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Detecting anomalous time series is key for scientific, medical and industrial tasks, but is challenging due to its inherent unsupervised nature. In recent years, progress has been made on this task by learning increasingly more complex features, often using deep neural networks. In this work, we argue that shallow fe...
[ { "created": "Tue, 8 Feb 2022 18:58:53 GMT", "version": "v1" } ]
2022-02-09
[ [ "Hoshen", "Yedid", "" ] ]
Detecting anomalous time series is key for scientific, medical and industrial tasks, but is challenging due to its inherent unsupervised nature. In recent years, progress has been made on this task by learning increasingly more complex features, often using deep neural networks. In this work, we argue that shallow feat...
1802.01618
Imene Trigui
Imene Trigui, and Sofiene Affes
Unified Analysis and Optimization of D2D Communications in Cellular Networks Over Fading Channels
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper develops an innovative approach to the modeling and analysis of downlink cellular networks with device-to-device (D$2$D) transmissions. The analytical embodiment of the signal-to-noise and-interference ratio (SINR) analysis in general fading channels is unified due to the H-transform theory, a taxonomy nev...
[ { "created": "Mon, 5 Feb 2018 19:34:40 GMT", "version": "v1" }, { "created": "Thu, 12 Apr 2018 19:27:26 GMT", "version": "v2" } ]
2018-04-16
[ [ "Trigui", "Imene", "" ], [ "Affes", "Sofiene", "" ] ]
This paper develops an innovative approach to the modeling and analysis of downlink cellular networks with device-to-device (D$2$D) transmissions. The analytical embodiment of the signal-to-noise and-interference ratio (SINR) analysis in general fading channels is unified due to the H-transform theory, a taxonomy never...
2008.11055
Luciano Oliveira
Gabriel Lefundes, Luciano Oliveira
On estimating gaze by self-attention augmented convolutions
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Estimation of 3D gaze is highly relevant to multiple fields, including but not limited to interactive systems, specialized human-computer interfaces, and behavioral research. Although recently deep learning methods have boosted the accuracy of appearance-based gaze estimation, there is still room for improvement in t...
[ { "created": "Tue, 25 Aug 2020 14:29:05 GMT", "version": "v1" }, { "created": "Tue, 3 Nov 2020 13:49:19 GMT", "version": "v2" } ]
2020-11-04
[ [ "Lefundes", "Gabriel", "" ], [ "Oliveira", "Luciano", "" ] ]
Estimation of 3D gaze is highly relevant to multiple fields, including but not limited to interactive systems, specialized human-computer interfaces, and behavioral research. Although recently deep learning methods have boosted the accuracy of appearance-based gaze estimation, there is still room for improvement in the...
1809.00258
Yogatheesan Varatharajah
Yogatheesan Varatharajah, Brent Berry, Sanmi Koyejo, and Ravishankar Iyer
A Contextual-bandit-based Approach for Informed Decision-making in Clinical Trials
13 pages, 2 figures
null
null
null
cs.AI stat.AP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Clinical trials involving multiple treatments utilize randomization of the treatment assignments to enable the evaluation of treatment efficacies in an unbiased manner. Such evaluation is performed in post hoc studies that usually use supervised-learning methods that rely on large amounts of data collected in a rando...
[ { "created": "Sat, 1 Sep 2018 22:07:23 GMT", "version": "v1" } ]
2018-09-10
[ [ "Varatharajah", "Yogatheesan", "" ], [ "Berry", "Brent", "" ], [ "Koyejo", "Sanmi", "" ], [ "Iyer", "Ravishankar", "" ] ]
Clinical trials involving multiple treatments utilize randomization of the treatment assignments to enable the evaluation of treatment efficacies in an unbiased manner. Such evaluation is performed in post hoc studies that usually use supervised-learning methods that rely on large amounts of data collected in a randomi...
2204.11138
Su Jiang
Su Jiang, Louis J. Durlofsky
Use of Multifidelity Training Data and Transfer Learning for Efficient Construction of Subsurface Flow Surrogate Models
null
null
10.1016/j.jcp.2022.111800
null
cs.LG physics.geo-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Data assimilation presents computational challenges because many high-fidelity models must be simulated. Various deep-learning-based surrogate modeling techniques have been developed to reduce the simulation costs associated with these applications. However, to construct data-driven surrogate models, several thousand...
[ { "created": "Sat, 23 Apr 2022 20:09:49 GMT", "version": "v1" } ]
2022-12-28
[ [ "Jiang", "Su", "" ], [ "Durlofsky", "Louis J.", "" ] ]
Data assimilation presents computational challenges because many high-fidelity models must be simulated. Various deep-learning-based surrogate modeling techniques have been developed to reduce the simulation costs associated with these applications. However, to construct data-driven surrogate models, several thousand h...
1509.06084
EPTCS
J. Strother Moore (Department of Computer Science, The University of Texas at Austin)
Stateman: Using Metafunctions to Manage Large Terms Representing Machine States
In Proceedings ACL2 2015, arXiv:1509.05526
EPTCS 192, 2015, pp. 93-109
10.4204/EPTCS.192.8
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
When ACL2 is used to model the operational semantics of computing machines, machine states are typically represented by terms recording the contents of the state components. When models are realistic and are stepped through thousands of machine cycles, these terms can grow quite large and the cost of simplifying them...
[ { "created": "Mon, 21 Sep 2015 00:35:40 GMT", "version": "v1" } ]
2015-09-22
[ [ "Moore", "J. Strother", "", "Department of Computer Science, The University of\n Texas at Austin" ] ]
When ACL2 is used to model the operational semantics of computing machines, machine states are typically represented by terms recording the contents of the state components. When models are realistic and are stepped through thousands of machine cycles, these terms can grow quite large and the cost of simplifying them o...
2404.02152
Chong Bao
Chong Bao, Yinda Zhang, Yuan Li, Xiyu Zhang, Bangbang Yang, Hujun Bao, Marc Pollefeys, Guofeng Zhang, Zhaopeng Cui
GeneAvatar: Generic Expression-Aware Volumetric Head Avatar Editing from a Single Image
Accepted to CVPR 2024. Project page: https://zju3dv.github.io/geneavatar/
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Recently, we have witnessed the explosive growth of various volumetric representations in modeling animatable head avatars. However, due to the diversity of frameworks, there is no practical method to support high-level applications like 3D head avatar editing across different representations. In this paper, we propo...
[ { "created": "Tue, 2 Apr 2024 17:58:35 GMT", "version": "v1" } ]
2024-04-03
[ [ "Bao", "Chong", "" ], [ "Zhang", "Yinda", "" ], [ "Li", "Yuan", "" ], [ "Zhang", "Xiyu", "" ], [ "Yang", "Bangbang", "" ], [ "Bao", "Hujun", "" ], [ "Pollefeys", "Marc", "" ], [ "Zhang", "Guofen...
Recently, we have witnessed the explosive growth of various volumetric representations in modeling animatable head avatars. However, due to the diversity of frameworks, there is no practical method to support high-level applications like 3D head avatar editing across different representations. In this paper, we propose...
1910.02655
Amir Soleimani
Amir Soleimani, Christof Monz, Marcel Worring
BERT for Evidence Retrieval and Claim Verification
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Motivated by the promising performance of pre-trained language models, we investigate BERT in an evidence retrieval and claim verification pipeline for the FEVER fact extraction and verification challenge. To this end, we propose to use two BERT models, one for retrieving potential evidence sentences supporting or re...
[ { "created": "Mon, 7 Oct 2019 07:58:26 GMT", "version": "v1" } ]
2019-10-08
[ [ "Soleimani", "Amir", "" ], [ "Monz", "Christof", "" ], [ "Worring", "Marcel", "" ] ]
Motivated by the promising performance of pre-trained language models, we investigate BERT in an evidence retrieval and claim verification pipeline for the FEVER fact extraction and verification challenge. To this end, we propose to use two BERT models, one for retrieving potential evidence sentences supporting or reje...
2203.15448
H\"armel Nestra
Dan Bogdanov (1), Joosep J\"a\"ager (1), Peeter Laud (1), H\"armel Nestra (1), Martin Pettai (1), Jaak Randmets (1), Ville Sokk (1), Kert Tali (1), Sandhra-Mirella Valdma (1) ((1) Cybernetica AS)
ZK-SecreC: a Domain-Specific Language for Zero Knowledge Proofs
75 pp
null
null
null
cs.PL cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present ZK-SecreC, a domain-specific language for zero-knowledge proofs. We present the rationale for its design, its syntax and semantics, and demonstrate its usefulness on the basis of a number of non-trivial examples. The design features a type system, where each piece of data is assigned both a confidentiality...
[ { "created": "Tue, 29 Mar 2022 11:35:11 GMT", "version": "v1" }, { "created": "Fri, 26 Aug 2022 13:43:41 GMT", "version": "v2" } ]
2022-08-29
[ [ "Bogdanov", "Dan", "", "Cybernetica AS" ], [ "Jääger", "Joosep", "", "Cybernetica AS" ], [ "Laud", "Peeter", "", "Cybernetica AS" ], [ "Nestra", "Härmel", "", "Cybernetica AS" ], [ "Pettai", "Martin", "", "Cybernetica ...
We present ZK-SecreC, a domain-specific language for zero-knowledge proofs. We present the rationale for its design, its syntax and semantics, and demonstrate its usefulness on the basis of a number of non-trivial examples. The design features a type system, where each piece of data is assigned both a confidentiality a...
2107.14297
Enrico Ubaldi
Enrico Ubaldi, Takahiro Yabe, Nicholas K. W. Jones, Maham Faisal Khan, Satish V. Ukkusuri, Riccardo Di Clemente, Emanuele Strano
Mobilkit: A Python Toolkit for Urban Resilience and Disaster Risk Management Analytics using High Frequency Human Mobility Data
3 pages, 1 figure, KDD KDD Workshop on Data-driven Humanitarian Mapping, 27th ACM SIGKDD Conference
Journal of Open Source Software, 9(95), 5201, 2024
10.21105/joss.05201
null
cs.CY cs.SI physics.soc-ph
http://creativecommons.org/licenses/by-nc-sa/4.0/
Increasingly available high-frequency location datasets derived from smartphones provide unprecedented insight into trajectories of human mobility. These datasets can play a significant and growing role in informing preparedness and response to natural disasters. However, limited tools exist to enable rapid analytics...
[ { "created": "Thu, 29 Jul 2021 19:49:54 GMT", "version": "v1" }, { "created": "Thu, 16 Sep 2021 08:54:13 GMT", "version": "v2" } ]
2024-03-05
[ [ "Ubaldi", "Enrico", "" ], [ "Yabe", "Takahiro", "" ], [ "Jones", "Nicholas K. W.", "" ], [ "Khan", "Maham Faisal", "" ], [ "Ukkusuri", "Satish V.", "" ], [ "Di Clemente", "Riccardo", "" ], [ "Strano", "Emanuele...
Increasingly available high-frequency location datasets derived from smartphones provide unprecedented insight into trajectories of human mobility. These datasets can play a significant and growing role in informing preparedness and response to natural disasters. However, limited tools exist to enable rapid analytics u...
2404.16223
Marcos V. Conde
Marcos V. Conde and Florin-Alexandru Vasluianu and Radu Timofte and Jianxing Zhang and Jia Li and Fan Wang and Xiaopeng Li and Zikun Liu and Hyunhee Park and Sejun Song and Changho Kim and Zhijuan Huang and Hongyuan Yu and Cheng Wan and Wending Xiang and Jiamin Lin and Hang Zhong and Qiaosong Zhang and Yue Sun ...
Deep RAW Image Super-Resolution. A NTIRE 2024 Challenge Survey
CVPR 2024 - NTIRE Workshop
null
null
null
cs.CV eess.IV
http://creativecommons.org/licenses/by-sa/4.0/
This paper reviews the NTIRE 2024 RAW Image Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Super-Resolution could be essential in modern Image Signal Processing (ISP) pipelines, however, this problem is not as explored as in the RGB domain. Th goal of this challenge i...
[ { "created": "Wed, 24 Apr 2024 21:51:01 GMT", "version": "v1" } ]
2024-04-26
[ [ "Conde", "Marcos V.", "" ], [ "Vasluianu", "Florin-Alexandru", "" ], [ "Timofte", "Radu", "" ], [ "Zhang", "Jianxing", "" ], [ "Li", "Jia", "" ], [ "Wang", "Fan", "" ], [ "Li", "Xiaopeng", "" ], [ "...
This paper reviews the NTIRE 2024 RAW Image Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Super-Resolution could be essential in modern Image Signal Processing (ISP) pipelines, however, this problem is not as explored as in the RGB domain. Th goal of this challenge is ...
2011.11305
Ioannis Apostolopoulos
Ioannis D. Apostolopoulos, Mpesiana Tzani
Industrial object, machine part and defect recognition towards fully automated industrial monitoring employing deep learning. The case of multilevel VGG19
17 pages, 10 figures
Journal of Ambient Intelligence and Humanized Computing, 2022
10.1007/s12652-021-03688-7
null
cs.CV eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Modern industry requires modern solutions for monitoring the automatic production of goods. Smart monitoring of the functionality of the mechanical parts of technology systems or machines is mandatory for a fully automatic production process. Although Deep Learning has been advancing, allowing for real-time object de...
[ { "created": "Mon, 23 Nov 2020 10:05:50 GMT", "version": "v1" } ]
2022-01-11
[ [ "Apostolopoulos", "Ioannis D.", "" ], [ "Tzani", "Mpesiana", "" ] ]
Modern industry requires modern solutions for monitoring the automatic production of goods. Smart monitoring of the functionality of the mechanical parts of technology systems or machines is mandatory for a fully automatic production process. Although Deep Learning has been advancing, allowing for real-time object dete...
2302.11985
Shin Hwei Tan
Hsu Myat Win, Haibo Wang, Shin Hwei Tan
Automatic Detecting Unethical Behavior in Open-source Software Projects
11 pages
null
null
null
cs.SE
http://creativecommons.org/licenses/by/4.0/
Given the rapid growth of Open-Source Software (OSS) projects, ethical considerations are becoming more important. Past studies focused on specific ethical issues (e.g., gender bias and fairness in OSS). There is little to no study on the different types of unethical behavior in OSS projects. We present the first stu...
[ { "created": "Thu, 23 Feb 2023 13:05:25 GMT", "version": "v1" } ]
2023-02-24
[ [ "Win", "Hsu Myat", "" ], [ "Wang", "Haibo", "" ], [ "Tan", "Shin Hwei", "" ] ]
Given the rapid growth of Open-Source Software (OSS) projects, ethical considerations are becoming more important. Past studies focused on specific ethical issues (e.g., gender bias and fairness in OSS). There is little to no study on the different types of unethical behavior in OSS projects. We present the first study...
2401.08903
Fengfan Zhou
Fengfan Zhou, Qianyu Zhou, Bangjie Yin, Hui Zheng, Xuequan Lu, Lizhuang Ma, Hefei Ling
Rethinking Impersonation and Dodging Attacks on Face Recognition Systems
null
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Face Recognition (FR) systems can be easily deceived by adversarial examples that manipulate benign face images through imperceptible perturbations. Adversarial attacks on FR encompass two types: impersonation (targeted) attacks and dodging (untargeted) attacks. Previous methods often achieve a successful impersonati...
[ { "created": "Wed, 17 Jan 2024 01:10:17 GMT", "version": "v1" }, { "created": "Fri, 16 Feb 2024 02:55:23 GMT", "version": "v2" }, { "created": "Thu, 25 Apr 2024 08:31:00 GMT", "version": "v3" } ]
2024-04-26
[ [ "Zhou", "Fengfan", "" ], [ "Zhou", "Qianyu", "" ], [ "Yin", "Bangjie", "" ], [ "Zheng", "Hui", "" ], [ "Lu", "Xuequan", "" ], [ "Ma", "Lizhuang", "" ], [ "Ling", "Hefei", "" ] ]
Face Recognition (FR) systems can be easily deceived by adversarial examples that manipulate benign face images through imperceptible perturbations. Adversarial attacks on FR encompass two types: impersonation (targeted) attacks and dodging (untargeted) attacks. Previous methods often achieve a successful impersonation...
2403.10293
Verena Blaschke
Verena Blaschke, Barbara Kova\v{c}i\'c, Siyao Peng, Hinrich Sch\"utze, Barbara Plank
MaiBaam: A Multi-Dialectal Bavarian Universal Dependency Treebank
LREC-COLING 2024
null
null
null
cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
Despite the success of the Universal Dependencies (UD) project exemplified by its impressive language breadth, there is still a lack in `within-language breadth': most treebanks focus on standard languages. Even for German, the language with the most annotations in UD, so far no treebank exists for one of its languag...
[ { "created": "Fri, 15 Mar 2024 13:33:10 GMT", "version": "v1" } ]
2024-03-18
[ [ "Blaschke", "Verena", "" ], [ "Kovačić", "Barbara", "" ], [ "Peng", "Siyao", "" ], [ "Schütze", "Hinrich", "" ], [ "Plank", "Barbara", "" ] ]
Despite the success of the Universal Dependencies (UD) project exemplified by its impressive language breadth, there is still a lack in `within-language breadth': most treebanks focus on standard languages. Even for German, the language with the most annotations in UD, so far no treebank exists for one of its language ...
1808.10363
Mat\'u\v{s} Sul\'ir
Mat\'u\v{s} Sul\'ir, Jaroslav Porub\"an, Ondrej Zori\v{c}\'ak
IDE-Independent Program Comprehension Tools via Source File Overwriting
null
2017 IEEE 14th International Scientific Conference on Informatics, IEEE, 2017, pp. 372-376
10.1109/INFORMATICS.2017.8327277
null
cs.SE cs.PL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Traditionally, we have two possibilities to design tools for program comprehension and analysis. The first option is to create a standalone program, independent of any source code editor. This way, the act of source code editing is separated from the act of viewing the code analysis results. The second option is to c...
[ { "created": "Thu, 30 Aug 2018 15:45:52 GMT", "version": "v1" } ]
2018-08-31
[ [ "Sulír", "Matúš", "" ], [ "Porubän", "Jaroslav", "" ], [ "Zoričák", "Ondrej", "" ] ]
Traditionally, we have two possibilities to design tools for program comprehension and analysis. The first option is to create a standalone program, independent of any source code editor. This way, the act of source code editing is separated from the act of viewing the code analysis results. The second option is to cre...
2406.15762
Zhichao Chen
Zhichao Chen, Haoxuan Li, Fangyikang Wang, Odin Zhang, Hu Xu, Xiaoyu Jiang, Zhihuan Song, Eric H. Wang
Rethinking the Diffusion Models for Numerical Tabular Data Imputation from the Perspective of Wasserstein Gradient Flow
null
null
null
null
cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
Diffusion models (DMs) have gained attention in Missing Data Imputation (MDI), but there remain two long-neglected issues to be addressed: (1). Inaccurate Imputation, which arises from inherently sample-diversification-pursuing generative process of DMs. (2). Difficult Training, which stems from intricate design requ...
[ { "created": "Sat, 22 Jun 2024 06:59:32 GMT", "version": "v1" } ]
2024-06-25
[ [ "Chen", "Zhichao", "" ], [ "Li", "Haoxuan", "" ], [ "Wang", "Fangyikang", "" ], [ "Zhang", "Odin", "" ], [ "Xu", "Hu", "" ], [ "Jiang", "Xiaoyu", "" ], [ "Song", "Zhihuan", "" ], [ "Wang", "Eric...
Diffusion models (DMs) have gained attention in Missing Data Imputation (MDI), but there remain two long-neglected issues to be addressed: (1). Inaccurate Imputation, which arises from inherently sample-diversification-pursuing generative process of DMs. (2). Difficult Training, which stems from intricate design requir...
2309.04878
Ekzhin Ear
Ekzhin Ear, Jose L. C. Remy, Antonia Feffer, Shouhuai Xu
Characterizing Cyber Attacks against Space Systems with Missing Data: Framework and Case Study
Accepted for publication: IEEE International Conference on Communications and Network Security 2023 (IEEE CNS)
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cybersecurity of space systems is an emerging topic, but there is no single dataset that documents cyber attacks against space systems that have occurred in the past. These incidents are often scattered in media reports while missing many details, which we dub the missing-data problem. Nevertheless, even "low-quality...
[ { "created": "Sat, 9 Sep 2023 21:40:00 GMT", "version": "v1" } ]
2023-09-12
[ [ "Ear", "Ekzhin", "" ], [ "Remy", "Jose L. C.", "" ], [ "Feffer", "Antonia", "" ], [ "Xu", "Shouhuai", "" ] ]
Cybersecurity of space systems is an emerging topic, but there is no single dataset that documents cyber attacks against space systems that have occurred in the past. These incidents are often scattered in media reports while missing many details, which we dub the missing-data problem. Nevertheless, even "low-quality" ...
2305.09204
Yifan Jiang
Yifan Jiang, Shane Steinert-Threlkeld
The Weighted M\"obius Score: A Unified Framework for Feature Attribution
null
null
null
null
cs.LG cs.AI cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Feature attribution aims to explain the reasoning behind a black-box model's prediction by identifying the impact of each feature on the prediction. Recent work has extended feature attribution to interactions between multiple features. However, the lack of a unified framework has led to a proliferation of methods th...
[ { "created": "Tue, 16 May 2023 06:27:27 GMT", "version": "v1" } ]
2023-05-17
[ [ "Jiang", "Yifan", "" ], [ "Steinert-Threlkeld", "Shane", "" ] ]
Feature attribution aims to explain the reasoning behind a black-box model's prediction by identifying the impact of each feature on the prediction. Recent work has extended feature attribution to interactions between multiple features. However, the lack of a unified framework has led to a proliferation of methods that...
2005.10848
Surin Ahn
Surin Ahn, Ayfer Ozgur and Mert Pilanci
Global Multiclass Classification and Dataset Construction via Heterogeneous Local Experts
27 pages, 8 figures, to be published in IEEE Journal on Selected Areas in Information Theory (JSAIT) - Special Issue on Estimation and Inference
null
10.1109/JSAIT.2020.3041804
null
cs.LG cs.IT math.IT stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the domains of dataset construction and crowdsourcing, a notable challenge is to aggregate labels from a heterogeneous set of labelers, each of whom is potentially an expert in some subset of tasks (and less reliable in others). To reduce costs of hiring human labelers or training automated labeling systems, it is...
[ { "created": "Thu, 21 May 2020 18:07:42 GMT", "version": "v1" }, { "created": "Mon, 25 May 2020 04:34:43 GMT", "version": "v2" }, { "created": "Tue, 5 Jan 2021 23:34:36 GMT", "version": "v3" } ]
2021-01-07
[ [ "Ahn", "Surin", "" ], [ "Ozgur", "Ayfer", "" ], [ "Pilanci", "Mert", "" ] ]
In the domains of dataset construction and crowdsourcing, a notable challenge is to aggregate labels from a heterogeneous set of labelers, each of whom is potentially an expert in some subset of tasks (and less reliable in others). To reduce costs of hiring human labelers or training automated labeling systems, it is o...
2107.12407
Shannon Veitch
Thomas Humphries, Rasoul Akhavan Mahdavi, Shannon Veitch, Florian Kerschbaum
Selective MPC: Distributed Computation of Differentially Private Key-Value Statistics
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Key-value data is a naturally occurring data type that has not been thoroughly investigated in the local trust model. Existing local differentially private (LDP) solutions for computing statistics over key-value data suffer from the inherent accuracy limitations of each user adding their own noise. Multi-party comput...
[ { "created": "Mon, 26 Jul 2021 18:01:19 GMT", "version": "v1" }, { "created": "Tue, 30 Aug 2022 15:18:44 GMT", "version": "v2" } ]
2022-08-31
[ [ "Humphries", "Thomas", "" ], [ "Mahdavi", "Rasoul Akhavan", "" ], [ "Veitch", "Shannon", "" ], [ "Kerschbaum", "Florian", "" ] ]
Key-value data is a naturally occurring data type that has not been thoroughly investigated in the local trust model. Existing local differentially private (LDP) solutions for computing statistics over key-value data suffer from the inherent accuracy limitations of each user adding their own noise. Multi-party computat...
1209.3353
Shipra Agrawal
Shipra Agrawal, Navin Goyal
Further Optimal Regret Bounds for Thompson Sampling
arXiv admin note: substantial text overlap with arXiv:1111.1797
null
null
null
cs.LG cs.DS stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Thompson Sampling is one of the oldest heuristics for multi-armed bandit problems. It is a randomized algorithm based on Bayesian ideas, and has recently generated significant interest after several studies demonstrated it to have better empirical performance compared to the state of the art methods. In this paper, w...
[ { "created": "Sat, 15 Sep 2012 03:41:18 GMT", "version": "v1" } ]
2012-09-18
[ [ "Agrawal", "Shipra", "" ], [ "Goyal", "Navin", "" ] ]
Thompson Sampling is one of the oldest heuristics for multi-armed bandit problems. It is a randomized algorithm based on Bayesian ideas, and has recently generated significant interest after several studies demonstrated it to have better empirical performance compared to the state of the art methods. In this paper, we ...
2406.11159
Siyuan Yu
Siyuan Yu, Wei Chen, H. Vincent Poor
Distributed Stochastic Gradient Descent with Staleness: A Stochastic Delay Differential Equation Based Framework
13 pages, 9 figures
null
null
null
cs.LG cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Distributed stochastic gradient descent (SGD) has attracted considerable recent attention due to its potential for scaling computational resources, reducing training time, and helping protect user privacy in machine learning. However, the staggers and limited bandwidth may induce random computational/communication de...
[ { "created": "Mon, 17 Jun 2024 02:56:55 GMT", "version": "v1" } ]
2024-06-18
[ [ "Yu", "Siyuan", "" ], [ "Chen", "Wei", "" ], [ "Poor", "H. Vincent", "" ] ]
Distributed stochastic gradient descent (SGD) has attracted considerable recent attention due to its potential for scaling computational resources, reducing training time, and helping protect user privacy in machine learning. However, the staggers and limited bandwidth may induce random computational/communication dela...
1908.05293
Rahul Mitra
Rahul Mitra, Nitesh B. Gundavarapu, Abhishek Sharma, Arjun Jain
Multiview-Consistent Semi-Supervised Learning for 3D Human Pose Estimation
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
The best performing methods for 3D human pose estimation from monocular images require large amounts of in-the-wild 2D and controlled 3D pose annotated datasets which are costly and require sophisticated systems to acquire. To reduce this annotation dependency, we propose Multiview-Consistent Semi Supervised Learning...
[ { "created": "Wed, 14 Aug 2019 18:13:57 GMT", "version": "v1" }, { "created": "Sat, 30 Nov 2019 06:44:56 GMT", "version": "v2" }, { "created": "Tue, 25 Feb 2020 06:14:42 GMT", "version": "v3" } ]
2020-02-26
[ [ "Mitra", "Rahul", "" ], [ "Gundavarapu", "Nitesh B.", "" ], [ "Sharma", "Abhishek", "" ], [ "Jain", "Arjun", "" ] ]
The best performing methods for 3D human pose estimation from monocular images require large amounts of in-the-wild 2D and controlled 3D pose annotated datasets which are costly and require sophisticated systems to acquire. To reduce this annotation dependency, we propose Multiview-Consistent Semi Supervised Learning (...
1804.07376
Ashkan Yousefpour
Ashkan Yousefpour, Genya Ishigaki, Riti Gour, Jason P. Jue
On Reducing IoT Service Delay via Fog Offloading
null
IEEE Internet of Things Journal, vol. 5, no. 2, pp. 998-1010, April 2018
10.1109/JIOT.2017.2788802
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the Internet of Things (IoT) becoming a major component of our daily life, understanding how to improve the quality of service (QoS) for IoT applications through fog computing is becoming an important problem. In this paper, we introduce a general framework for IoT-fog-cloud applications, and propose a delay-min...
[ { "created": "Thu, 19 Apr 2018 20:58:04 GMT", "version": "v1" } ]
2018-04-23
[ [ "Yousefpour", "Ashkan", "" ], [ "Ishigaki", "Genya", "" ], [ "Gour", "Riti", "" ], [ "Jue", "Jason P.", "" ] ]
With the Internet of Things (IoT) becoming a major component of our daily life, understanding how to improve the quality of service (QoS) for IoT applications through fog computing is becoming an important problem. In this paper, we introduce a general framework for IoT-fog-cloud applications, and propose a delay-minim...
1911.00238
Takato Horii
Kyoichiro Kobayashi, Takato Horii, Ryo Iwaki, Yukie Nagai and Minoru Asada
Situated GAIL: Multitask imitation using task-conditioned adversarial inverse reinforcement learning
Submitted to Advanced Robotics
null
null
null
cs.LG cs.AI cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Generative adversarial imitation learning (GAIL) has attracted increasing attention in the field of robot learning. It enables robots to learn a policy to achieve a task demonstrated by an expert while simultaneously estimating the reward function behind the expert's behaviors. However, this framework is limited to l...
[ { "created": "Fri, 1 Nov 2019 07:50:30 GMT", "version": "v1" } ]
2019-11-04
[ [ "Kobayashi", "Kyoichiro", "" ], [ "Horii", "Takato", "" ], [ "Iwaki", "Ryo", "" ], [ "Nagai", "Yukie", "" ], [ "Asada", "Minoru", "" ] ]
Generative adversarial imitation learning (GAIL) has attracted increasing attention in the field of robot learning. It enables robots to learn a policy to achieve a task demonstrated by an expert while simultaneously estimating the reward function behind the expert's behaviors. However, this framework is limited to lea...
1408.1292
Ilja Kuzborskij
Ilja Kuzborskij, Francesco Orabona, Barbara Caputo
Scalable Greedy Algorithms for Transfer Learning
null
null
10.1016/j.cviu.2016.09.003
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we consider the binary transfer learning problem, focusing on how to select and combine sources from a large pool to yield a good performance on a target task. Constraining our scenario to real world, we do not assume the direct access to the source data, but rather we employ the source hypotheses train...
[ { "created": "Wed, 6 Aug 2014 14:27:57 GMT", "version": "v1" }, { "created": "Thu, 4 Dec 2014 15:56:53 GMT", "version": "v2" }, { "created": "Thu, 8 Oct 2015 10:27:39 GMT", "version": "v3" }, { "created": "Sat, 18 Jun 2016 00:17:50 GMT", "version": "v4" } ]
2016-09-16
[ [ "Kuzborskij", "Ilja", "" ], [ "Orabona", "Francesco", "" ], [ "Caputo", "Barbara", "" ] ]
In this paper we consider the binary transfer learning problem, focusing on how to select and combine sources from a large pool to yield a good performance on a target task. Constraining our scenario to real world, we do not assume the direct access to the source data, but rather we employ the source hypotheses trained...
1308.1464
Andy Terrel
Andy R. Terrel and Kyle T. Mandli
ManyClaw: Slicing and dicing Riemann solvers for next generation highly parallel architectures
TACC-Intel Symposium on Highly Parallel Architectures. 2012
null
null
null
cs.CE cs.MS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Next generation computer architectures will include order of magnitude more intra-node parallelism; however, many application programmers have a difficult time keeping their codes current with the state-of-the-art machines. In this context, we analyze Hyperbolic PDE solvers, which are used in the solution of many imp...
[ { "created": "Wed, 7 Aug 2013 02:24:20 GMT", "version": "v1" } ]
2013-08-08
[ [ "Terrel", "Andy R.", "" ], [ "Mandli", "Kyle T.", "" ] ]
Next generation computer architectures will include order of magnitude more intra-node parallelism; however, many application programmers have a difficult time keeping their codes current with the state-of-the-art machines. In this context, we analyze Hyperbolic PDE solvers, which are used in the solution of many impor...
1411.0154
Ferruccio Guidi Dr
Ferruccio Guidi
Extending the Applicability Condition in the Formal System $\lambda\delta$
36 pages, updated to appear as a technical report
null
null
AMS-Acta 4411
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The formal system $\lambda\delta$ is a typed lambda calculus derived from $\Lambda_\infty$, aiming to support the foundations of Mathematics that require an underlying theory of expressions (for example the Minimal Type Theory). The system is developed in the context of the Hypertextual Electronic Library of Mathemat...
[ { "created": "Sat, 1 Nov 2014 18:58:40 GMT", "version": "v1" }, { "created": "Fri, 6 Mar 2015 14:49:56 GMT", "version": "v2" }, { "created": "Wed, 27 Nov 2019 22:41:24 GMT", "version": "v3" } ]
2019-12-02
[ [ "Guidi", "Ferruccio", "" ] ]
The formal system $\lambda\delta$ is a typed lambda calculus derived from $\Lambda_\infty$, aiming to support the foundations of Mathematics that require an underlying theory of expressions (for example the Minimal Type Theory). The system is developed in the context of the Hypertextual Electronic Library of Mathematic...
2205.00893
Emmanuel Kwarteng
Emmanuel Kwarteng (PhD Candidate), Dr. Mumin Cebe
A Survey on Security Issues in Modern Implantable Devices: Solutions and Future Issues
There are 18 pages including reference pages, 5 figures, and 4 tables submitted to Smart Health by Elsevier. Emmanuel Kwarteng: Conceptualization, Investigation, Resources, Methodology, Writing-Original Draft, Visualization. Mumin Cebe: Writing-Review & Editing, Validation, Supervision
null
null
null
cs.CR
http://creativecommons.org/licenses/by-nc-nd/4.0/
Implantable Medical Devices (IMD) is a fast pace growing medical field and continues to grow in the foreseeable future. Advancement in science and technology has led to the IMD devices offering advanced medical treatments. Modern IMDs can automatically monitor and manage different patients' health conditions without ...
[ { "created": "Mon, 2 May 2022 13:03:41 GMT", "version": "v1" } ]
2022-05-03
[ [ "Kwarteng", "Emmanuel", "", "PhD Candidate" ], [ "Cebe", "Dr. Mumin", "" ] ]
Implantable Medical Devices (IMD) is a fast pace growing medical field and continues to grow in the foreseeable future. Advancement in science and technology has led to the IMD devices offering advanced medical treatments. Modern IMDs can automatically monitor and manage different patients' health conditions without an...
2302.01714
Muah Kim
Muah Kim, Rick Fritschek, Rafael F. Schaefer
Learning End-to-End Channel Coding with Diffusion Models
6 pages, WSA/SCC 2023
null
null
null
cs.IT cs.LG math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
It is a known problem that deep-learning-based end-to-end (E2E) channel coding systems depend on a known and differentiable channel model, due to the learning process and based on the gradient-descent optimization methods. This places the challenge to approximate or generate the channel or its derivative from samples...
[ { "created": "Fri, 3 Feb 2023 13:11:57 GMT", "version": "v1" }, { "created": "Wed, 29 Nov 2023 14:54:04 GMT", "version": "v2" } ]
2023-11-30
[ [ "Kim", "Muah", "" ], [ "Fritschek", "Rick", "" ], [ "Schaefer", "Rafael F.", "" ] ]
It is a known problem that deep-learning-based end-to-end (E2E) channel coding systems depend on a known and differentiable channel model, due to the learning process and based on the gradient-descent optimization methods. This places the challenge to approximate or generate the channel or its derivative from samples g...
2107.13423
Guangliang Pan
Guangliang Pan, Zitong Liu, Wei Wang, Minglei Li
A Signal Detection Scheme Based on Deep Learning in OFDM Systems
null
null
null
null
cs.IT cs.LG eess.SP math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Channel estimation and signal detection are essential steps to ensure the quality of end-to-end communication in orthogonal frequency-division multiplexing (OFDM) systems. In this paper, we develop a DDLSD approach, i.e., Data-driven Deep Learning for Signal Detection in OFDM systems. First, the OFDM system model is ...
[ { "created": "Sat, 24 Jul 2021 04:25:46 GMT", "version": "v1" } ]
2021-07-29
[ [ "Pan", "Guangliang", "" ], [ "Liu", "Zitong", "" ], [ "Wang", "Wei", "" ], [ "Li", "Minglei", "" ] ]
Channel estimation and signal detection are essential steps to ensure the quality of end-to-end communication in orthogonal frequency-division multiplexing (OFDM) systems. In this paper, we develop a DDLSD approach, i.e., Data-driven Deep Learning for Signal Detection in OFDM systems. First, the OFDM system model is es...
2406.06045
Ke Niu
Ke Niu, Haiyang Yu, Xuelin Qian, Teng Fu, Bin Li, and Xiangyang Xue
Synthesizing Efficient Data with Diffusion Models for Person Re-Identification Pre-Training
null
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Existing person re-identification (Re-ID) methods principally deploy the ImageNet-1K dataset for model initialization, which inevitably results in sub-optimal situations due to the large domain gap. One of the key challenges is that building large-scale person Re-ID datasets is time-consuming. Some previous efforts a...
[ { "created": "Mon, 10 Jun 2024 06:26:03 GMT", "version": "v1" } ]
2024-06-11
[ [ "Niu", "Ke", "" ], [ "Yu", "Haiyang", "" ], [ "Qian", "Xuelin", "" ], [ "Fu", "Teng", "" ], [ "Li", "Bin", "" ], [ "Xue", "Xiangyang", "" ] ]
Existing person re-identification (Re-ID) methods principally deploy the ImageNet-1K dataset for model initialization, which inevitably results in sub-optimal situations due to the large domain gap. One of the key challenges is that building large-scale person Re-ID datasets is time-consuming. Some previous efforts add...
2307.10751
Advait Sarkar
Advait Sarkar
Exploring Perspectives on the Impact of Artificial Intelligence on the Creativity of Knowledge Work: Beyond Mechanised Plagiarism and Stochastic Parrots
Advait Sarkar. 2023. Exploring Perspectives on the Impact of Artificial Intelligence on the Creativity of Knowledge Work Beyond Mechanised Plagiarism and Stochastic Parrots. In Annual Symposium on Human-Computer Interaction for Work 2023 (CHIWORK 2023), June 13-16, 2023, Oldenburg, Germany. ACM, New York, NY, U...
null
10.1145/3596671.3597650
null
cs.HC cs.AI cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Artificial Intelligence (AI), and in particular generative models, are transformative tools for knowledge work. They problematise notions of creativity, originality, plagiarism, the attribution of credit, and copyright ownership. Critics of generative models emphasise the reliance on large amounts of training data, a...
[ { "created": "Thu, 20 Jul 2023 10:26:57 GMT", "version": "v1" } ]
2023-07-21
[ [ "Sarkar", "Advait", "" ] ]
Artificial Intelligence (AI), and in particular generative models, are transformative tools for knowledge work. They problematise notions of creativity, originality, plagiarism, the attribution of credit, and copyright ownership. Critics of generative models emphasise the reliance on large amounts of training data, and...
cs/0402009
Richard McClatchey
F Estrella, C del Frate, T Hauer, R McClatchey, M Odeh, D Rogulin, S R Amendolia, D Schottlander, T Solomonides, R Warren
Resolving Clinicians Queries Across a Grids Infrastructure
8 pages, 3 figures. Presented at the 2nd Int Conf on HealthGrids Clermont-Ferrand, France January 2004 and accepted by Methods of Information in Medicine
null
null
null
cs.DB cs.SE
null
The past decade has witnessed order of magnitude increases in computing power, data storage capacity and network speed, giving birth to applications which may handle large data volumes of increased complexity, distributed over the Internet. Grids computing promises to resolve many of the difficulties in facilitating ...
[ { "created": "Tue, 3 Feb 2004 14:32:39 GMT", "version": "v1" } ]
2007-05-23
[ [ "Estrella", "F", "" ], [ "del Frate", "C", "" ], [ "Hauer", "T", "" ], [ "McClatchey", "R", "" ], [ "Odeh", "M", "" ], [ "Rogulin", "D", "" ], [ "Amendolia", "S R", "" ], [ "Schottlander", "D", ...
The past decade has witnessed order of magnitude increases in computing power, data storage capacity and network speed, giving birth to applications which may handle large data volumes of increased complexity, distributed over the Internet. Grids computing promises to resolve many of the difficulties in facilitating me...
2305.04239
Zhitao Liu
Zhitao Liu, Zengyu Liu, Jiwei Wei, Guan Wang, Zhenjiang Du, Ning Xie, Heng Tao Shen
Instance-Variant Loss with Gaussian RBF Kernel for 3D Cross-modal Retriveal
null
null
null
null
cs.CV cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
3D cross-modal retrieval is gaining attention in the multimedia community. Central to this topic is learning a joint embedding space to represent data from different modalities, such as images, 3D point clouds, and polygon meshes, to extract modality-invariant and discriminative features. Hence, the performance of cr...
[ { "created": "Sun, 7 May 2023 10:12:14 GMT", "version": "v1" } ]
2023-05-09
[ [ "Liu", "Zhitao", "" ], [ "Liu", "Zengyu", "" ], [ "Wei", "Jiwei", "" ], [ "Wang", "Guan", "" ], [ "Du", "Zhenjiang", "" ], [ "Xie", "Ning", "" ], [ "Shen", "Heng Tao", "" ] ]
3D cross-modal retrieval is gaining attention in the multimedia community. Central to this topic is learning a joint embedding space to represent data from different modalities, such as images, 3D point clouds, and polygon meshes, to extract modality-invariant and discriminative features. Hence, the performance of cros...
2010.01150
Xiang Dai
Xiang Dai and Sarvnaz Karimi and Ben Hachey and Cecile Paris
Cost-effective Selection of Pretraining Data: A Case Study of Pretraining BERT on Social Media
Findings of EMNLP 2020
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Recent studies on domain-specific BERT models show that effectiveness on downstream tasks can be improved when models are pretrained on in-domain data. Often, the pretraining data used in these models are selected based on their subject matter, e.g., biology or computer science. Given the range of applications using ...
[ { "created": "Fri, 2 Oct 2020 18:06:31 GMT", "version": "v1" } ]
2020-10-06
[ [ "Dai", "Xiang", "" ], [ "Karimi", "Sarvnaz", "" ], [ "Hachey", "Ben", "" ], [ "Paris", "Cecile", "" ] ]
Recent studies on domain-specific BERT models show that effectiveness on downstream tasks can be improved when models are pretrained on in-domain data. Often, the pretraining data used in these models are selected based on their subject matter, e.g., biology or computer science. Given the range of applications using so...
2405.18042
Youngwan Lee
Youngwan Lee, Jeffrey Ryan Willette, Jonghee Kim, Sung Ju Hwang
Visualizing the loss landscape of Self-supervised Vision Transformer
NeurIPS 2023 Workshop: Self-Supervised Learning - Theory and Practice
null
null
null
cs.CV cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
The Masked autoencoder (MAE) has drawn attention as a representative self-supervised approach for masked image modeling with vision transformers. However, even though MAE shows better generalization capability than fully supervised training from scratch, the reason why has not been explored. In another line of work, ...
[ { "created": "Tue, 28 May 2024 10:54:26 GMT", "version": "v1" } ]
2024-05-29
[ [ "Lee", "Youngwan", "" ], [ "Willette", "Jeffrey Ryan", "" ], [ "Kim", "Jonghee", "" ], [ "Hwang", "Sung Ju", "" ] ]
The Masked autoencoder (MAE) has drawn attention as a representative self-supervised approach for masked image modeling with vision transformers. However, even though MAE shows better generalization capability than fully supervised training from scratch, the reason why has not been explored. In another line of work, th...
1906.04279
Zhizhou Ren
Zhizhou Ren, Kefan Dong, Yuan Zhou, Qiang Liu, Jian Peng
Exploration via Hindsight Goal Generation
Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019)
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Goal-oriented reinforcement learning has recently been a practical framework for robotic manipulation tasks, in which an agent is required to reach a certain goal defined by a function on the state space. However, the sparsity of such reward definition makes traditional reinforcement learning algorithms very ineffici...
[ { "created": "Mon, 10 Jun 2019 21:21:18 GMT", "version": "v1" }, { "created": "Thu, 5 Dec 2019 05:35:33 GMT", "version": "v2" }, { "created": "Wed, 18 Dec 2019 04:31:39 GMT", "version": "v3" } ]
2019-12-19
[ [ "Ren", "Zhizhou", "" ], [ "Dong", "Kefan", "" ], [ "Zhou", "Yuan", "" ], [ "Liu", "Qiang", "" ], [ "Peng", "Jian", "" ] ]
Goal-oriented reinforcement learning has recently been a practical framework for robotic manipulation tasks, in which an agent is required to reach a certain goal defined by a function on the state space. However, the sparsity of such reward definition makes traditional reinforcement learning algorithms very inefficien...
2112.13099
Amir Shaikhha
Amir Shaikhha, Marios Kelepeshis, Mahdi Ghorbani
Fine-Tuning Data Structures for Analytical Query Processing
null
null
null
null
cs.DB cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce a framework for automatically choosing data structures to support efficient computation of analytical workloads. Our contributions are twofold. First, we introduce a novel low-level intermediate language that can express the algorithms behind various query processing paradigms such as classical joins, gr...
[ { "created": "Fri, 24 Dec 2021 16:36:35 GMT", "version": "v1" } ]
2021-12-28
[ [ "Shaikhha", "Amir", "" ], [ "Kelepeshis", "Marios", "" ], [ "Ghorbani", "Mahdi", "" ] ]
We introduce a framework for automatically choosing data structures to support efficient computation of analytical workloads. Our contributions are twofold. First, we introduce a novel low-level intermediate language that can express the algorithms behind various query processing paradigms such as classical joins, grou...
1503.05992
Sugata Sanyal
Subhamoy Chakraborti, D. P. Acharjya, Sugata Sanyal
Application Security framework for Mobile App Development in Enterprise setup
7 pages
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Enterprise Mobility has been increasing the reach over the years. Initially Mobile devices were adopted as consumer devices. However, the enterprises world over have rightly taken the leap and started using the ubiquitous technology for managing its employees as well as to reach out to the customers. While the Mobile...
[ { "created": "Fri, 20 Mar 2015 04:55:50 GMT", "version": "v1" } ]
2015-03-23
[ [ "Chakraborti", "Subhamoy", "" ], [ "Acharjya", "D. P.", "" ], [ "Sanyal", "Sugata", "" ] ]
Enterprise Mobility has been increasing the reach over the years. Initially Mobile devices were adopted as consumer devices. However, the enterprises world over have rightly taken the leap and started using the ubiquitous technology for managing its employees as well as to reach out to the customers. While the Mobile e...
2209.07000
Shikhar Singh
Shikhar Singh, Ehsan Qasemi, Muhao Chen
VIPHY: Probing "Visible" Physical Commonsense Knowledge
In Progress (under review)
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
In recent years, vision-language models (VLMs) have shown remarkable performance on visual reasoning tasks (e.g. attributes, location). While such tasks measure the requisite knowledge to ground and reason over a given visual instance, they do not, however, measure the ability of VLMs to retain and generalize such kn...
[ { "created": "Thu, 15 Sep 2022 02:06:25 GMT", "version": "v1" } ]
2022-09-16
[ [ "Singh", "Shikhar", "" ], [ "Qasemi", "Ehsan", "" ], [ "Chen", "Muhao", "" ] ]
In recent years, vision-language models (VLMs) have shown remarkable performance on visual reasoning tasks (e.g. attributes, location). While such tasks measure the requisite knowledge to ground and reason over a given visual instance, they do not, however, measure the ability of VLMs to retain and generalize such know...
2308.10962
Adrian Boedtker Ghansah
Adrian B. Ghansah, Jeeseop Kim, Maegan Tucker, Aaron D. Ames
Humanoid Robot Co-Design: Coupling Hardware Design with Gait Generation via Hybrid Zero Dynamics
7 pages, 6 figures, accepted to CDC 2023
null
null
null
cs.RO math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Selecting robot design parameters can be challenging since these parameters are often coupled with the performance of the controller and, therefore, the resulting capabilities of the robot. This leads to a time-consuming and often expensive process whereby one iterates between designing the robot and manually evaluat...
[ { "created": "Mon, 21 Aug 2023 18:15:47 GMT", "version": "v1" } ]
2023-08-23
[ [ "Ghansah", "Adrian B.", "" ], [ "Kim", "Jeeseop", "" ], [ "Tucker", "Maegan", "" ], [ "Ames", "Aaron D.", "" ] ]
Selecting robot design parameters can be challenging since these parameters are often coupled with the performance of the controller and, therefore, the resulting capabilities of the robot. This leads to a time-consuming and often expensive process whereby one iterates between designing the robot and manually evaluatin...
1911.01156
Alun Preece
Frank Stein, Alun Preece
AAAI FSS-19: Artificial Intelligence in Government and Public Sector Proceedings
Post-symposium proceedings including 18 papers
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Proceedings of the AAAI Fall Symposium on Artificial Intelligence in Government and Public Sector, Arlington, Virginia, USA, November 7-8, 2019
[ { "created": "Mon, 4 Nov 2019 12:26:51 GMT", "version": "v1" }, { "created": "Thu, 28 Nov 2019 08:07:11 GMT", "version": "v2" } ]
2019-12-02
[ [ "Stein", "Frank", "" ], [ "Preece", "Alun", "" ] ]
Proceedings of the AAAI Fall Symposium on Artificial Intelligence in Government and Public Sector, Arlington, Virginia, USA, November 7-8, 2019
1107.3245
Piotr Frackiewicz
Piotr Frackiewicz
Quantum information approach to normal representation of extensive games
null
null
null
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We modify the concept of quantum strategic game to make it useful for extensive form games. We prove that our modification allows to consider the normal representation of any finite extensive game using the fundamental concepts of quantum information. The Selten's Horse game and the general form of two-stage extensiv...
[ { "created": "Sat, 16 Jul 2011 18:42:17 GMT", "version": "v1" }, { "created": "Tue, 19 Jul 2011 05:59:25 GMT", "version": "v2" } ]
2011-07-20
[ [ "Frackiewicz", "Piotr", "" ] ]
We modify the concept of quantum strategic game to make it useful for extensive form games. We prove that our modification allows to consider the normal representation of any finite extensive game using the fundamental concepts of quantum information. The Selten's Horse game and the general form of two-stage extensive ...
2008.07956
Farhan Khawar
Farhan Khawar, Leonard Kin Man Poon, Nevin Lianwen Zhang
Learning the Structure of Auto-Encoding Recommenders
Proceedings of The Web Conference 2020
null
10.1145/3366423.3380135
null
cs.IR cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Autoencoder recommenders have recently shown state-of-the-art performance in the recommendation task due to their ability to model non-linear item relationships effectively. However, existing autoencoder recommenders use fully-connected neural network layers and do not employ structure learning. This can lead to inef...
[ { "created": "Tue, 18 Aug 2020 14:37:40 GMT", "version": "v1" } ]
2020-08-19
[ [ "Khawar", "Farhan", "" ], [ "Poon", "Leonard Kin Man", "" ], [ "Zhang", "Nevin Lianwen", "" ] ]
Autoencoder recommenders have recently shown state-of-the-art performance in the recommendation task due to their ability to model non-linear item relationships effectively. However, existing autoencoder recommenders use fully-connected neural network layers and do not employ structure learning. This can lead to ineffi...
2210.07312
Md Masudur Rahman
Md Masudur Rahman, Yexiang Xue
Bootstrap Advantage Estimation for Policy Optimization in Reinforcement Learning
Accepted at IEEE ICMLA 2022
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes an advantage estimation approach based on data augmentation for policy optimization. Unlike using data augmentation on the input to learn value and policy function as existing methods use, our method uses data augmentation to compute a bootstrap advantage estimation. This Bootstrap Advantage Estim...
[ { "created": "Thu, 13 Oct 2022 19:30:43 GMT", "version": "v1" } ]
2022-10-17
[ [ "Rahman", "Md Masudur", "" ], [ "Xue", "Yexiang", "" ] ]
This paper proposes an advantage estimation approach based on data augmentation for policy optimization. Unlike using data augmentation on the input to learn value and policy function as existing methods use, our method uses data augmentation to compute a bootstrap advantage estimation. This Bootstrap Advantage Estimat...
2211.05184
Zishan Gu
Zishan Gu, Jintang Li and Liang Chen
Are All Edges Necessary? A Unified Framework for Graph Purification
null
null
null
null
cs.SI cs.LG
http://creativecommons.org/licenses/by/4.0/
Graph Neural Networks (GNNs) as deep learning models working on graph-structure data have achieved advanced performance in many works. However, it has been proved repeatedly that, not all edges in a graph are necessary for the training of machine learning models. In other words, some of the connections between nodes ...
[ { "created": "Wed, 9 Nov 2022 20:28:25 GMT", "version": "v1" } ]
2022-11-11
[ [ "Gu", "Zishan", "" ], [ "Li", "Jintang", "" ], [ "Chen", "Liang", "" ] ]
Graph Neural Networks (GNNs) as deep learning models working on graph-structure data have achieved advanced performance in many works. However, it has been proved repeatedly that, not all edges in a graph are necessary for the training of machine learning models. In other words, some of the connections between nodes ma...
0809.3352
Steffen Kuehn
Steffen Kuehn
Generalized Prediction Intervals for Arbitrary Distributed High-Dimensional Data
13 pages, 3 figures
null
null
null
cs.CV cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper generalizes the traditional statistical concept of prediction intervals for arbitrary probability density functions in high-dimensional feature spaces by introducing significance level distributions, which provides interval-independent probabilities for continuous random variables. The advantage of the tra...
[ { "created": "Fri, 19 Sep 2008 11:02:39 GMT", "version": "v1" } ]
2008-09-22
[ [ "Kuehn", "Steffen", "" ] ]
This paper generalizes the traditional statistical concept of prediction intervals for arbitrary probability density functions in high-dimensional feature spaces by introducing significance level distributions, which provides interval-independent probabilities for continuous random variables. The advantage of the trans...
1809.09912
Maarten Vanhoof
Maarten Vanhoof, Thomas Ploetz, Zbigniew Smoreda
Geographical veracity of indicators derived from mobile phone data
4 pages, 3 figures, 2 tables. Short paper contributed to the Netmob 2017 conference in Milan
null
null
null
cs.CY
http://creativecommons.org/licenses/by-nc-sa/4.0/
In this contribution we summarize insights on the geographical veracity of using mobile phone data to create (statistical) indicators. We focus on problems that persist with spatial allocation, spatial delineation and spatial aggregation of information obtained from mobile phone data. For each of the cases, we offer ...
[ { "created": "Wed, 26 Sep 2018 11:24:37 GMT", "version": "v1" } ]
2018-09-27
[ [ "Vanhoof", "Maarten", "" ], [ "Ploetz", "Thomas", "" ], [ "Smoreda", "Zbigniew", "" ] ]
In this contribution we summarize insights on the geographical veracity of using mobile phone data to create (statistical) indicators. We focus on problems that persist with spatial allocation, spatial delineation and spatial aggregation of information obtained from mobile phone data. For each of the cases, we offer in...
2305.06361
Chenguang Wang
Chenguang Wang, Tianshu Yu
Efficient Training of Multi-task Combinarotial Neural Solver with Multi-armed Bandits
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Efficiently training a multi-task neural solver for various combinatorial optimization problems (COPs) has been less studied so far. In this paper, we propose a general and efficient training paradigm based on multi-armed bandits to deliver a unified combinarotial multi-task neural solver. To this end, we resort to t...
[ { "created": "Wed, 10 May 2023 14:20:34 GMT", "version": "v1" }, { "created": "Mon, 9 Oct 2023 06:35:46 GMT", "version": "v2" } ]
2023-10-10
[ [ "Wang", "Chenguang", "" ], [ "Yu", "Tianshu", "" ] ]
Efficiently training a multi-task neural solver for various combinatorial optimization problems (COPs) has been less studied so far. In this paper, we propose a general and efficient training paradigm based on multi-armed bandits to deliver a unified combinarotial multi-task neural solver. To this end, we resort to the...
2403.16898
Jialun Cao
Jialun Cao and Wuqi Zhang and Shing-Chi Cheung
Concerned with Data Contamination? Assessing Countermeasures in Code Language Model
Adjust the format so that the layout looks better
null
null
null
cs.SE cs.CR
http://creativecommons.org/licenses/by/4.0/
Various techniques have been proposed to leverage the capabilities of code language models (CLMs) for SE tasks. While these techniques typically evaluate their effectiveness using publicly available datasets, the evaluation can be subject to data contamination threats where the evaluation datasets have already been u...
[ { "created": "Mon, 25 Mar 2024 16:10:25 GMT", "version": "v1" }, { "created": "Thu, 28 Mar 2024 05:00:47 GMT", "version": "v2" } ]
2024-03-29
[ [ "Cao", "Jialun", "" ], [ "Zhang", "Wuqi", "" ], [ "Cheung", "Shing-Chi", "" ] ]
Various techniques have been proposed to leverage the capabilities of code language models (CLMs) for SE tasks. While these techniques typically evaluate their effectiveness using publicly available datasets, the evaluation can be subject to data contamination threats where the evaluation datasets have already been use...
2106.03412
Silvia-Laura Pintea
Silvia L.Pintea and Nergis Tomen and Stanley F. Goes and Marco Loog and Jan C. van Gemert
Resolution learning in deep convolutional networks using scale-space theory
Preprint accepted by IEEE Transactions on Image Processing, 2021 (TIP). Link to final published article: https://ieeexplore.ieee.org/abstract/document/9552550
IEEE Transactions on Image Processing, vol. 30, pp. 8342-8353, 2021
10.1109/TIP.2021.3115001
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Resolution in deep convolutional neural networks (CNNs) is typically bounded by the receptive field size through filter sizes, and subsampling layers or strided convolutions on feature maps. The optimal resolution may vary significantly depending on the dataset. Modern CNNs hard-code their resolution hyper-parameters...
[ { "created": "Mon, 7 Jun 2021 08:23:02 GMT", "version": "v1" }, { "created": "Wed, 30 Jun 2021 14:08:16 GMT", "version": "v2" }, { "created": "Tue, 24 Oct 2023 14:22:39 GMT", "version": "v3" } ]
2023-10-25
[ [ "Pintea", "Silvia L.", "" ], [ "Tomen", "Nergis", "" ], [ "Goes", "Stanley F.", "" ], [ "Loog", "Marco", "" ], [ "van Gemert", "Jan C.", "" ] ]
Resolution in deep convolutional neural networks (CNNs) is typically bounded by the receptive field size through filter sizes, and subsampling layers or strided convolutions on feature maps. The optimal resolution may vary significantly depending on the dataset. Modern CNNs hard-code their resolution hyper-parameters i...
1811.07628
Goutam Bhat
Martin Danelljan, Goutam Bhat, Fahad Shahbaz Khan, Michael Felsberg
ATOM: Accurate Tracking by Overlap Maximization
CVPR 2019 (Oral). Complete code and models are available at https://github.com/visionml/pytracking
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
While recent years have witnessed astonishing improvements in visual tracking robustness, the advancements in tracking accuracy have been limited. As the focus has been directed towards the development of powerful classifiers, the problem of accurate target state estimation has been largely overlooked. In fact, most ...
[ { "created": "Mon, 19 Nov 2018 11:40:17 GMT", "version": "v1" }, { "created": "Thu, 11 Apr 2019 17:56:18 GMT", "version": "v2" } ]
2019-04-12
[ [ "Danelljan", "Martin", "" ], [ "Bhat", "Goutam", "" ], [ "Khan", "Fahad Shahbaz", "" ], [ "Felsberg", "Michael", "" ] ]
While recent years have witnessed astonishing improvements in visual tracking robustness, the advancements in tracking accuracy have been limited. As the focus has been directed towards the development of powerful classifiers, the problem of accurate target state estimation has been largely overlooked. In fact, most tr...
2004.14503
Ji Ma
Ji Ma, Ivan Korotkov, Yinfei Yang, Keith Hall and Ryan McDonald
Zero-shot Neural Passage Retrieval via Domain-targeted Synthetic Question Generation
14 pages, 4 figures
null
null
null
cs.IR cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A major obstacle to the wide-spread adoption of neural retrieval models is that they require large supervised training sets to surpass traditional term-based techniques, which are constructed from raw corpora. In this paper, we propose an approach to zero-shot learning for passage retrieval that uses synthetic questi...
[ { "created": "Wed, 29 Apr 2020 22:21:31 GMT", "version": "v1" }, { "created": "Sat, 23 Jan 2021 13:29:55 GMT", "version": "v2" }, { "created": "Wed, 27 Jan 2021 16:04:12 GMT", "version": "v3" } ]
2021-01-28
[ [ "Ma", "Ji", "" ], [ "Korotkov", "Ivan", "" ], [ "Yang", "Yinfei", "" ], [ "Hall", "Keith", "" ], [ "McDonald", "Ryan", "" ] ]
A major obstacle to the wide-spread adoption of neural retrieval models is that they require large supervised training sets to surpass traditional term-based techniques, which are constructed from raw corpora. In this paper, we propose an approach to zero-shot learning for passage retrieval that uses synthetic question...
2203.15215
Li Ni
Li Ni, Hefei Xu, Yiwen Zhang and Wenjian Luo
Spatial-Aware Local Community Detection Guided by Dominance Relation
null
null
null
null
cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The problem of finding the spatial-aware community for a given node has been defined and investigated in geo-social networks. However, existing studies suffer from two limitations: a) the criteria of defining communities are determined by parameters, which are difficult to set; b) algorithms may require global inform...
[ { "created": "Tue, 29 Mar 2022 03:16:14 GMT", "version": "v1" } ]
2022-03-30
[ [ "Ni", "Li", "" ], [ "Xu", "Hefei", "" ], [ "Zhang", "Yiwen", "" ], [ "Luo", "Wenjian", "" ] ]
The problem of finding the spatial-aware community for a given node has been defined and investigated in geo-social networks. However, existing studies suffer from two limitations: a) the criteria of defining communities are determined by parameters, which are difficult to set; b) algorithms may require global informat...
2203.08565
Valentin Hofmann
Valentin Hofmann, Goran Glava\v{s}, Nikola Ljube\v{s}i\'c, Janet B. Pierrehumbert, Hinrich Sch\"utze
Geographic Adaptation of Pretrained Language Models
TACL 2024 (pre-MIT Press publication version)
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
While pretrained language models (PLMs) have been shown to possess a plethora of linguistic knowledge, the existing body of research has largely neglected extralinguistic knowledge, which is generally difficult to obtain by pretraining on text alone. Here, we contribute to closing this gap by examining geolinguistic ...
[ { "created": "Wed, 16 Mar 2022 11:55:00 GMT", "version": "v1" }, { "created": "Mon, 2 Jan 2023 00:20:48 GMT", "version": "v2" }, { "created": "Sun, 28 Jan 2024 22:57:45 GMT", "version": "v3" } ]
2024-01-30
[ [ "Hofmann", "Valentin", "" ], [ "Glavaš", "Goran", "" ], [ "Ljubešić", "Nikola", "" ], [ "Pierrehumbert", "Janet B.", "" ], [ "Schütze", "Hinrich", "" ] ]
While pretrained language models (PLMs) have been shown to possess a plethora of linguistic knowledge, the existing body of research has largely neglected extralinguistic knowledge, which is generally difficult to obtain by pretraining on text alone. Here, we contribute to closing this gap by examining geolinguistic kn...
2203.11604
Pawel Sroka
Pawe{\l} Sroka, Pawe{\l} Kryszkiewicz, Adrian Kliks
Radio Environment Maps for Dynamic Frequency Selection in V2X Communications
null
2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring), 2020
10.1109/VTC2020-Spring48590.2020.9128655
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we investigate the concept of database supported Vehicular Dynamic Spectrum Access (VDSA) for platooning. As various researchers show that the 5.9 GHz band, devoted for Intelligent Transportation Systems, may suffer from congestion of the channel, we propose to offload part of this traffic to white-spa...
[ { "created": "Tue, 22 Mar 2022 10:39:40 GMT", "version": "v1" } ]
2022-03-23
[ [ "Sroka", "Paweł", "" ], [ "Kryszkiewicz", "Paweł", "" ], [ "Kliks", "Adrian", "" ] ]
In this paper, we investigate the concept of database supported Vehicular Dynamic Spectrum Access (VDSA) for platooning. As various researchers show that the 5.9 GHz band, devoted for Intelligent Transportation Systems, may suffer from congestion of the channel, we propose to offload part of this traffic to white-space...
2203.00508
Zhong Tian
Zhong Tian, Zhengchuan Chen, Min Wang, Yunjian Jia, and Wanli Wen
Reconfigurable Intelligent Surface-Aided Spectrum Sharing Coexisting with Multiple Primary Networks
null
null
null
null
cs.IT eess.SP math.IT
http://creativecommons.org/publicdomain/zero/1.0/
Considering the spectrum sharing system (SSS) coexisting with multiple primary networks, we have employed a well-designed reconfigurable intelligent surface (RIS) to control the radio environments of wireless channels and relieve the scarcity of the spectrum resource in this work. Specifically, the enhancement of the...
[ { "created": "Tue, 1 Mar 2022 14:53:13 GMT", "version": "v1" }, { "created": "Fri, 4 Nov 2022 04:55:35 GMT", "version": "v2" } ]
2022-11-07
[ [ "Tian", "Zhong", "" ], [ "Chen", "Zhengchuan", "" ], [ "Wang", "Min", "" ], [ "Jia", "Yunjian", "" ], [ "Wen", "Wanli", "" ] ]
Considering the spectrum sharing system (SSS) coexisting with multiple primary networks, we have employed a well-designed reconfigurable intelligent surface (RIS) to control the radio environments of wireless channels and relieve the scarcity of the spectrum resource in this work. Specifically, the enhancement of the s...
1310.5497
Jocelyne Troccaz
Emmanuel Promayon (TIMC-IMAG), Celine Fouard (TIMC-IMAG), Mathieu Bailet (TIMC-IMAG), Aurelien Deram (TIMC-IMAG), Gaelle Fiard, Nikolai Hungr (TIMC-IMAG), Vincent Luboz (TIMC-IMAG), Yohan Payan (TIMC-IMAG), Johan Sarrazin (TIMC-IMAG), Nicolas Saubat (TIMC-IMAG), Sonia Yuki Selmi (TIMC-IMAG), Sandrine Voros (TIM...
Using CamiTK for rapid prototyping of interactive Computer Assisted Medical Intervention applications
null
Conference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 2013 (2013) 4933-6
10.1109/EMBC.2013.6610654
null
cs.OH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Computer Assisted Medical Intervention (CAMI hereafter) is a complex multi-disciplinary field. CAMI research requires the collaboration of experts in several fields as diverse as medicine, computer science, mathematics, instrumentation, signal processing, mechanics, modeling, automatics, optics, etc.
[ { "created": "Mon, 21 Oct 2013 10:40:02 GMT", "version": "v1" } ]
2013-10-22
[ [ "Promayon", "Emmanuel", "", "TIMC-IMAG" ], [ "Fouard", "Celine", "", "TIMC-IMAG" ], [ "Bailet", "Mathieu", "", "TIMC-IMAG" ], [ "Deram", "Aurelien", "", "TIMC-IMAG" ], [ "Fiard", "Gaelle", "", "TIMC-IMAG" ], [ ...
Computer Assisted Medical Intervention (CAMI hereafter) is a complex multi-disciplinary field. CAMI research requires the collaboration of experts in several fields as diverse as medicine, computer science, mathematics, instrumentation, signal processing, mechanics, modeling, automatics, optics, etc.
2406.03894
Yaozhong Gan
Yaozhong Gan, Renye Yan, Xiaoyang Tan, Zhe Wu, Junliang Xing
Transductive Off-policy Proximal Policy Optimization
18
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Proximal Policy Optimization (PPO) is a popular model-free reinforcement learning algorithm, esteemed for its simplicity and efficacy. However, due to its inherent on-policy nature, its proficiency in harnessing data from disparate policies is constrained. This paper introduces a novel off-policy extension to the ori...
[ { "created": "Thu, 6 Jun 2024 09:29:40 GMT", "version": "v1" } ]
2024-06-07
[ [ "Gan", "Yaozhong", "" ], [ "Yan", "Renye", "" ], [ "Tan", "Xiaoyang", "" ], [ "Wu", "Zhe", "" ], [ "Xing", "Junliang", "" ] ]
Proximal Policy Optimization (PPO) is a popular model-free reinforcement learning algorithm, esteemed for its simplicity and efficacy. However, due to its inherent on-policy nature, its proficiency in harnessing data from disparate policies is constrained. This paper introduces a novel off-policy extension to the origi...
2009.02018
DongGyu Joo
Doyeon Kim, Donggyu Joo, Junmo Kim
TiVGAN: Text to Image to Video Generation with Step-by-Step Evolutionary Generator
IEEE Access
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Advances in technology have led to the development of methods that can create desired visual multimedia. In particular, image generation using deep learning has been extensively studied across diverse fields. In comparison, video generation, especially on conditional inputs, remains a challenging and less explored ar...
[ { "created": "Fri, 4 Sep 2020 06:33:08 GMT", "version": "v1" }, { "created": "Mon, 28 Jun 2021 00:25:23 GMT", "version": "v2" } ]
2021-06-29
[ [ "Kim", "Doyeon", "" ], [ "Joo", "Donggyu", "" ], [ "Kim", "Junmo", "" ] ]
Advances in technology have led to the development of methods that can create desired visual multimedia. In particular, image generation using deep learning has been extensively studied across diverse fields. In comparison, video generation, especially on conditional inputs, remains a challenging and less explored area...
2008.09817
Elizabeth Huang
Elizabeth Y. Huang and Dario Paccagnan and Wenjun Mei and Francesco Bullo
Assign and Appraise: Achieving Optimal Performance in Collaborative Teams
null
null
null
null
cs.SI cs.SY eess.SY math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Tackling complex team problems requires understanding each team member's skills in order to devise a task assignment maximizing the team performance. This paper proposes a novel quantitative model describing the decentralized process by which individuals in a team learn who has what abilities, while concurrently assi...
[ { "created": "Sat, 22 Aug 2020 11:39:09 GMT", "version": "v1" } ]
2020-08-25
[ [ "Huang", "Elizabeth Y.", "" ], [ "Paccagnan", "Dario", "" ], [ "Mei", "Wenjun", "" ], [ "Bullo", "Francesco", "" ] ]
Tackling complex team problems requires understanding each team member's skills in order to devise a task assignment maximizing the team performance. This paper proposes a novel quantitative model describing the decentralized process by which individuals in a team learn who has what abilities, while concurrently assign...
1608.01373
Lin Li
Lin Li and W.M. Campbell
Matching Community Structure Across Online Social Networks
null
Workshop on Networks in the Social and Information Sciences, NIPS 2015
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The discovery of community structure in networks is a problem of considerable interest in recent years. In online social networks, often times, users are simultaneously involved in multiple social media sites, some of which share common social relationships. It is of great interest to uncover a shared community struc...
[ { "created": "Wed, 3 Aug 2016 22:02:29 GMT", "version": "v1" } ]
2016-08-05
[ [ "Li", "Lin", "" ], [ "Campbell", "W. M.", "" ] ]
The discovery of community structure in networks is a problem of considerable interest in recent years. In online social networks, often times, users are simultaneously involved in multiple social media sites, some of which share common social relationships. It is of great interest to uncover a shared community structu...
1711.00244
Anamitra R. Choudhury
Dharma Teja Vooturi, Saurabh Goyal, Anamitra R. Choudhury, Yogish Sabharwal, Ashish Verma
Efficient Inferencing of Compressed Deep Neural Networks
null
null
null
null
cs.DC cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large number of weights in deep neural networks makes the models difficult to be deployed in low memory environments such as, mobile phones, IOT edge devices as well as "inferencing as a service" environments on cloud. Prior work has considered reduction in the size of the models, through compression techniques like ...
[ { "created": "Wed, 1 Nov 2017 08:16:40 GMT", "version": "v1" } ]
2017-11-02
[ [ "Vooturi", "Dharma Teja", "" ], [ "Goyal", "Saurabh", "" ], [ "Choudhury", "Anamitra R.", "" ], [ "Sabharwal", "Yogish", "" ], [ "Verma", "Ashish", "" ] ]
Large number of weights in deep neural networks makes the models difficult to be deployed in low memory environments such as, mobile phones, IOT edge devices as well as "inferencing as a service" environments on cloud. Prior work has considered reduction in the size of the models, through compression techniques like pr...
2211.05446
Meng Chen
Meng Chen, Li Lu, Jiadi Yu, Yingying Chen, Zhongjie Ba, Feng Lin, Kui Ren
Privacy-Utility Balanced Voice De-Identification Using Adversarial Examples
null
null
null
null
cs.SD cs.CR cs.LG eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Faced with the threat of identity leakage during voice data publishing, users are engaged in a privacy-utility dilemma when enjoying convenient voice services. Existing studies employ direct modification or text-based re-synthesis to de-identify users' voices, but resulting in inconsistent audibility in the presence ...
[ { "created": "Thu, 10 Nov 2022 09:35:58 GMT", "version": "v1" } ]
2022-11-11
[ [ "Chen", "Meng", "" ], [ "Lu", "Li", "" ], [ "Yu", "Jiadi", "" ], [ "Chen", "Yingying", "" ], [ "Ba", "Zhongjie", "" ], [ "Lin", "Feng", "" ], [ "Ren", "Kui", "" ] ]
Faced with the threat of identity leakage during voice data publishing, users are engaged in a privacy-utility dilemma when enjoying convenient voice services. Existing studies employ direct modification or text-based re-synthesis to de-identify users' voices, but resulting in inconsistent audibility in the presence of...
1802.08130
Jos\'e Vuelvas
Jos\'e Vuelvas and Fredy Ruiz
A novel incentive-based demand response model for Cournot competition in electricity markets
null
Vuelvas, J. & Ruiz, F. Energy Syst (2018). https://doi.org/10.1007/s12667-018-0271-2
null
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents an analysis of competition between generators when incentive-based demand response is employed in an electricity market. Thermal and hydropower generation are considered in the model. A smooth inverse demand function is designed using a sigmoid and two linear functions for modeling the consumer pr...
[ { "created": "Thu, 22 Feb 2018 16:12:09 GMT", "version": "v1" } ]
2018-02-23
[ [ "Vuelvas", "José", "" ], [ "Ruiz", "Fredy", "" ] ]
This paper presents an analysis of competition between generators when incentive-based demand response is employed in an electricity market. Thermal and hydropower generation are considered in the model. A smooth inverse demand function is designed using a sigmoid and two linear functions for modeling the consumer pref...
2210.16074
David Biesner
David Biesner, Helen Schneider, Benjamin Wulff, Ulrike Attenberger, Rafet Sifa
Improving Chest X-Ray Classification by RNN-based Patient Monitoring
To be published in proceedings of IEEE International Conference on Machine Learning Applications IEEE ICMLA 2022
null
null
null
cs.LG cs.CV
http://creativecommons.org/licenses/by/4.0/
Chest X-Ray imaging is one of the most common radiological tools for detection of various pathologies related to the chest area and lung function. In a clinical setting, automated assessment of chest radiographs has the potential of assisting physicians in their decision making process and optimize clinical workflows...
[ { "created": "Fri, 28 Oct 2022 11:47:15 GMT", "version": "v1" } ]
2022-10-31
[ [ "Biesner", "David", "" ], [ "Schneider", "Helen", "" ], [ "Wulff", "Benjamin", "" ], [ "Attenberger", "Ulrike", "" ], [ "Sifa", "Rafet", "" ] ]
Chest X-Ray imaging is one of the most common radiological tools for detection of various pathologies related to the chest area and lung function. In a clinical setting, automated assessment of chest radiographs has the potential of assisting physicians in their decision making process and optimize clinical workflows, ...
1501.02967
Thanh Bui
Thanh Bui
Analysis of Docker Security
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Over the last few years, the use of virtualization technologies has increased dramatically. This makes the demand for efficient and secure virtualization solutions become more obvious. Container-based virtualization and hypervisor-based virtualization are two main types of virtualization technologies that have emerge...
[ { "created": "Tue, 13 Jan 2015 11:44:02 GMT", "version": "v1" } ]
2015-01-14
[ [ "Bui", "Thanh", "" ] ]
Over the last few years, the use of virtualization technologies has increased dramatically. This makes the demand for efficient and secure virtualization solutions become more obvious. Container-based virtualization and hypervisor-based virtualization are two main types of virtualization technologies that have emerged ...
2105.04328
Indrajit Kurmi
D.C. Schedl, I. Kurmi, and O. Bimber
An Autonomous Drone for Search and Rescue in Forests using Airborne Optical Sectioning
21 pages, 9 figures
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
Drones will play an essential role in human-machine teaming in future search and rescue (SAR) missions. We present a first prototype that finds people fully autonomously in densely occluded forests. In the course of 17 field experiments conducted over various forest types and under different flying conditions, our dr...
[ { "created": "Mon, 10 May 2021 13:05:22 GMT", "version": "v1" } ]
2021-05-11
[ [ "Schedl", "D. C.", "" ], [ "Kurmi", "I.", "" ], [ "Bimber", "O.", "" ] ]
Drones will play an essential role in human-machine teaming in future search and rescue (SAR) missions. We present a first prototype that finds people fully autonomously in densely occluded forests. In the course of 17 field experiments conducted over various forest types and under different flying conditions, our dron...
1201.1812
Jiun-Hung Yu
Jiun-Hung Yu and Hans-Andrea Loeliger
On Polynomial Remainder Codes
null
null
null
null
cs.IT math.IT math.RA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Polynomial remainder codes are a large class of codes derived from the Chinese remainder theorem that includes Reed-Solomon codes as a special case. In this paper, we revisit these codes and study them more carefully than in previous work. We explicitly allow the code symbols to be polynomials of different degrees, w...
[ { "created": "Mon, 9 Jan 2012 16:00:45 GMT", "version": "v1" } ]
2012-01-10
[ [ "Yu", "Jiun-Hung", "" ], [ "Loeliger", "Hans-Andrea", "" ] ]
Polynomial remainder codes are a large class of codes derived from the Chinese remainder theorem that includes Reed-Solomon codes as a special case. In this paper, we revisit these codes and study them more carefully than in previous work. We explicitly allow the code symbols to be polynomials of different degrees, whi...
1210.6685
Guodong Shi
Guodong Shi, Alexandre Proutiere and Karl Henrik Johansson
Distributed Optimization: Convergence Conditions from a Dynamical System Perspective
null
null
null
null
cs.SY cs.DC math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper explores the fundamental properties of distributed minimization of a sum of functions with each function only known to one node, and a pre-specified level of node knowledge and computational capacity. We define the optimization information each node receives from its objective function, the neighboring inf...
[ { "created": "Wed, 24 Oct 2012 21:28:36 GMT", "version": "v1" } ]
2012-10-26
[ [ "Shi", "Guodong", "" ], [ "Proutiere", "Alexandre", "" ], [ "Johansson", "Karl Henrik", "" ] ]
This paper explores the fundamental properties of distributed minimization of a sum of functions with each function only known to one node, and a pre-specified level of node knowledge and computational capacity. We define the optimization information each node receives from its objective function, the neighboring infor...
2310.11960
Yanming Kang
Yanming Kang, Giang Tran, Hans De Sterck
Fast Multipole Attention: A Divide-and-Conquer Attention Mechanism for Long Sequences
null
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Transformer-based models have achieved state-of-the-art performance in many areas. However, the quadratic complexity of self-attention with respect to the input length hinders the applicability of Transformer-based models to long sequences. To address this, we present Fast Multipole Attention, a new attention mechani...
[ { "created": "Wed, 18 Oct 2023 13:40:41 GMT", "version": "v1" }, { "created": "Sat, 21 Oct 2023 01:56:32 GMT", "version": "v2" }, { "created": "Tue, 30 Jul 2024 15:02:51 GMT", "version": "v3" } ]
2024-07-31
[ [ "Kang", "Yanming", "" ], [ "Tran", "Giang", "" ], [ "De Sterck", "Hans", "" ] ]
Transformer-based models have achieved state-of-the-art performance in many areas. However, the quadratic complexity of self-attention with respect to the input length hinders the applicability of Transformer-based models to long sequences. To address this, we present Fast Multipole Attention, a new attention mechanism...
1910.14026
Federico Orsini
Federico Orsini, Massimiliano Gastaldi, Luca Mantecchini, Riccardo Rossi
Neural networks trained with WiFi traces to predict airport passenger behavior
Post-print of paper presented at the 2019 6th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)
2019 6th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)
10.1109/MTITS.2019.8883365
null
cs.LG eess.SP stat.AP stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The use of neural networks to predict airport passenger activity choices inside the terminal is presented in this paper. Three network architectures are proposed: Feedforward Neural Networks (FNN), Long Short-Term Memory (LSTM) networks, and a combination of the two. Inputs to these models are both static (passenger ...
[ { "created": "Wed, 30 Oct 2019 08:11:38 GMT", "version": "v1" } ]
2019-11-01
[ [ "Orsini", "Federico", "" ], [ "Gastaldi", "Massimiliano", "" ], [ "Mantecchini", "Luca", "" ], [ "Rossi", "Riccardo", "" ] ]
The use of neural networks to predict airport passenger activity choices inside the terminal is presented in this paper. Three network architectures are proposed: Feedforward Neural Networks (FNN), Long Short-Term Memory (LSTM) networks, and a combination of the two. Inputs to these models are both static (passenger an...