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2203.15404
Christian Huber
Christian Huber, Rishu Kumar, Ond\v{r}ej Bojar, Alexander Waibel
Short-Term Word-Learning in a Dynamically Changing Environment
This paper was submitted to Interspeech 2022
null
null
null
cs.CL
http://creativecommons.org/licenses/by-sa/4.0/
Neural sequence-to-sequence automatic speech recognition (ASR) systems are in principle open vocabulary systems, when using appropriate modeling units. In practice, however, they often fail to recognize words not seen during training, e.g., named entities, numbers or technical terms. To alleviate this problem, Huber ...
[ { "created": "Tue, 29 Mar 2022 10:05:39 GMT", "version": "v1" } ]
2022-03-30
[ [ "Huber", "Christian", "" ], [ "Kumar", "Rishu", "" ], [ "Bojar", "Ondřej", "" ], [ "Waibel", "Alexander", "" ] ]
Neural sequence-to-sequence automatic speech recognition (ASR) systems are in principle open vocabulary systems, when using appropriate modeling units. In practice, however, they often fail to recognize words not seen during training, e.g., named entities, numbers or technical terms. To alleviate this problem, Huber et...
2405.01649
Tianle Xia
Tianle Xia, Liang Ding, Guojia Wan, Yibing Zhan, Bo Du, Dacheng Tao
Improving Complex Reasoning over Knowledge Graph with Logic-Aware Curriculum Tuning
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Answering complex queries over incomplete knowledge graphs (KGs) is a challenging job. Most previous works have focused on learning entity/relation embeddings and simulating first-order logic operators with various neural networks. However, they are bottlenecked by the inability to share world knowledge to improve lo...
[ { "created": "Thu, 2 May 2024 18:12:08 GMT", "version": "v1" }, { "created": "Tue, 7 May 2024 16:10:51 GMT", "version": "v2" }, { "created": "Wed, 8 May 2024 18:21:04 GMT", "version": "v3" } ]
2024-05-10
[ [ "Xia", "Tianle", "" ], [ "Ding", "Liang", "" ], [ "Wan", "Guojia", "" ], [ "Zhan", "Yibing", "" ], [ "Du", "Bo", "" ], [ "Tao", "Dacheng", "" ] ]
Answering complex queries over incomplete knowledge graphs (KGs) is a challenging job. Most previous works have focused on learning entity/relation embeddings and simulating first-order logic operators with various neural networks. However, they are bottlenecked by the inability to share world knowledge to improve logi...
2211.15107
Yash Sanjay Bhalgat
Yash Bhalgat, Joao F. Henriques, Andrew Zisserman
A Light Touch Approach to Teaching Transformers Multi-view Geometry
Camera-ready version. Accepted to CVPR 2023
null
null
null
cs.CV cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Transformers are powerful visual learners, in large part due to their conspicuous lack of manually-specified priors. This flexibility can be problematic in tasks that involve multiple-view geometry, due to the near-infinite possible variations in 3D shapes and viewpoints (requiring flexibility), and the precise natur...
[ { "created": "Mon, 28 Nov 2022 07:54:06 GMT", "version": "v1" }, { "created": "Sun, 2 Apr 2023 12:15:52 GMT", "version": "v2" } ]
2023-04-04
[ [ "Bhalgat", "Yash", "" ], [ "Henriques", "Joao F.", "" ], [ "Zisserman", "Andrew", "" ] ]
Transformers are powerful visual learners, in large part due to their conspicuous lack of manually-specified priors. This flexibility can be problematic in tasks that involve multiple-view geometry, due to the near-infinite possible variations in 3D shapes and viewpoints (requiring flexibility), and the precise nature ...
1609.02770
Andrew Gilbert
Andrew Gilbert, Richard Bowden
Image and Video Mining through Online Learning
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Within the field of image and video recognition, the traditional approach is a dataset split into fixed training and test partitions. However, the labelling of the training set is time-consuming, especially as datasets grow in size and complexity. Furthermore, this approach is not applicable to the home user, who wan...
[ { "created": "Fri, 9 Sep 2016 12:49:22 GMT", "version": "v1" }, { "created": "Wed, 7 Dec 2016 12:26:30 GMT", "version": "v2" } ]
2016-12-08
[ [ "Gilbert", "Andrew", "" ], [ "Bowden", "Richard", "" ] ]
Within the field of image and video recognition, the traditional approach is a dataset split into fixed training and test partitions. However, the labelling of the training set is time-consuming, especially as datasets grow in size and complexity. Furthermore, this approach is not applicable to the home user, who wants...
2106.07317
Alexandru-Ionut Imbrea
Alexandru-Ionut Imbrea
Automated Machine Learning Techniques for Data Streams
11 pages, 14 figures, Originally published as https://essay.utwente.nl/80548 at the 32nd Twente Student Conference on IT Jan. 31st, 2019, Enschede, The Netherlands, Supervised by: dr. Doina Bucur, dr. Claudio Pinho Rebelo de S\'a
null
null
UTwente Essay no: 80548
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Automated machine learning techniques benefited from tremendous research progress in recently. These developments and the continuous-growing demand for machine learning experts led to the development of numerous AutoML tools. However, these tools assume that the entire training dataset is available upfront and that t...
[ { "created": "Mon, 14 Jun 2021 11:42:46 GMT", "version": "v1" } ]
2021-06-15
[ [ "Imbrea", "Alexandru-Ionut", "" ] ]
Automated machine learning techniques benefited from tremendous research progress in recently. These developments and the continuous-growing demand for machine learning experts led to the development of numerous AutoML tools. However, these tools assume that the entire training dataset is available upfront and that the...
1707.00445
David Sanchez
David S\'anchez, Montserrat Batet
Privacy-preserving data outsourcing in the cloud via semantic data splitting
null
Computer Communications, Volume 110, Pages 187-201 (15 September 2017)
10.1016/j.comcom.2017.06.012
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Even though cloud computing provides many intrinsic benefits, privacy concerns related to the lack of control over the storage and management of the outsourced data still prevent many customers from migrating to the cloud. Several privacy-protection mechanisms based on a prior encryption of the data to be outsourced ...
[ { "created": "Mon, 3 Jul 2017 08:49:20 GMT", "version": "v1" } ]
2017-07-07
[ [ "Sánchez", "David", "" ], [ "Batet", "Montserrat", "" ] ]
Even though cloud computing provides many intrinsic benefits, privacy concerns related to the lack of control over the storage and management of the outsourced data still prevent many customers from migrating to the cloud. Several privacy-protection mechanisms based on a prior encryption of the data to be outsourced ha...
1012.3947
Agust\'in Valverde
Dov Gabbay and David Pearce and Agust\'i n Valverde
Interpolation in Equilibrium Logic and Answer Set Programming: the Propositional Case
ASPOCP 2010
null
null
null
cs.LO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Interpolation is an important property of classical and many non classical logics that has been shown to have interesting applications in computer science and AI. Here we study the Interpolation Property for the propositional version of the non-monotonic system of equilibrium logic, establishing weaker or stronger fo...
[ { "created": "Fri, 17 Dec 2010 18:05:51 GMT", "version": "v1" } ]
2010-12-20
[ [ "Gabbay", "Dov", "" ], [ "Pearce", "David", "" ], [ "Valverde", "Agustí n", "" ] ]
Interpolation is an important property of classical and many non classical logics that has been shown to have interesting applications in computer science and AI. Here we study the Interpolation Property for the propositional version of the non-monotonic system of equilibrium logic, establishing weaker or stronger form...
2210.10392
Youjia Zhang
Youjia Zhang, Soyun Choi, and Sungeun Hong
Spatio-channel Attention Blocks for Cross-modal Crowd Counting
Accepted to ACCV 2022 (Oral). Code is available at https://github.com/vcllab/csca
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Crowd counting research has made significant advancements in real-world applications, but it remains a formidable challenge in cross-modal settings. Most existing methods rely solely on the optical features of RGB images, ignoring the feasibility of other modalities such as thermal and depth images. The inherently si...
[ { "created": "Wed, 19 Oct 2022 09:05:00 GMT", "version": "v1" }, { "created": "Mon, 24 Oct 2022 04:10:54 GMT", "version": "v2" }, { "created": "Wed, 2 Nov 2022 07:29:09 GMT", "version": "v3" }, { "created": "Mon, 14 Nov 2022 11:40:00 GMT", "version": "v4" } ]
2022-11-15
[ [ "Zhang", "Youjia", "" ], [ "Choi", "Soyun", "" ], [ "Hong", "Sungeun", "" ] ]
Crowd counting research has made significant advancements in real-world applications, but it remains a formidable challenge in cross-modal settings. Most existing methods rely solely on the optical features of RGB images, ignoring the feasibility of other modalities such as thermal and depth images. The inherently sign...
1207.1114
Yao Lu
Yao Lu, Kaizhu Huang, Cheng-Lin Liu
A Fast Projected Fixed-Point Algorithm for Large Graph Matching
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a fast approximate algorithm for large graph matching. A new projected fixed-point method is defined and a new doubly stochastic projection is adopted to derive the algorithm. Previous graph matching algorithms suffer from high computational complexity and therefore do not have good scalability with respec...
[ { "created": "Tue, 3 Jul 2012 18:20:25 GMT", "version": "v1" }, { "created": "Mon, 9 Jul 2012 14:50:16 GMT", "version": "v2" }, { "created": "Fri, 10 Aug 2012 08:51:17 GMT", "version": "v3" } ]
2012-08-13
[ [ "Lu", "Yao", "" ], [ "Huang", "Kaizhu", "" ], [ "Liu", "Cheng-Lin", "" ] ]
We propose a fast approximate algorithm for large graph matching. A new projected fixed-point method is defined and a new doubly stochastic projection is adopted to derive the algorithm. Previous graph matching algorithms suffer from high computational complexity and therefore do not have good scalability with respect ...
1509.09236
Nicolas Gillis
Nicolas Gillis, Stephen A. Vavasis
On the Complexity of Robust PCA and $\ell_1$-norm Low-Rank Matrix Approximation
16 pages, some typos corrected
Mathematics of Operations Research 43 (4), pp. 1072-1084, 2018
10.1287/moor.2017.0895
null
cs.LG cs.CC math.NA math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The low-rank matrix approximation problem with respect to the component-wise $\ell_1$-norm ($\ell_1$-LRA), which is closely related to robust principal component analysis (PCA), has become a very popular tool in data mining and machine learning. Robust PCA aims at recovering a low-rank matrix that was perturbed with ...
[ { "created": "Wed, 30 Sep 2015 16:05:50 GMT", "version": "v1" }, { "created": "Sun, 8 Nov 2015 16:48:44 GMT", "version": "v2" }, { "created": "Wed, 19 Apr 2017 10:12:17 GMT", "version": "v3" } ]
2018-12-19
[ [ "Gillis", "Nicolas", "" ], [ "Vavasis", "Stephen A.", "" ] ]
The low-rank matrix approximation problem with respect to the component-wise $\ell_1$-norm ($\ell_1$-LRA), which is closely related to robust principal component analysis (PCA), has become a very popular tool in data mining and machine learning. Robust PCA aims at recovering a low-rank matrix that was perturbed with sp...
2304.00954
Fnu Aryan
Aryan, Bowen Li, Sebastian Scherer, Yun-Jou Lin, Chen Wang
AirLoc: Object-based Indoor Relocalization
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Indoor relocalization is vital for both robotic tasks like autonomous exploration and civil applications such as navigation with a cell phone in a shopping mall. Some previous approaches adopt geometrical information such as key-point features or local textures to carry out indoor relocalization, but they either easi...
[ { "created": "Mon, 3 Apr 2023 13:16:47 GMT", "version": "v1" } ]
2023-04-04
[ [ "Aryan", "", "" ], [ "Li", "Bowen", "" ], [ "Scherer", "Sebastian", "" ], [ "Lin", "Yun-Jou", "" ], [ "Wang", "Chen", "" ] ]
Indoor relocalization is vital for both robotic tasks like autonomous exploration and civil applications such as navigation with a cell phone in a shopping mall. Some previous approaches adopt geometrical information such as key-point features or local textures to carry out indoor relocalization, but they either easily...
2401.02914
Parvin Malekzadeh
Parvin Malekzadeh, Ming Hou, Konstantinos N. Plataniotis
A unified uncertainty-aware exploration: Combining epistemic and aleatory uncertainty
Accepted by ICASSP2023
null
10.1109/ICASSP49357.2023.10095594
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Exploration is a significant challenge in practical reinforcement learning (RL), and uncertainty-aware exploration that incorporates the quantification of epistemic and aleatory uncertainty has been recognized as an effective exploration strategy. However, capturing the combined effect of aleatory and epistemic uncer...
[ { "created": "Fri, 5 Jan 2024 17:39:00 GMT", "version": "v1" } ]
2024-01-08
[ [ "Malekzadeh", "Parvin", "" ], [ "Hou", "Ming", "" ], [ "Plataniotis", "Konstantinos N.", "" ] ]
Exploration is a significant challenge in practical reinforcement learning (RL), and uncertainty-aware exploration that incorporates the quantification of epistemic and aleatory uncertainty has been recognized as an effective exploration strategy. However, capturing the combined effect of aleatory and epistemic uncerta...
2212.01537
Hao Ren
Hao Ren, Guowen Xu, Tianwei Zhang, Jianting Ning, Xinyi Huang, Hongwei Li, Rongxing Lu
Efficiency Boosting of Secure Cross-platform Recommender Systems over Sparse Data
null
null
null
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
Fueled by its successful commercialization, the recommender system (RS) has gained widespread attention. However, as the training data fed into the RS models are often highly sensitive, it ultimately leads to severe privacy concerns, especially when data are shared among different platforms. In this paper, we follow ...
[ { "created": "Sat, 3 Dec 2022 05:10:13 GMT", "version": "v1" } ]
2022-12-06
[ [ "Ren", "Hao", "" ], [ "Xu", "Guowen", "" ], [ "Zhang", "Tianwei", "" ], [ "Ning", "Jianting", "" ], [ "Huang", "Xinyi", "" ], [ "Li", "Hongwei", "" ], [ "Lu", "Rongxing", "" ] ]
Fueled by its successful commercialization, the recommender system (RS) has gained widespread attention. However, as the training data fed into the RS models are often highly sensitive, it ultimately leads to severe privacy concerns, especially when data are shared among different platforms. In this paper, we follow th...
2002.03509
Shangbang Long
Shangbang Long, Yushuo Guan, Kaigui Bian, Cong Yao
A New Perspective for Flexible Feature Gathering in Scene Text Recognition Via Character Anchor Pooling
To appear at ICASSP 2020
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Irregular scene text recognition has attracted much attention from the research community, mainly due to the complexity of shapes of text in natural scene. However, recent methods either rely on shape-sensitive modules such as bounding box regression, or discard sequence learning. To tackle these issues, we propo...
[ { "created": "Mon, 10 Feb 2020 03:01:23 GMT", "version": "v1" } ]
2020-02-11
[ [ "Long", "Shangbang", "" ], [ "Guan", "Yushuo", "" ], [ "Bian", "Kaigui", "" ], [ "Yao", "Cong", "" ] ]
Irregular scene text recognition has attracted much attention from the research community, mainly due to the complexity of shapes of text in natural scene. However, recent methods either rely on shape-sensitive modules such as bounding box regression, or discard sequence learning. To tackle these issues, we propose a p...
2312.06409
Zhiyu Pan
Zhiyu Pan, Zhicheng Zhong, Wenxuan Guo, Yifan Chen, Jianjiang Feng, Jie Zhou
LiCamPose: Combining Multi-View LiDAR and RGB Cameras for Robust Single-frame 3D Human Pose Estimation
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Several methods have been proposed to estimate 3D human pose from multi-view images, achieving satisfactory performance on public datasets collected under relatively simple conditions. However, there are limited approaches studying extracting 3D human skeletons from multimodal inputs, such as RGB and point cloud data...
[ { "created": "Mon, 11 Dec 2023 14:30:11 GMT", "version": "v1" }, { "created": "Tue, 12 Dec 2023 04:37:20 GMT", "version": "v2" }, { "created": "Tue, 16 Jul 2024 09:30:58 GMT", "version": "v3" } ]
2024-07-17
[ [ "Pan", "Zhiyu", "" ], [ "Zhong", "Zhicheng", "" ], [ "Guo", "Wenxuan", "" ], [ "Chen", "Yifan", "" ], [ "Feng", "Jianjiang", "" ], [ "Zhou", "Jie", "" ] ]
Several methods have been proposed to estimate 3D human pose from multi-view images, achieving satisfactory performance on public datasets collected under relatively simple conditions. However, there are limited approaches studying extracting 3D human skeletons from multimodal inputs, such as RGB and point cloud data. ...
1409.0098
Hung-Lung Wang
Hung-Lung Wang
An optimal algorithm for the weighted backup 2-center problem on a tree
14 pages, 4 figures
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we are concerned with the weighted backup 2-center problem on a tree. The backup 2-center problem is a kind of center facility location problem, in which one is asked to deploy two facilities, with a given probability to fail, in a network. Given that the two facilities do not fail simultaneously, the ...
[ { "created": "Sat, 30 Aug 2014 10:16:48 GMT", "version": "v1" }, { "created": "Wed, 17 Sep 2014 04:03:20 GMT", "version": "v2" }, { "created": "Wed, 8 Jul 2015 03:49:42 GMT", "version": "v3" } ]
2015-07-09
[ [ "Wang", "Hung-Lung", "" ] ]
In this paper, we are concerned with the weighted backup 2-center problem on a tree. The backup 2-center problem is a kind of center facility location problem, in which one is asked to deploy two facilities, with a given probability to fail, in a network. Given that the two facilities do not fail simultaneously, the go...
2403.11202
Kaiyan Chang
Kaiyan Chang and Kun Wang and Nan Yang and Ying Wang and Dantong Jin and Wenlong Zhu and Zhirong Chen and Cangyuan Li and Hao Yan and Yunhao Zhou and Zhuoliang Zhao and Yuan Cheng and Yudong Pan and Yiqi Liu and Mengdi Wang and Shengwen Liang and Yinhe Han and Huawei Li and Xiaowei Li
Data is all you need: Finetuning LLMs for Chip Design via an Automated design-data augmentation framework
DAC 2024
null
10.1145/3649329.3657356
null
cs.AR cs.AI cs.PL
http://creativecommons.org/licenses/by/4.0/
Recent advances in large language models have demonstrated their potential for automated generation of hardware description language (HDL) code from high-level prompts. Researchers have utilized fine-tuning to enhance the ability of these large language models (LLMs) in the field of Chip Design. However, the lack of ...
[ { "created": "Sun, 17 Mar 2024 13:01:03 GMT", "version": "v1" }, { "created": "Wed, 10 Jul 2024 09:06:40 GMT", "version": "v2" } ]
2024-07-11
[ [ "Chang", "Kaiyan", "" ], [ "Wang", "Kun", "" ], [ "Yang", "Nan", "" ], [ "Wang", "Ying", "" ], [ "Jin", "Dantong", "" ], [ "Zhu", "Wenlong", "" ], [ "Chen", "Zhirong", "" ], [ "Li", "Cangyuan", ...
Recent advances in large language models have demonstrated their potential for automated generation of hardware description language (HDL) code from high-level prompts. Researchers have utilized fine-tuning to enhance the ability of these large language models (LLMs) in the field of Chip Design. However, the lack of Ve...
1703.05185
Manuel Mazzara
Manuel Mazzara
Designing a pi-based Programming Language in the .NET framework: CLR interoperability from the Programmer's point of view
null
null
null
null
cs.PL cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Interoperability is the ability of a programming language to work with systems based on different languages and paradigms. These days, many widely used high-level language impementations provide access to external functionalities. In this paper, we present some ideas on CLR interoperability focusing on the kind of co...
[ { "created": "Wed, 15 Mar 2017 14:40:21 GMT", "version": "v1" } ]
2017-03-16
[ [ "Mazzara", "Manuel", "" ] ]
Interoperability is the ability of a programming language to work with systems based on different languages and paradigms. These days, many widely used high-level language impementations provide access to external functionalities. In this paper, we present some ideas on CLR interoperability focusing on the kind of cons...
2403.08778
Chuang Wang
Chuang Wang, Zhengping Li, Yuwen Hao, Lijun Wang, Xiaoxue Li
Faster Projected GAN: Towards Faster Few-Shot Image Generation
9 pages,7 figures,4 tables
null
null
null
cs.CV cs.GR eess.IV
http://creativecommons.org/licenses/by/4.0/
In order to solve the problems of long training time, large consumption of computing resources and huge parameter amount of GAN network in image generation, this paper proposes an improved GAN network model, which is named Faster Projected GAN, based on Projected GAN. The proposed network is mainly focuses on the imp...
[ { "created": "Tue, 23 Jan 2024 07:55:27 GMT", "version": "v1" } ]
2024-03-15
[ [ "Wang", "Chuang", "" ], [ "Li", "Zhengping", "" ], [ "Hao", "Yuwen", "" ], [ "Wang", "Lijun", "" ], [ "Li", "Xiaoxue", "" ] ]
In order to solve the problems of long training time, large consumption of computing resources and huge parameter amount of GAN network in image generation, this paper proposes an improved GAN network model, which is named Faster Projected GAN, based on Projected GAN. The proposed network is mainly focuses on the impro...
2104.13365
Majed El Helou
Majed El Helou and Ruofan Zhou and Sabine Susstrunk and Radu Timofte
NTIRE 2021 Depth Guided Image Relighting Challenge
Code and data available on https://github.com/majedelhelou/VIDIT
IEEE Conference on Computer Vision and Pattern Recognition Workshops 2021
null
null
cs.CV eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Image relighting is attracting increasing interest due to its various applications. From a research perspective, image relighting can be exploited to conduct both image normalization for domain adaptation, and also for data augmentation. It also has multiple direct uses for photo montage and aesthetic enhancement. In...
[ { "created": "Tue, 27 Apr 2021 17:53:32 GMT", "version": "v1" } ]
2021-04-28
[ [ "Helou", "Majed El", "" ], [ "Zhou", "Ruofan", "" ], [ "Susstrunk", "Sabine", "" ], [ "Timofte", "Radu", "" ] ]
Image relighting is attracting increasing interest due to its various applications. From a research perspective, image relighting can be exploited to conduct both image normalization for domain adaptation, and also for data augmentation. It also has multiple direct uses for photo montage and aesthetic enhancement. In t...
2406.18864
Wenxuan Ma
Wenxuan Ma, Shuang Li, Lincan Cai, Jingxuan Kang
Learning Modality Knowledge Alignment for Cross-Modality Transfer
ICML 2024
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Cross-modality transfer aims to leverage large pretrained models to complete tasks that may not belong to the modality of pretraining data. Existing works achieve certain success in extending classical finetuning to cross-modal scenarios, yet we still lack understanding about the influence of modality gap on the tran...
[ { "created": "Thu, 27 Jun 2024 03:23:47 GMT", "version": "v1" } ]
2024-06-28
[ [ "Ma", "Wenxuan", "" ], [ "Li", "Shuang", "" ], [ "Cai", "Lincan", "" ], [ "Kang", "Jingxuan", "" ] ]
Cross-modality transfer aims to leverage large pretrained models to complete tasks that may not belong to the modality of pretraining data. Existing works achieve certain success in extending classical finetuning to cross-modal scenarios, yet we still lack understanding about the influence of modality gap on the transf...
2307.16317
Weidong Li
Weidong Li, Mengxiao Zhang, Libo Zhang, Jiamou Liu
Integrated Private Data Trading Systems for Data Marketplaces
null
null
null
null
cs.MA
http://creativecommons.org/licenses/by/4.0/
In the digital age, data is a valuable commodity, and data marketplaces offer lucrative opportunities for data owners to monetize their private data. However, data privacy is a significant concern, and differential privacy has become a popular solution to address this issue. Private data trading systems (PDQS) facili...
[ { "created": "Sun, 30 Jul 2023 20:54:04 GMT", "version": "v1" } ]
2023-08-01
[ [ "Li", "Weidong", "" ], [ "Zhang", "Mengxiao", "" ], [ "Zhang", "Libo", "" ], [ "Liu", "Jiamou", "" ] ]
In the digital age, data is a valuable commodity, and data marketplaces offer lucrative opportunities for data owners to monetize their private data. However, data privacy is a significant concern, and differential privacy has become a popular solution to address this issue. Private data trading systems (PDQS) facilita...
2106.04823
Sina Mohseni
Sina Mohseni and Haotao Wang and Zhiding Yu and Chaowei Xiao and Zhangyang Wang and Jay Yadawa
Taxonomy of Machine Learning Safety: A Survey and Primer
null
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The open-world deployment of Machine Learning (ML) algorithms in safety-critical applications such as autonomous vehicles needs to address a variety of ML vulnerabilities such as interpretability, verifiability, and performance limitations. Research explores different approaches to improve ML dependability by proposi...
[ { "created": "Wed, 9 Jun 2021 05:56:42 GMT", "version": "v1" }, { "created": "Tue, 8 Mar 2022 00:22:37 GMT", "version": "v2" } ]
2022-03-09
[ [ "Mohseni", "Sina", "" ], [ "Wang", "Haotao", "" ], [ "Yu", "Zhiding", "" ], [ "Xiao", "Chaowei", "" ], [ "Wang", "Zhangyang", "" ], [ "Yadawa", "Jay", "" ] ]
The open-world deployment of Machine Learning (ML) algorithms in safety-critical applications such as autonomous vehicles needs to address a variety of ML vulnerabilities such as interpretability, verifiability, and performance limitations. Research explores different approaches to improve ML dependability by proposing...
2306.00301
Sagnik Anupam
Shinjini Ghosh, Sagnik Anupam
CapText: Large Language Model-based Caption Generation From Image Context and Description
Update 6/6/23: Fixed typographic error in abstract
null
null
null
cs.LG cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
While deep-learning models have been shown to perform well on image-to-text datasets, it is difficult to use them in practice for captioning images. This is because captions traditionally tend to be context-dependent and offer complementary information about an image, while models tend to produce descriptions that de...
[ { "created": "Thu, 1 Jun 2023 02:40:44 GMT", "version": "v1" }, { "created": "Tue, 6 Jun 2023 03:41:05 GMT", "version": "v2" } ]
2023-06-07
[ [ "Ghosh", "Shinjini", "" ], [ "Anupam", "Sagnik", "" ] ]
While deep-learning models have been shown to perform well on image-to-text datasets, it is difficult to use them in practice for captioning images. This is because captions traditionally tend to be context-dependent and offer complementary information about an image, while models tend to produce descriptions that desc...
1910.07655
Saeid Asgari Taghanaki
Saeid Asgari Taghanaki, Kumar Abhishek, Joseph Paul Cohen, Julien Cohen-Adad, Ghassan Hamarneh
Deep Semantic Segmentation of Natural and Medical Images: A Review
45 pages, 16 figures. Accepted for publication in Springer Artificial Intelligence Review
null
null
null
cs.CV cs.LG eess.IV
http://creativecommons.org/licenses/by/4.0/
The semantic image segmentation task consists of classifying each pixel of an image into an instance, where each instance corresponds to a class. This task is a part of the concept of scene understanding or better explaining the global context of an image. In the medical image analysis domain, image segmentation can ...
[ { "created": "Wed, 16 Oct 2019 06:35:50 GMT", "version": "v1" }, { "created": "Sat, 2 Nov 2019 18:18:01 GMT", "version": "v2" }, { "created": "Wed, 3 Jun 2020 22:20:36 GMT", "version": "v3" }, { "created": "Sun, 31 Mar 2024 02:57:09 GMT", "version": "v4" } ]
2024-04-02
[ [ "Taghanaki", "Saeid Asgari", "" ], [ "Abhishek", "Kumar", "" ], [ "Cohen", "Joseph Paul", "" ], [ "Cohen-Adad", "Julien", "" ], [ "Hamarneh", "Ghassan", "" ] ]
The semantic image segmentation task consists of classifying each pixel of an image into an instance, where each instance corresponds to a class. This task is a part of the concept of scene understanding or better explaining the global context of an image. In the medical image analysis domain, image segmentation can be...
2010.11724
Yunchao Wei
Yunchao Wei, Shuai Zheng, Ming-Ming Cheng, Hang Zhao, Liwei Wang, Errui Ding, Yi Yang, Antonio Torralba, Ting Liu, Guolei Sun, Wenguan Wang, Luc Van Gool, Wonho Bae, Junhyug Noh, Jinhwan Seo, Gunhee Kim, Hao Zhao, Ming Lu, Anbang Yao, Yiwen Guo, Yurong Chen, Li Zhang, Chuangchuang Tan, Tao Ruan, Guanghua Gu, Sh...
LID 2020: The Learning from Imperfect Data Challenge Results
Summary of the 2nd Learning from Imperfect Data Workshop in conjunction with CVPR 2020
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Learning from imperfect data becomes an issue in many industrial applications after the research community has made profound progress in supervised learning from perfectly annotated datasets. The purpose of the Learning from Imperfect Data (LID) workshop is to inspire and facilitate the research in developing novel a...
[ { "created": "Sat, 17 Oct 2020 13:06:12 GMT", "version": "v1" } ]
2020-10-23
[ [ "Wei", "Yunchao", "" ], [ "Zheng", "Shuai", "" ], [ "Cheng", "Ming-Ming", "" ], [ "Zhao", "Hang", "" ], [ "Wang", "Liwei", "" ], [ "Ding", "Errui", "" ], [ "Yang", "Yi", "" ], [ "Torralba", "Ant...
Learning from imperfect data becomes an issue in many industrial applications after the research community has made profound progress in supervised learning from perfectly annotated datasets. The purpose of the Learning from Imperfect Data (LID) workshop is to inspire and facilitate the research in developing novel app...
2209.01391
Loc Hoang Tran
Loc H. Tran, Nguyen Trinh, Linh H. Tran
Hypergraph convolutional neural network-based clustering technique
null
null
null
null
cs.LG
http://creativecommons.org/publicdomain/zero/1.0/
This paper constitutes the novel hypergraph convolutional neural networkbased clustering technique. This technique is employed to solve the clustering problem for the Citeseer dataset and the Cora dataset. Each dataset contains the feature matrix and the incidence matrix of the hypergraph (i.e., constructed from the ...
[ { "created": "Sat, 3 Sep 2022 10:25:15 GMT", "version": "v1" } ]
2022-09-07
[ [ "Tran", "Loc H.", "" ], [ "Trinh", "Nguyen", "" ], [ "Tran", "Linh H.", "" ] ]
This paper constitutes the novel hypergraph convolutional neural networkbased clustering technique. This technique is employed to solve the clustering problem for the Citeseer dataset and the Cora dataset. Each dataset contains the feature matrix and the incidence matrix of the hypergraph (i.e., constructed from the fe...
1803.01390
Jelle Hellings
Jelle Hellings, Marc Gyssens, Yuqing Wu, Dirk Van Gucht, Jan Van den Bussche, Stijn Vansummeren, George H. L. Fletcher
Comparing Downward Fragments of the Relational Calculus with Transitive Closure on Trees
null
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Motivated by the continuing interest in the tree data model, we study the expressive power of downward navigational query languages on trees and chains. Basic navigational queries are built from the identity relation and edge relations using composition and union. We study the effects on relative expressiveness when ...
[ { "created": "Sun, 4 Mar 2018 17:38:51 GMT", "version": "v1" } ]
2018-03-06
[ [ "Hellings", "Jelle", "" ], [ "Gyssens", "Marc", "" ], [ "Wu", "Yuqing", "" ], [ "Van Gucht", "Dirk", "" ], [ "Bussche", "Jan Van den", "" ], [ "Vansummeren", "Stijn", "" ], [ "Fletcher", "George H. L.", "" ...
Motivated by the continuing interest in the tree data model, we study the expressive power of downward navigational query languages on trees and chains. Basic navigational queries are built from the identity relation and edge relations using composition and union. We study the effects on relative expressiveness when we...
1912.09040
Zichen Zhang
Zichen Zhang, Qingfeng Lan, Lei Ding, Yue Wang, Negar Hassanpour, Russell Greiner
Reducing Selection Bias in Counterfactual Reasoning for Individual Treatment Effects Estimation
NeurIPS 2019 Workshop on "Do the right thing": machine learning and causal inference for improved decision making
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Counterfactual reasoning is an important paradigm applicable in many fields, such as healthcare, economics, and education. In this work, we propose a novel method to address the issue of \textit{selection bias}. We learn two groups of latent random variables, where one group corresponds to variables that only cause s...
[ { "created": "Thu, 19 Dec 2019 07:10:00 GMT", "version": "v1" } ]
2019-12-20
[ [ "Zhang", "Zichen", "" ], [ "Lan", "Qingfeng", "" ], [ "Ding", "Lei", "" ], [ "Wang", "Yue", "" ], [ "Hassanpour", "Negar", "" ], [ "Greiner", "Russell", "" ] ]
Counterfactual reasoning is an important paradigm applicable in many fields, such as healthcare, economics, and education. In this work, we propose a novel method to address the issue of \textit{selection bias}. We learn two groups of latent random variables, where one group corresponds to variables that only cause sel...
2210.07246
Hongde Wu
Hongde Wu
Topics in Deep Learning and Optimization Algorithms for IoT Applications in Smart Transportation
The manuscript of thesis has been accepted and leads to the award of Master of Engineering in Dublin City University in September 2022
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Nowadays, the Internet of Things (IoT) has become one of the most important technologies which enables a variety of connected and intelligent applications in smart cities. The smart decision making process of IoT devices not only relies on the large volume of data collected from their sensors, but also depends on adv...
[ { "created": "Thu, 13 Oct 2022 11:45:30 GMT", "version": "v1" } ]
2022-10-17
[ [ "Wu", "Hongde", "" ] ]
Nowadays, the Internet of Things (IoT) has become one of the most important technologies which enables a variety of connected and intelligent applications in smart cities. The smart decision making process of IoT devices not only relies on the large volume of data collected from their sensors, but also depends on advan...
2006.11998
Xiaowei Wu
Xiaowei Wu, Min Qiu, Jinhong Yuan
Partially Information Coupled Duo-Binary Turbo Codes
Accepted at the ISIT 2020
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Partially information coupled turbo codes (PIC-TCs) is a class of spatially coupled turbo codes that can approach the BEC capacity while keeping the encoding and decoding architectures of the underlying component codes unchanged. However, PIC-TCs have significant rate loss compared to its component rate-1/3 turbo cod...
[ { "created": "Mon, 22 Jun 2020 04:03:52 GMT", "version": "v1" } ]
2020-06-23
[ [ "Wu", "Xiaowei", "" ], [ "Qiu", "Min", "" ], [ "Yuan", "Jinhong", "" ] ]
Partially information coupled turbo codes (PIC-TCs) is a class of spatially coupled turbo codes that can approach the BEC capacity while keeping the encoding and decoding architectures of the underlying component codes unchanged. However, PIC-TCs have significant rate loss compared to its component rate-1/3 turbo code,...
1808.08213
Arquimedes Canedo
Jiang Wan, Blake S. Pollard, Sujit Rokka Chhetri, Palash Goyal, Mohammad Abdullah Al Faruque, Arquimedes Canedo
Future Automation Engineering using Structural Graph Convolutional Neural Networks
ICCAD 2018
null
10.1145/3240765.3243477
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The digitalization of automation engineering generates large quantities of engineering data that is interlinked in knowledge graphs. Classifying and clustering subgraphs according to their functionality is useful to discover functionally equivalent engineering artifacts that exhibit different graph structures. This p...
[ { "created": "Fri, 24 Aug 2018 17:07:05 GMT", "version": "v1" } ]
2018-08-27
[ [ "Wan", "Jiang", "" ], [ "Pollard", "Blake S.", "" ], [ "Chhetri", "Sujit Rokka", "" ], [ "Goyal", "Palash", "" ], [ "Faruque", "Mohammad Abdullah Al", "" ], [ "Canedo", "Arquimedes", "" ] ]
The digitalization of automation engineering generates large quantities of engineering data that is interlinked in knowledge graphs. Classifying and clustering subgraphs according to their functionality is useful to discover functionally equivalent engineering artifacts that exhibit different graph structures. This pap...
2004.12822
Hippolyte Signargout
Sylvain Gravier (IF), Hippolyte Signargout (ENS Lyon), Souad Slimani
Optimal Adjacent Vertex-Distinguishing Edge-Colorings of Circulant Graphs
Editor-neutral version
null
null
null
cs.DM math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A $k$-proper edge-coloring of a graph G is called adjacent vertex-distinguishing if any two adjacent vertices are distinguished by the set of colors appearing in the edges incident to each vertex. The smallest value $k$ for which $G$ admits such coloring is denoted by $\chi'_a(G)$. We prove that $\chi'_a(G) = 2R + 1$...
[ { "created": "Mon, 27 Apr 2020 14:03:45 GMT", "version": "v1" }, { "created": "Thu, 7 May 2020 16:29:15 GMT", "version": "v2" }, { "created": "Fri, 12 Jun 2020 12:25:39 GMT", "version": "v3" }, { "created": "Tue, 4 Jan 2022 09:00:16 GMT", "version": "v4" } ]
2022-01-05
[ [ "Gravier", "Sylvain", "", "IF" ], [ "Signargout", "Hippolyte", "", "ENS Lyon" ], [ "Slimani", "Souad", "" ] ]
A $k$-proper edge-coloring of a graph G is called adjacent vertex-distinguishing if any two adjacent vertices are distinguished by the set of colors appearing in the edges incident to each vertex. The smallest value $k$ for which $G$ admits such coloring is denoted by $\chi'_a(G)$. We prove that $\chi'_a(G) = 2R + 1$ f...
2312.07245
Renyang Liu
Renyang Liu, Wei Zhou, Xin Jin, Song Gao, Yuanyu Wang, Ruxin Wang
DTA: Distribution Transform-based Attack for Query-Limited Scenario
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In generating adversarial examples, the conventional black-box attack methods rely on sufficient feedback from the to-be-attacked models by repeatedly querying until the attack is successful, which usually results in thousands of trials during an attack. This may be unacceptable in real applications since Machine Lea...
[ { "created": "Tue, 12 Dec 2023 13:21:03 GMT", "version": "v1" } ]
2023-12-13
[ [ "Liu", "Renyang", "" ], [ "Zhou", "Wei", "" ], [ "Jin", "Xin", "" ], [ "Gao", "Song", "" ], [ "Wang", "Yuanyu", "" ], [ "Wang", "Ruxin", "" ] ]
In generating adversarial examples, the conventional black-box attack methods rely on sufficient feedback from the to-be-attacked models by repeatedly querying until the attack is successful, which usually results in thousands of trials during an attack. This may be unacceptable in real applications since Machine Learn...
2108.09859
Hongyuan Zhan
Hongyuan Zhan and Kamesh Madduri and Venkataraman Shankar
Convex Latent Effect Logit Model via Sparse and Low-rank Decomposition
null
null
null
null
cs.LG stat.ME stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a convex formulation for learning logistic regression model (logit) with latent heterogeneous effect on sub-population. In transportation, logistic regression and its variants are often interpreted as discrete choice models under utility theory (McFadden, 2001). Two prominent applications of...
[ { "created": "Sun, 22 Aug 2021 22:23:39 GMT", "version": "v1" } ]
2021-08-24
[ [ "Zhan", "Hongyuan", "" ], [ "Madduri", "Kamesh", "" ], [ "Shankar", "Venkataraman", "" ] ]
In this paper, we propose a convex formulation for learning logistic regression model (logit) with latent heterogeneous effect on sub-population. In transportation, logistic regression and its variants are often interpreted as discrete choice models under utility theory (McFadden, 2001). Two prominent applications of l...
2212.09994
Bing Wang
Xinyu Pi, Bing Wang, Yan Gao, Jiaqi Guo, Zhoujun Li, Jian-Guang Lou
Towards Robustness of Text-to-SQL Models Against Natural and Realistic Adversarial Table Perturbation
Accepted by ACL 2022 (Oral)
null
null
null
cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
The robustness of Text-to-SQL parsers against adversarial perturbations plays a crucial role in delivering highly reliable applications. Previous studies along this line primarily focused on perturbations in the natural language question side, neglecting the variability of tables. Motivated by this, we propose the Ad...
[ { "created": "Tue, 20 Dec 2022 04:38:23 GMT", "version": "v1" } ]
2022-12-21
[ [ "Pi", "Xinyu", "" ], [ "Wang", "Bing", "" ], [ "Gao", "Yan", "" ], [ "Guo", "Jiaqi", "" ], [ "Li", "Zhoujun", "" ], [ "Lou", "Jian-Guang", "" ] ]
The robustness of Text-to-SQL parsers against adversarial perturbations plays a crucial role in delivering highly reliable applications. Previous studies along this line primarily focused on perturbations in the natural language question side, neglecting the variability of tables. Motivated by this, we propose the Adve...
2206.07434
Jinyi Wu
Jinyi Wu, Xun Gong, Zhemin Zhang
Self-Supervised Implicit Attention: Guided Attention by The Model Itself
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose Self-Supervised Implicit Attention (SSIA), a new approach that adaptively guides deep neural network models to gain attention by exploiting the properties of the models themselves. SSIA is a novel attention mechanism that does not require any extra parameters, computation, or memory access costs during inf...
[ { "created": "Wed, 15 Jun 2022 10:13:34 GMT", "version": "v1" }, { "created": "Thu, 21 Jul 2022 14:19:11 GMT", "version": "v2" } ]
2022-07-22
[ [ "Wu", "Jinyi", "" ], [ "Gong", "Xun", "" ], [ "Zhang", "Zhemin", "" ] ]
We propose Self-Supervised Implicit Attention (SSIA), a new approach that adaptively guides deep neural network models to gain attention by exploiting the properties of the models themselves. SSIA is a novel attention mechanism that does not require any extra parameters, computation, or memory access costs during infer...
2203.06615
Amit Tsvieli
Amit Tsvieli and Nir Weinberger
Learning Maximum Margin Channel Decoders
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The problem of learning a channel decoder is considered for two channel models. The first model is an additive noise channel whose noise distribution is unknown and nonparametric. The learner is provided with a fixed codebook and a dataset comprised of independent samples of the noise, and is required to select a pre...
[ { "created": "Sun, 13 Mar 2022 10:10:51 GMT", "version": "v1" }, { "created": "Wed, 15 Feb 2023 22:11:39 GMT", "version": "v2" } ]
2023-02-17
[ [ "Tsvieli", "Amit", "" ], [ "Weinberger", "Nir", "" ] ]
The problem of learning a channel decoder is considered for two channel models. The first model is an additive noise channel whose noise distribution is unknown and nonparametric. The learner is provided with a fixed codebook and a dataset comprised of independent samples of the noise, and is required to select a preci...
1707.01086
Jie Yang
Xinyang Feng, Jie Yang, Andrew F. Laine, and Elsa D. Angelini
Discriminative Localization in CNNs for Weakly-Supervised Segmentation of Pulmonary Nodules
null
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017
10.1007/978-3-319-66179-7_65
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Automated detection and segmentation of pulmonary nodules on lung computed tomography (CT) scans can facilitate early lung cancer diagnosis. Existing supervised approaches for automated nodule segmentation on CT scans require voxel-based annotations for training, which are labor- and time-consuming to obtain. In this...
[ { "created": "Tue, 4 Jul 2017 17:54:57 GMT", "version": "v1" }, { "created": "Thu, 22 Feb 2018 19:24:06 GMT", "version": "v2" } ]
2018-02-26
[ [ "Feng", "Xinyang", "" ], [ "Yang", "Jie", "" ], [ "Laine", "Andrew F.", "" ], [ "Angelini", "Elsa D.", "" ] ]
Automated detection and segmentation of pulmonary nodules on lung computed tomography (CT) scans can facilitate early lung cancer diagnosis. Existing supervised approaches for automated nodule segmentation on CT scans require voxel-based annotations for training, which are labor- and time-consuming to obtain. In this w...
1606.03966
Siddhartha Sen
Alekh Agarwal, Sarah Bird, Markus Cozowicz, Luong Hoang, John Langford, Stephen Lee, Jiaji Li, Dan Melamed, Gal Oshri, Oswaldo Ribas, Siddhartha Sen, Alex Slivkins
Making Contextual Decisions with Low Technical Debt
null
null
null
null
cs.LG cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Applications and systems are constantly faced with decisions that require picking from a set of actions based on contextual information. Reinforcement-based learning algorithms such as contextual bandits can be very effective in these settings, but applying them in practice is fraught with technical debt, and no gene...
[ { "created": "Mon, 13 Jun 2016 14:17:00 GMT", "version": "v1" }, { "created": "Tue, 9 May 2017 14:41:15 GMT", "version": "v2" } ]
2017-05-10
[ [ "Agarwal", "Alekh", "" ], [ "Bird", "Sarah", "" ], [ "Cozowicz", "Markus", "" ], [ "Hoang", "Luong", "" ], [ "Langford", "John", "" ], [ "Lee", "Stephen", "" ], [ "Li", "Jiaji", "" ], [ "Melamed", ...
Applications and systems are constantly faced with decisions that require picking from a set of actions based on contextual information. Reinforcement-based learning algorithms such as contextual bandits can be very effective in these settings, but applying them in practice is fraught with technical debt, and no genera...
1907.05007
Minchul Shin
Minchul Shin, Sanghyuk Park, Taeksoo Kim
Semi-supervised Feature-Level Attribute Manipulation for Fashion Image Retrieval
Accepted to BMVC 2019
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
With a growing demand for the search by image, many works have studied the task of fashion instance-level image retrieval (FIR). Furthermore, the recent works introduce a concept of fashion attribute manipulation (FAM) which manipulates a specific attribute (e.g color) of a fashion item while maintaining the rest of ...
[ { "created": "Thu, 11 Jul 2019 05:51:49 GMT", "version": "v1" } ]
2019-07-12
[ [ "Shin", "Minchul", "" ], [ "Park", "Sanghyuk", "" ], [ "Kim", "Taeksoo", "" ] ]
With a growing demand for the search by image, many works have studied the task of fashion instance-level image retrieval (FIR). Furthermore, the recent works introduce a concept of fashion attribute manipulation (FAM) which manipulates a specific attribute (e.g color) of a fashion item while maintaining the rest of th...
1907.13003
Lanlan Su
Lanlan Su, Mengmou Li, Vijay Gupta and Graziano Chesi
Distributed Resource Allocation over Time-varying Balanced Digraphs with Discrete-time Communication
12 pages, 7 figures
null
null
null
cs.MA cs.SY eess.SY math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work is concerned with the problem of distributed resource allocation in continuous-time setting but with discrete-time communication over infinitely jointly connected and balanced digraphs. We provide a passivity-based perspective for the continuous-time algorithm, based on which an intermittent communication s...
[ { "created": "Tue, 30 Jul 2019 15:12:28 GMT", "version": "v1" }, { "created": "Tue, 3 Mar 2020 17:13:07 GMT", "version": "v2" }, { "created": "Fri, 15 Jan 2021 15:42:09 GMT", "version": "v3" } ]
2021-01-18
[ [ "Su", "Lanlan", "" ], [ "Li", "Mengmou", "" ], [ "Gupta", "Vijay", "" ], [ "Chesi", "Graziano", "" ] ]
This work is concerned with the problem of distributed resource allocation in continuous-time setting but with discrete-time communication over infinitely jointly connected and balanced digraphs. We provide a passivity-based perspective for the continuous-time algorithm, based on which an intermittent communication sch...
1602.08207
Philip Schniter
Alyson K. Fletcher and Philip Schniter
Learning and Free Energies for Vector Approximate Message Passing
null
null
null
null
cs.IT math.IT stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Vector approximate message passing (VAMP) is a computationally simple approach to the recovery of a signal $\mathbf{x}$ from noisy linear measurements $\mathbf{y}=\mathbf{Ax}+\mathbf{w}$. Like the AMP proposed by Donoho, Maleki, and Montanari in 2009, VAMP is characterized by a rigorous state evolution (SE) that hold...
[ { "created": "Fri, 26 Feb 2016 06:06:13 GMT", "version": "v1" }, { "created": "Wed, 12 Oct 2016 06:37:00 GMT", "version": "v2" }, { "created": "Mon, 9 Jan 2017 17:54:12 GMT", "version": "v3" }, { "created": "Thu, 8 Mar 2018 15:55:46 GMT", "version": "v4" } ]
2018-03-09
[ [ "Fletcher", "Alyson K.", "" ], [ "Schniter", "Philip", "" ] ]
Vector approximate message passing (VAMP) is a computationally simple approach to the recovery of a signal $\mathbf{x}$ from noisy linear measurements $\mathbf{y}=\mathbf{Ax}+\mathbf{w}$. Like the AMP proposed by Donoho, Maleki, and Montanari in 2009, VAMP is characterized by a rigorous state evolution (SE) that holds ...
1905.02472
Ingo Van Duijn
Chen Avin, Ingo van Duijn, Stefan Schmid
Self-Adjusting Linear Networks
null
null
null
null
cs.DS cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Emerging networked systems become increasingly flexible and reconfigurable. This introduces an opportunity to adjust networked systems in a demand-aware manner, leveraging spatial and temporal locality in the workload for online optimizations. However, it also introduces a trade-off: while more frequent adjustments c...
[ { "created": "Tue, 7 May 2019 11:09:10 GMT", "version": "v1" } ]
2019-05-08
[ [ "Avin", "Chen", "" ], [ "van Duijn", "Ingo", "" ], [ "Schmid", "Stefan", "" ] ]
Emerging networked systems become increasingly flexible and reconfigurable. This introduces an opportunity to adjust networked systems in a demand-aware manner, leveraging spatial and temporal locality in the workload for online optimizations. However, it also introduces a trade-off: while more frequent adjustments can...
1912.12836
Maciej Paszynski
Maciej Paszynski and Leszek Siwik and Witold Dzwinel and Keshav Pingali
Supermodeling of tumor dynamics with parallel isogeometric analysis solver
32 pages, 22 figures
null
null
null
cs.CE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Supermodeling is a modern, model-ensembling paradigm that integrates several self-synchronized imperfect sub-models by controlling a few meta-parameters to generate more accurate predictions of complex systems' dynamics. Continual synchronization between sub-models allows for trajectory predictions with superior accu...
[ { "created": "Mon, 30 Dec 2019 07:38:58 GMT", "version": "v1" }, { "created": "Fri, 4 Sep 2020 09:18:26 GMT", "version": "v2" }, { "created": "Sun, 27 Dec 2020 19:58:13 GMT", "version": "v3" }, { "created": "Fri, 26 Feb 2021 11:03:44 GMT", "version": "v4" } ]
2021-03-01
[ [ "Paszynski", "Maciej", "" ], [ "Siwik", "Leszek", "" ], [ "Dzwinel", "Witold", "" ], [ "Pingali", "Keshav", "" ] ]
Supermodeling is a modern, model-ensembling paradigm that integrates several self-synchronized imperfect sub-models by controlling a few meta-parameters to generate more accurate predictions of complex systems' dynamics. Continual synchronization between sub-models allows for trajectory predictions with superior accura...
1001.2752
Charles Sauerbier
Charles Sauerbier
A Polynomial Diophantine Generator Function for Integer Residuals
7 pages, 0 figures
null
null
null
cs.DM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Two Diophantine equation generator function for integer residuals produced by integer division over closed intervals are presented. One each for the closed intervals [1,Floor(n^0.5)] and [Ceiling(n^0.5),n], respectively.
[ { "created": "Fri, 15 Jan 2010 19:04:54 GMT", "version": "v1" } ]
2010-01-18
[ [ "Sauerbier", "Charles", "" ] ]
Two Diophantine equation generator function for integer residuals produced by integer division over closed intervals are presented. One each for the closed intervals [1,Floor(n^0.5)] and [Ceiling(n^0.5),n], respectively.
2309.04422
Thomas Huang
Thomas E. Huang, Yifan Liu, Luc Van Gool, Fisher Yu
Video Task Decathlon: Unifying Image and Video Tasks in Autonomous Driving
ICCV 2023, project page at https://www.vis.xyz/pub/vtd
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Performing multiple heterogeneous visual tasks in dynamic scenes is a hallmark of human perception capability. Despite remarkable progress in image and video recognition via representation learning, current research still focuses on designing specialized networks for singular, homogeneous, or simple combination of ta...
[ { "created": "Fri, 8 Sep 2023 16:33:27 GMT", "version": "v1" }, { "created": "Sun, 26 Nov 2023 15:25:11 GMT", "version": "v2" } ]
2023-11-28
[ [ "Huang", "Thomas E.", "" ], [ "Liu", "Yifan", "" ], [ "Van Gool", "Luc", "" ], [ "Yu", "Fisher", "" ] ]
Performing multiple heterogeneous visual tasks in dynamic scenes is a hallmark of human perception capability. Despite remarkable progress in image and video recognition via representation learning, current research still focuses on designing specialized networks for singular, homogeneous, or simple combination of task...
2402.02980
Md Muzakkir Quamar Mr
Md Muzakkir Quamar and Ali Nasir
Review on Fault Diagnosis and Fault-Tolerant Control Scheme for Robotic Manipulators: Recent Advances in AI, Machine Learning, and Digital Twin
24 pages, 6 figures
null
null
null
cs.RO cs.LG cs.SY eess.SY
http://creativecommons.org/licenses/by/4.0/
This comprehensive review article delves into the intricate realm of fault-tolerant control (FTC) schemes tailored for robotic manipulators. Our exploration spans the historical evolution of FTC, tracing its development over time, and meticulously examines the recent breakthroughs fueled by the synergistic integratio...
[ { "created": "Mon, 5 Feb 2024 13:12:33 GMT", "version": "v1" } ]
2024-02-06
[ [ "Quamar", "Md Muzakkir", "" ], [ "Nasir", "Ali", "" ] ]
This comprehensive review article delves into the intricate realm of fault-tolerant control (FTC) schemes tailored for robotic manipulators. Our exploration spans the historical evolution of FTC, tracing its development over time, and meticulously examines the recent breakthroughs fueled by the synergistic integration ...
1907.00239
Dmitriy Zhuk
Dmitriy Zhuk and Barnaby Martin
QCSP monsters and the demise of the Chen Conjecture
Lemma 17 was retracted and the boundary between co-NP-complete and PSpace-complete has shifted
null
null
null
cs.CC cs.LO math.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We give a surprising classification for the computational complexity of the Quantified Constraint Satisfaction Problem over a constraint language $\Gamma$, QCSP$(\Gamma)$, where $\Gamma$ is a finite language over $3$ elements which contains all constants. In particular, such problems are either in P, NP-complete, co-...
[ { "created": "Sat, 29 Jun 2019 17:13:13 GMT", "version": "v1" }, { "created": "Sun, 4 Aug 2019 20:41:38 GMT", "version": "v2" }, { "created": "Sat, 2 Nov 2019 07:35:11 GMT", "version": "v3" }, { "created": "Wed, 27 Jul 2022 07:53:00 GMT", "version": "v4" } ]
2022-07-28
[ [ "Zhuk", "Dmitriy", "" ], [ "Martin", "Barnaby", "" ] ]
We give a surprising classification for the computational complexity of the Quantified Constraint Satisfaction Problem over a constraint language $\Gamma$, QCSP$(\Gamma)$, where $\Gamma$ is a finite language over $3$ elements which contains all constants. In particular, such problems are either in P, NP-complete, co-NP...
2310.07652
Lei Wang
Lei Wang, Songheng Zhang, Yun Wang, Ee-Peng Lim, Yong Wang
LLM4Vis: Explainable Visualization Recommendation using ChatGPT
EMNLP 2023 (Industry Track)
null
null
null
cs.HC cs.CL
http://creativecommons.org/licenses/by/4.0/
Data visualization is a powerful tool for exploring and communicating insights in various domains. To automate visualization choice for datasets, a task known as visualization recommendation has been proposed. Various machine-learning-based approaches have been developed for this purpose, but they often require a lar...
[ { "created": "Wed, 11 Oct 2023 16:51:46 GMT", "version": "v1" }, { "created": "Mon, 16 Oct 2023 03:34:47 GMT", "version": "v2" } ]
2023-10-17
[ [ "Wang", "Lei", "" ], [ "Zhang", "Songheng", "" ], [ "Wang", "Yun", "" ], [ "Lim", "Ee-Peng", "" ], [ "Wang", "Yong", "" ] ]
Data visualization is a powerful tool for exploring and communicating insights in various domains. To automate visualization choice for datasets, a task known as visualization recommendation has been proposed. Various machine-learning-based approaches have been developed for this purpose, but they often require a large...
1911.09796
Anum Ali
Anum Ali, Nuria Gonz\'alez-Prelcic, Robert W. Heath Jr., Amitava Ghosh
Leveraging Sensing at the Infrastructure for mmWave Communication
null
null
null
null
cs.IT eess.SP math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Vehicle-to-everything (V2X) communication in the mmWave band is one way to achieve high data-rates for applications like infotainment, cooperative perception, and augmented reality assisted driving etc. MmWave communication relies on large antennas arrays, and configuring these arrays poses high training overhead. In...
[ { "created": "Fri, 22 Nov 2019 00:35:46 GMT", "version": "v1" } ]
2019-11-25
[ [ "Ali", "Anum", "" ], [ "González-Prelcic", "Nuria", "" ], [ "Heath", "Robert W.", "Jr." ], [ "Ghosh", "Amitava", "" ] ]
Vehicle-to-everything (V2X) communication in the mmWave band is one way to achieve high data-rates for applications like infotainment, cooperative perception, and augmented reality assisted driving etc. MmWave communication relies on large antennas arrays, and configuring these arrays poses high training overhead. In t...
1812.01278
Dorien Herremans
Kin Wah Edward Lin, Balamurali B.T., Enyan Koh, Simon Lui, Dorien Herremans
Singing Voice Separation Using a Deep Convolutional Neural Network Trained by Ideal Binary Mask and Cross Entropy
In Press, Neural Computing and Applications, Springer. 2019
null
null
null
cs.SD cs.AI cs.LG eess.AS stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Separating a singing voice from its music accompaniment remains an important challenge in the field of music information retrieval. We present a unique neural network approach inspired by a technique that has revolutionized the field of vision: pixel-wise image classification, which we combine with cross entropy loss...
[ { "created": "Tue, 4 Dec 2018 08:47:41 GMT", "version": "v1" } ]
2018-12-05
[ [ "Lin", "Kin Wah Edward", "" ], [ "T.", "Balamurali B.", "" ], [ "Koh", "Enyan", "" ], [ "Lui", "Simon", "" ], [ "Herremans", "Dorien", "" ] ]
Separating a singing voice from its music accompaniment remains an important challenge in the field of music information retrieval. We present a unique neural network approach inspired by a technique that has revolutionized the field of vision: pixel-wise image classification, which we combine with cross entropy loss a...
0911.0105
Ian Pratt-Hartmann
Ian Pratt-Hartmann and Ivo D\"untsch
Functions Definable by Numerical Set-Expressions
null
Journal of Logic and Computation, 24(4), 2013, pp. 873-895
10.1093/logcom/exr050
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A "numerical set-expression" is a term specifying a cascade of arithmetic and logical operations to be performed on sets of non-negative integers. If these operations are confined to the usual Boolean operations together with the result of lifting addition to the level of sets, we speak of "additive circuits". If the...
[ { "created": "Sat, 31 Oct 2009 23:17:49 GMT", "version": "v1" } ]
2024-04-24
[ [ "Pratt-Hartmann", "Ian", "" ], [ "Düntsch", "Ivo", "" ] ]
A "numerical set-expression" is a term specifying a cascade of arithmetic and logical operations to be performed on sets of non-negative integers. If these operations are confined to the usual Boolean operations together with the result of lifting addition to the level of sets, we speak of "additive circuits". If they ...
2104.11280
Aliaksandr Siarohin
Aliaksandr Siarohin, Oliver J. Woodford, Jian Ren, Menglei Chai and Sergey Tulyakov
Motion Representations for Articulated Animation
null
CVPR 2021
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
We propose novel motion representations for animating articulated objects consisting of distinct parts. In a completely unsupervised manner, our method identifies object parts, tracks them in a driving video, and infers their motions by considering their principal axes. In contrast to the previous keypoint-based work...
[ { "created": "Thu, 22 Apr 2021 18:53:56 GMT", "version": "v1" } ]
2021-04-26
[ [ "Siarohin", "Aliaksandr", "" ], [ "Woodford", "Oliver J.", "" ], [ "Ren", "Jian", "" ], [ "Chai", "Menglei", "" ], [ "Tulyakov", "Sergey", "" ] ]
We propose novel motion representations for animating articulated objects consisting of distinct parts. In a completely unsupervised manner, our method identifies object parts, tracks them in a driving video, and infers their motions by considering their principal axes. In contrast to the previous keypoint-based works,...
1808.07962
Siyuan Qi
Siyuan Qi, Wenguan Wang, Baoxiong Jia, Jianbing Shen, Song-Chun Zhu
Learning Human-Object Interactions by Graph Parsing Neural Networks
This paper is published in ECCV 2018
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper addresses the task of detecting and recognizing human-object interactions (HOI) in images and videos. We introduce the Graph Parsing Neural Network (GPNN), a framework that incorporates structural knowledge while being differentiable end-to-end. For a given scene, GPNN infers a parse graph that includes i)...
[ { "created": "Thu, 23 Aug 2018 23:04:22 GMT", "version": "v1" } ]
2018-08-27
[ [ "Qi", "Siyuan", "" ], [ "Wang", "Wenguan", "" ], [ "Jia", "Baoxiong", "" ], [ "Shen", "Jianbing", "" ], [ "Zhu", "Song-Chun", "" ] ]
This paper addresses the task of detecting and recognizing human-object interactions (HOI) in images and videos. We introduce the Graph Parsing Neural Network (GPNN), a framework that incorporates structural knowledge while being differentiable end-to-end. For a given scene, GPNN infers a parse graph that includes i) t...
2002.03932
Wei-Cheng Chang
Wei-Cheng Chang, Felix X. Yu, Yin-Wen Chang, Yiming Yang, Sanjiv Kumar
Pre-training Tasks for Embedding-based Large-scale Retrieval
Accepted by ICLR 2020
null
null
null
cs.LG cs.CL cs.IR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the large-scale query-document retrieval problem: given a query (e.g., a question), return the set of relevant documents (e.g., paragraphs containing the answer) from a large document corpus. This problem is often solved in two steps. The retrieval phase first reduces the solution space, returning a subse...
[ { "created": "Mon, 10 Feb 2020 16:44:00 GMT", "version": "v1" } ]
2020-02-11
[ [ "Chang", "Wei-Cheng", "" ], [ "Yu", "Felix X.", "" ], [ "Chang", "Yin-Wen", "" ], [ "Yang", "Yiming", "" ], [ "Kumar", "Sanjiv", "" ] ]
We consider the large-scale query-document retrieval problem: given a query (e.g., a question), return the set of relevant documents (e.g., paragraphs containing the answer) from a large document corpus. This problem is often solved in two steps. The retrieval phase first reduces the solution space, returning a subset ...
2311.17847
Hesham Mostafa
Hesham Mostafa and Adam Grabowski and Md Asadullah Turja and Juan Cervino and Alejandro Ribeiro and Nageen Himayat
FastSample: Accelerating Distributed Graph Neural Network Training for Billion-Scale Graphs
null
null
null
null
cs.DC
http://creativecommons.org/licenses/by/4.0/
Training Graph Neural Networks(GNNs) on a large monolithic graph presents unique challenges as the graph cannot fit within a single machine and it cannot be decomposed into smaller disconnected components. Distributed sampling-based training distributes the graph across multiple machines and trains the GNN on small p...
[ { "created": "Wed, 29 Nov 2023 17:49:48 GMT", "version": "v1" } ]
2023-11-30
[ [ "Mostafa", "Hesham", "" ], [ "Grabowski", "Adam", "" ], [ "Turja", "Md Asadullah", "" ], [ "Cervino", "Juan", "" ], [ "Ribeiro", "Alejandro", "" ], [ "Himayat", "Nageen", "" ] ]
Training Graph Neural Networks(GNNs) on a large monolithic graph presents unique challenges as the graph cannot fit within a single machine and it cannot be decomposed into smaller disconnected components. Distributed sampling-based training distributes the graph across multiple machines and trains the GNN on small par...
2005.02725
Lu\'is M. S. Russo
Lu\'is M. S. Russo, Alexandre P. Francisco, Tatiana Rocher
Incremental Multiple Longest Common Sub-Sequences
The work reported in this article was supported by national funds through Funda\c{c}\~ao para a Ci\^encia e Tecnologia (FCT) through projects NGPHYLO PTDC/CCI-BIO/29676/2017 and UID/CEC/50021/2019. Funded in part by European Union Horizon 2020 research and innovation programme under the Marie Sk{\l}odowska-Curi...
null
null
null
cs.DS cs.CG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of updating the information about multiple longest common sub-sequences. This kind of sub-sequences is used to highlight information that is shared across several information sequences, therefore it is extensively used namely in bioinformatics and computational genomics. In this paper we propo...
[ { "created": "Wed, 6 May 2020 10:52:18 GMT", "version": "v1" } ]
2020-05-07
[ [ "Russo", "Luís M. S.", "" ], [ "Francisco", "Alexandre P.", "" ], [ "Rocher", "Tatiana", "" ] ]
We consider the problem of updating the information about multiple longest common sub-sequences. This kind of sub-sequences is used to highlight information that is shared across several information sequences, therefore it is extensively used namely in bioinformatics and computational genomics. In this paper we propose...
2310.10946
Yasunari Hikima
Yasunari Hikima
Multi-point Feedback of Bandit Convex Optimization with Hard Constraints
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
This paper studies bandit convex optimization with constraints, where the learner aims to generate a sequence of decisions under partial information of loss functions such that the cumulative loss is reduced as well as the cumulative constraint violation is simultaneously reduced. We adopt the cumulative \textit{hard...
[ { "created": "Tue, 17 Oct 2023 02:43:22 GMT", "version": "v1" } ]
2023-10-18
[ [ "Hikima", "Yasunari", "" ] ]
This paper studies bandit convex optimization with constraints, where the learner aims to generate a sequence of decisions under partial information of loss functions such that the cumulative loss is reduced as well as the cumulative constraint violation is simultaneously reduced. We adopt the cumulative \textit{hard} ...
2405.20624
Qianyu Huang
Qianyu Huang and Tongfang Zhao
Leveraging Large Language Models for Entity Matching
null
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Entity matching (EM) is a critical task in data integration, aiming to identify records across different datasets that refer to the same real-world entities. Traditional methods often rely on manually engineered features and rule-based systems, which struggle with diverse and unstructured data. The emergence of Large...
[ { "created": "Fri, 31 May 2024 05:22:07 GMT", "version": "v1" } ]
2024-06-03
[ [ "Huang", "Qianyu", "" ], [ "Zhao", "Tongfang", "" ] ]
Entity matching (EM) is a critical task in data integration, aiming to identify records across different datasets that refer to the same real-world entities. Traditional methods often rely on manually engineered features and rule-based systems, which struggle with diverse and unstructured data. The emergence of Large L...
1901.10263
Simon Razniewski
Cuong Xuan Chu, Simon Razniewski, Gerhard Weikum
TiFi: Taxonomy Induction for Fictional Domains [Extended version]
Extended version of The Web Conference 2019 paper
null
null
null
cs.CL cs.AI cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Taxonomies are important building blocks of structured knowledge bases, and their construction from text sources and Wikipedia has received much attention. In this paper we focus on the construction of taxonomies for fictional domains, using noisy category systems from fan wikis or text extraction as input. Such fict...
[ { "created": "Tue, 29 Jan 2019 13:07:13 GMT", "version": "v1" } ]
2019-01-30
[ [ "Chu", "Cuong Xuan", "" ], [ "Razniewski", "Simon", "" ], [ "Weikum", "Gerhard", "" ] ]
Taxonomies are important building blocks of structured knowledge bases, and their construction from text sources and Wikipedia has received much attention. In this paper we focus on the construction of taxonomies for fictional domains, using noisy category systems from fan wikis or text extraction as input. Such fictio...
1909.01051
Fabio Maria Carlucci
Vasco Lopes and Fabio Maria Carlucci and Pedro M Esperan\c{c}a and Marco Singh and Victor Gabillon and Antoine Yang and Hang Xu and Zewei Chen and Jun Wang
MANAS: Multi-Agent Neural Architecture Search
null
null
null
null
cs.CV cs.LG cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Neural Architecture Search (NAS) problem is typically formulated as a graph search problem where the goal is to learn the optimal operations over edges in order to maximise a graph-level global objective. Due to the large architecture parameter space, efficiency is a key bottleneck preventing NAS from its practic...
[ { "created": "Tue, 3 Sep 2019 10:36:37 GMT", "version": "v1" }, { "created": "Thu, 5 Sep 2019 12:36:50 GMT", "version": "v2" }, { "created": "Tue, 25 Feb 2020 11:37:52 GMT", "version": "v3" }, { "created": "Thu, 12 Jan 2023 11:00:56 GMT", "version": "v4" } ]
2023-01-13
[ [ "Lopes", "Vasco", "" ], [ "Carlucci", "Fabio Maria", "" ], [ "Esperança", "Pedro M", "" ], [ "Singh", "Marco", "" ], [ "Gabillon", "Victor", "" ], [ "Yang", "Antoine", "" ], [ "Xu", "Hang", "" ], [ ...
The Neural Architecture Search (NAS) problem is typically formulated as a graph search problem where the goal is to learn the optimal operations over edges in order to maximise a graph-level global objective. Due to the large architecture parameter space, efficiency is a key bottleneck preventing NAS from its practical...
2207.01934
Bjorge Meulemeester
Bjorge Meulemeester, David Martens
How sustainable is "common" data science in terms of power consumption?
conference paper, working paper, under review, 9 pages, 4 figures
null
null
null
cs.CY
http://creativecommons.org/licenses/by/4.0/
Continuous developments in data science have brought forth an exponential increase in complexity of machine learning models. Additionally, data scientists have become ubiquitous in the private market, academic environments and even as a hobby. All of these trends are on a steady rise, and are associated with an incre...
[ { "created": "Tue, 5 Jul 2022 10:15:22 GMT", "version": "v1" } ]
2022-07-25
[ [ "Meulemeester", "Bjorge", "" ], [ "Martens", "David", "" ] ]
Continuous developments in data science have brought forth an exponential increase in complexity of machine learning models. Additionally, data scientists have become ubiquitous in the private market, academic environments and even as a hobby. All of these trends are on a steady rise, and are associated with an increas...
2107.03011
Yifu Wang
Yifu Wang, Jiaqi Yang, Xin Peng, Peng Wu, Ling Gao, Kun Huang, Jiaben Chen, Laurent Kneip
Visual Odometry with an Event Camera Using Continuous Ray Warping and Volumetric Contrast Maximization
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a new solution to tracking and mapping with an event camera. The motion of the camera contains both rotation and translation, and the displacements happen in an arbitrarily structured environment. As a result, the image matching may no longer be represented by a low-dimensional homographic warping, thus co...
[ { "created": "Wed, 7 Jul 2021 04:32:57 GMT", "version": "v1" } ]
2021-07-08
[ [ "Wang", "Yifu", "" ], [ "Yang", "Jiaqi", "" ], [ "Peng", "Xin", "" ], [ "Wu", "Peng", "" ], [ "Gao", "Ling", "" ], [ "Huang", "Kun", "" ], [ "Chen", "Jiaben", "" ], [ "Kneip", "Laurent", "" ...
We present a new solution to tracking and mapping with an event camera. The motion of the camera contains both rotation and translation, and the displacements happen in an arbitrarily structured environment. As a result, the image matching may no longer be represented by a low-dimensional homographic warping, thus comp...
2107.14585
Alexander Genser Ag
Alexander Genser and Anastasios Kouvelas
Dynamic optimal congestion pricing in multi-region urban networks by application of a Multi-Layer-Neural network
null
Transportation Research Part C: Emerging Technologies, Volume 134, 2022
10.1016/j.trc.2021.103485
null
cs.RO cs.CE
http://creativecommons.org/licenses/by-nc-nd/4.0/
Traffic management by applying congestion pricing is a measure for mitigating congestion in protected city corridors. As a promising tool, pricing improves the level of service in a network and reduces travel delays. However, real-world implementations are restricted to static pricing, i.e., the price is fixed and no...
[ { "created": "Tue, 27 Jul 2021 14:16:59 GMT", "version": "v1" } ]
2021-12-14
[ [ "Genser", "Alexander", "" ], [ "Kouvelas", "Anastasios", "" ] ]
Traffic management by applying congestion pricing is a measure for mitigating congestion in protected city corridors. As a promising tool, pricing improves the level of service in a network and reduces travel delays. However, real-world implementations are restricted to static pricing, i.e., the price is fixed and not ...
2207.11912
Qinghua Liu
Qinghua Liu, Yuxiang Jiang
Dive into Big Model Training
Report
null
null
null
cs.LG cs.DC
http://creativecommons.org/licenses/by/4.0/
The increasing scale of model size and continuous improvement of performance herald the arrival of the Big Model era. In this report, we explore what and how the big model training works by diving into training objectives and training methodologies. Specifically,training objectives describe how to leverage web-scale ...
[ { "created": "Mon, 25 Jul 2022 05:38:39 GMT", "version": "v1" } ]
2022-07-26
[ [ "Liu", "Qinghua", "" ], [ "Jiang", "Yuxiang", "" ] ]
The increasing scale of model size and continuous improvement of performance herald the arrival of the Big Model era. In this report, we explore what and how the big model training works by diving into training objectives and training methodologies. Specifically,training objectives describe how to leverage web-scale da...
2310.18887
Yihong Sun
Yihong Sun, Bharath Hariharan
Dynamo-Depth: Fixing Unsupervised Depth Estimation for Dynamical Scenes
NeurIPS 2023
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Unsupervised monocular depth estimation techniques have demonstrated encouraging results but typically assume that the scene is static. These techniques suffer when trained on dynamical scenes, where apparent object motion can equally be explained by hypothesizing the object's independent motion, or by altering its d...
[ { "created": "Sun, 29 Oct 2023 03:24:16 GMT", "version": "v1" } ]
2023-10-31
[ [ "Sun", "Yihong", "" ], [ "Hariharan", "Bharath", "" ] ]
Unsupervised monocular depth estimation techniques have demonstrated encouraging results but typically assume that the scene is static. These techniques suffer when trained on dynamical scenes, where apparent object motion can equally be explained by hypothesizing the object's independent motion, or by altering its dep...
2203.12001
Shutian Liu
Shutian Liu, Quanyan Zhu
Mitigating Moral Hazard in Cyber Insurance Using Risk Preference Design
6 pages, 1 figure
null
null
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cyber insurance is a risk-sharing mechanism that can improve cyber-physical systems (CPS) security and resilience. The risk preference of the insured plays an important role in cyber insurance markets. With the advances in information technologies, it can be reshaped through nudging, marketing, or other types of info...
[ { "created": "Tue, 22 Mar 2022 19:03:49 GMT", "version": "v1" } ]
2022-03-24
[ [ "Liu", "Shutian", "" ], [ "Zhu", "Quanyan", "" ] ]
Cyber insurance is a risk-sharing mechanism that can improve cyber-physical systems (CPS) security and resilience. The risk preference of the insured plays an important role in cyber insurance markets. With the advances in information technologies, it can be reshaped through nudging, marketing, or other types of inform...
2109.07249
Ioannis Fudos
Anastasia Moutafidou, Vasileios Toulatzis and Ioannis Fudos
Temporal Parameter-free Deep Skinning of Animated Meshes
CGI 2021, LNCS Proceedings, to appear. For video and presentation and other info please see http://www.cgrg.cs.uoi.gr/single-publication?ID=48
Advances in Computer Graphics. CGI 2021. Lecture Notes in Computer Science, vol 13002. Springer, Cham
10.1007/978-3-030-89029-2_1
null
cs.GR cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In computer graphics, animation compression is essential for efficient storage, streaming and reproduction of animated meshes. Previous work has presented efficient techniques for compression by deriving skinning transformations and weights using clustering of vertices based on geometric features of vertices over tim...
[ { "created": "Wed, 15 Sep 2021 12:38:44 GMT", "version": "v1" } ]
2023-11-09
[ [ "Moutafidou", "Anastasia", "" ], [ "Toulatzis", "Vasileios", "" ], [ "Fudos", "Ioannis", "" ] ]
In computer graphics, animation compression is essential for efficient storage, streaming and reproduction of animated meshes. Previous work has presented efficient techniques for compression by deriving skinning transformations and weights using clustering of vertices based on geometric features of vertices over time....
0708.0598
Matthew McCool Dr
Matthew McCool
An Application of Chromatic Prototypes
This paper has been withdrawn
null
null
null
cs.HC cs.MM
null
This paper has been withdrawn.
[ { "created": "Sat, 4 Aug 2007 02:38:19 GMT", "version": "v1" }, { "created": "Sun, 3 Feb 2008 19:41:44 GMT", "version": "v2" } ]
2008-02-03
[ [ "McCool", "Matthew", "" ] ]
This paper has been withdrawn.
2310.11926
Andreas Bj\"orklund
Andreas Bj\"orklund and Petteri Kaski
The Asymptotic Rank Conjecture and the Set Cover Conjecture are not Both True
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Strassen's asymptotic rank conjecture [Progr. Math. 120 (1994)] claims a strong submultiplicative upper bound on the rank of a three-tensor obtained as an iterated Kronecker product of a constant-size base tensor. The conjecture, if true, most notably would put square matrix multiplication in quadratic time. We note ...
[ { "created": "Wed, 18 Oct 2023 12:42:05 GMT", "version": "v1" } ]
2023-10-19
[ [ "Björklund", "Andreas", "" ], [ "Kaski", "Petteri", "" ] ]
Strassen's asymptotic rank conjecture [Progr. Math. 120 (1994)] claims a strong submultiplicative upper bound on the rank of a three-tensor obtained as an iterated Kronecker product of a constant-size base tensor. The conjecture, if true, most notably would put square matrix multiplication in quadratic time. We note he...
2407.07577
Yatai Ji
Yatai Ji, Shilong Zhang, Jie Wu, Peize Sun, Weifeng Chen, Xuefeng Xiao, Sidi Yang, Yujiu Yang, Ping Luo
IDA-VLM: Towards Movie Understanding via ID-Aware Large Vision-Language Model
null
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The rapid advancement of Large Vision-Language models (LVLMs) has demonstrated a spectrum of emergent capabilities. Nevertheless, current models only focus on the visual content of a single scenario, while their ability to associate instances across different scenes has not yet been explored, which is essential for u...
[ { "created": "Wed, 10 Jul 2024 12:11:59 GMT", "version": "v1" } ]
2024-07-11
[ [ "Ji", "Yatai", "" ], [ "Zhang", "Shilong", "" ], [ "Wu", "Jie", "" ], [ "Sun", "Peize", "" ], [ "Chen", "Weifeng", "" ], [ "Xiao", "Xuefeng", "" ], [ "Yang", "Sidi", "" ], [ "Yang", "Yujiu", ...
The rapid advancement of Large Vision-Language models (LVLMs) has demonstrated a spectrum of emergent capabilities. Nevertheless, current models only focus on the visual content of a single scenario, while their ability to associate instances across different scenes has not yet been explored, which is essential for und...
2407.20410
Farzaneh Derakhshan
Farzaneh Derakhshan, Stephanie Balzer, Yue Yao
Regrading Policies for Flexible Information Flow Control in Session-Typed Concurrency
Technical report of ECOOP24 paper
null
null
null
cs.PL cs.LO
http://creativecommons.org/licenses/by/4.0/
Noninterference guarantees that an attacker cannot infer secrets by interacting with a program. Information flow control (IFC) type systems assert noninterference by tracking the level of information learned (pc) and disallowing communication to entities of lesser or unrelated level than the pc. Control flow construc...
[ { "created": "Mon, 29 Jul 2024 20:40:16 GMT", "version": "v1" } ]
2024-07-31
[ [ "Derakhshan", "Farzaneh", "" ], [ "Balzer", "Stephanie", "" ], [ "Yao", "Yue", "" ] ]
Noninterference guarantees that an attacker cannot infer secrets by interacting with a program. Information flow control (IFC) type systems assert noninterference by tracking the level of information learned (pc) and disallowing communication to entities of lesser or unrelated level than the pc. Control flow constructs...
1506.08839
Julian McAuley
Julian McAuley and Rahul Pandey and Jure Leskovec
Inferring Networks of Substitutable and Complementary Products
12 pages, 6 figures
null
null
null
cs.SI cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In a modern recommender system, it is important to understand how products relate to each other. For example, while a user is looking for mobile phones, it might make sense to recommend other phones, but once they buy a phone, we might instead want to recommend batteries, cases, or chargers. These two types of recomm...
[ { "created": "Mon, 29 Jun 2015 20:06:28 GMT", "version": "v1" } ]
2015-07-01
[ [ "McAuley", "Julian", "" ], [ "Pandey", "Rahul", "" ], [ "Leskovec", "Jure", "" ] ]
In a modern recommender system, it is important to understand how products relate to each other. For example, while a user is looking for mobile phones, it might make sense to recommend other phones, but once they buy a phone, we might instead want to recommend batteries, cases, or chargers. These two types of recommen...
2111.08227
Yuxuan Liang
Yuxuan Liang, Chuang Niu, Chen Wei, Shenghan Ren, Wenxiang Cong and Ge Wang
Phase function estimation from a diffuse optical image via deep learning
16 pages, 8 figures
null
10.1088/1361-6560/ac5b21
null
cs.LG physics.med-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The phase function is a key element of a light propagation model for Monte Carlo (MC) simulation, which is usually fitted with an analytic function with associated parameters. In recent years, machine learning methods were reported to estimate the parameters of the phase function of a particular form such as the Heny...
[ { "created": "Tue, 16 Nov 2021 04:59:25 GMT", "version": "v1" } ]
2022-04-06
[ [ "Liang", "Yuxuan", "" ], [ "Niu", "Chuang", "" ], [ "Wei", "Chen", "" ], [ "Ren", "Shenghan", "" ], [ "Cong", "Wenxiang", "" ], [ "Wang", "Ge", "" ] ]
The phase function is a key element of a light propagation model for Monte Carlo (MC) simulation, which is usually fitted with an analytic function with associated parameters. In recent years, machine learning methods were reported to estimate the parameters of the phase function of a particular form such as the Henyey...
2009.01441
Zhe Lin
Zhe Lin, Sharad Sinha, Hao Liang, Liang Feng, Wei Zhang
Scalable Light-Weight Integration of FPGA Based Accelerators with Chip Multi-Processors
published as a journal (TMSCS) paper in 2018
null
10.1109/TMSCS.2017.2754378
null
cs.AR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Modern multicore systems are migrating from homogeneous systems to heterogeneous systems with accelerator-based computing in order to overcome the barriers of performance and power walls. In this trend, FPGA-based accelerators are becoming increasingly attractive, due to their excellent flexibility and low design cos...
[ { "created": "Thu, 3 Sep 2020 04:02:47 GMT", "version": "v1" } ]
2020-09-04
[ [ "Lin", "Zhe", "" ], [ "Sinha", "Sharad", "" ], [ "Liang", "Hao", "" ], [ "Feng", "Liang", "" ], [ "Zhang", "Wei", "" ] ]
Modern multicore systems are migrating from homogeneous systems to heterogeneous systems with accelerator-based computing in order to overcome the barriers of performance and power walls. In this trend, FPGA-based accelerators are becoming increasingly attractive, due to their excellent flexibility and low design cost....
2008.00143
Lele Liao
Lele Liao, Zhaoyi Gu, Jing Lu
Efficient Independent Vector Extraction of Dominant Target Speech
null
null
null
null
cs.SD eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The complete decomposition performed by blind source separation is computationally demanding and superfluous when only the speech of one specific target speaker is desired. In this paper, we propose a computationally efficient blind speech extraction method based on a proper modification of the commonly utilized inde...
[ { "created": "Sat, 1 Aug 2020 01:23:36 GMT", "version": "v1" } ]
2020-08-04
[ [ "Liao", "Lele", "" ], [ "Gu", "Zhaoyi", "" ], [ "Lu", "Jing", "" ] ]
The complete decomposition performed by blind source separation is computationally demanding and superfluous when only the speech of one specific target speaker is desired. In this paper, we propose a computationally efficient blind speech extraction method based on a proper modification of the commonly utilized indepe...
2312.07886
Wei Gao
Kai Huang, Boyuan Yang and Wei Gao
Modality Plug-and-Play: Elastic Modality Adaptation in Multimodal LLMs for Embodied AI
null
null
null
null
cs.AI cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
Large Language Models (LLMs) are capable of reasoning over diverse input data modalities through pre-trained encoders. However, the growing diversity of input data modalities prevents incorporating all modalities into LLMs, especially when LLMs are deployed on resource-constrained edge devices for embodied AI applica...
[ { "created": "Wed, 13 Dec 2023 04:08:59 GMT", "version": "v1" } ]
2023-12-14
[ [ "Huang", "Kai", "" ], [ "Yang", "Boyuan", "" ], [ "Gao", "Wei", "" ] ]
Large Language Models (LLMs) are capable of reasoning over diverse input data modalities through pre-trained encoders. However, the growing diversity of input data modalities prevents incorporating all modalities into LLMs, especially when LLMs are deployed on resource-constrained edge devices for embodied AI applicati...
2308.03524
Jovan Komatovic
Pierre Civit, Seth Gilbert, Rachid Guerraoui, Jovan Komatovic, Manuel Vidigueira
Strong Byzantine Agreement with Adaptive Word Complexity
null
null
null
null
cs.DC
http://creativecommons.org/licenses/by/4.0/
The strong Byzantine agreement (SBA) problem is defined among n processes, out of which t < n can be faulty and behave arbitrarily. SBA allows correct (non-faulty) processes to agree on a common value. Moreover, if all correct processes have proposed the same value, only that value can be agreed upon. It has been kno...
[ { "created": "Mon, 7 Aug 2023 12:20:32 GMT", "version": "v1" } ]
2023-08-08
[ [ "Civit", "Pierre", "" ], [ "Gilbert", "Seth", "" ], [ "Guerraoui", "Rachid", "" ], [ "Komatovic", "Jovan", "" ], [ "Vidigueira", "Manuel", "" ] ]
The strong Byzantine agreement (SBA) problem is defined among n processes, out of which t < n can be faulty and behave arbitrarily. SBA allows correct (non-faulty) processes to agree on a common value. Moreover, if all correct processes have proposed the same value, only that value can be agreed upon. It has been known...
2405.08967
Jesus Garcia Fernandez
Jesus Garcia Fernandez, Sander Keemink, Marcel van Gerven
Gradient-Free Training of Recurrent Neural Networks using Random Perturbations
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Recurrent neural networks (RNNs) hold immense potential for computations due to their Turing completeness and sequential processing capabilities, yet existing methods for their training encounter efficiency challenges. Backpropagation through time (BPTT), the prevailing method, extends the backpropagation (BP) algori...
[ { "created": "Tue, 14 May 2024 21:15:29 GMT", "version": "v1" }, { "created": "Fri, 24 May 2024 12:00:40 GMT", "version": "v2" } ]
2024-05-27
[ [ "Fernandez", "Jesus Garcia", "" ], [ "Keemink", "Sander", "" ], [ "van Gerven", "Marcel", "" ] ]
Recurrent neural networks (RNNs) hold immense potential for computations due to their Turing completeness and sequential processing capabilities, yet existing methods for their training encounter efficiency challenges. Backpropagation through time (BPTT), the prevailing method, extends the backpropagation (BP) algorith...
2109.12457
Kaize Ding
Kaize Ding, Dingcheng Li, Alexander Hanbo Li, Xing Fan, Chenlei Guo, Yang Liu and Huan Liu
Learning to Selectively Learn for Weakly-supervised Paraphrase Generation
Accepted by EMNLP 2021 (long)
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Paraphrase generation is a longstanding NLP task that has diverse applications for downstream NLP tasks. However, the effectiveness of existing efforts predominantly relies on large amounts of golden labeled data. Though unsupervised endeavors have been proposed to address this issue, they may fail to generate meanin...
[ { "created": "Sat, 25 Sep 2021 23:31:13 GMT", "version": "v1" } ]
2021-09-28
[ [ "Ding", "Kaize", "" ], [ "Li", "Dingcheng", "" ], [ "Li", "Alexander Hanbo", "" ], [ "Fan", "Xing", "" ], [ "Guo", "Chenlei", "" ], [ "Liu", "Yang", "" ], [ "Liu", "Huan", "" ] ]
Paraphrase generation is a longstanding NLP task that has diverse applications for downstream NLP tasks. However, the effectiveness of existing efforts predominantly relies on large amounts of golden labeled data. Though unsupervised endeavors have been proposed to address this issue, they may fail to generate meaningf...
2007.02277
Javed Iqbal
Javed Iqbal and Mohsen Ali
Weakly Supervised Domain Adaptation for Built-up Region Segmentation in Aerial and Satellite Imagery
Accepted at ISPRS Journal of Photogrammetry and Remote Sensing
null
null
null
cs.CV eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes a novel domain adaptation algorithm to handle the challenges posed by the satellite and aerial imagery, and demonstrates its effectiveness on the built-up region segmentation problem. Built-up area estimation is an important component in understanding the human impact on the environment, the effec...
[ { "created": "Sun, 5 Jul 2020 10:05:01 GMT", "version": "v1" } ]
2020-07-07
[ [ "Iqbal", "Javed", "" ], [ "Ali", "Mohsen", "" ] ]
This paper proposes a novel domain adaptation algorithm to handle the challenges posed by the satellite and aerial imagery, and demonstrates its effectiveness on the built-up region segmentation problem. Built-up area estimation is an important component in understanding the human impact on the environment, the effect ...
1611.01754
Nhien-An Le-Khac
Pieter Van Vliet and M-T. Kechadi and Nhien-An Le-Khac
Forensics in Industrial Control System: A Case Study
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Industrial Control Systems (ICS) are used worldwide in critical infrastructures. An ICS system can be a single embedded system working stand-alone for controlling a simple process or ICS can also be a very complex Distributed Control System (DCS) connected to Supervisory Control And Data Acquisition (SCADA) system(s)...
[ { "created": "Sun, 6 Nov 2016 10:46:28 GMT", "version": "v1" } ]
2016-11-08
[ [ "Van Vliet", "Pieter", "" ], [ "Kechadi", "M-T.", "" ], [ "Le-Khac", "Nhien-An", "" ] ]
Industrial Control Systems (ICS) are used worldwide in critical infrastructures. An ICS system can be a single embedded system working stand-alone for controlling a simple process or ICS can also be a very complex Distributed Control System (DCS) connected to Supervisory Control And Data Acquisition (SCADA) system(s) i...
2403.08209
Hideo Bannai
Hideo Bannai, Mitsuru Funakoshi, Diptarama Hendrian, Myuji Matsuda, Simon J. Puglisi
Height-bounded Lempel-Ziv encodings
abstract shortened to fit arxiv requirements
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce height-bounded LZ encodings (LZHB), a new family of compressed representations that are variants of Lempel-Ziv parsings with a focus on bounding the worst-case access time to arbitrary positions in the text directly via the compressed representation. An LZ-like encoding is a partitioning of the string in...
[ { "created": "Wed, 13 Mar 2024 03:11:50 GMT", "version": "v1" }, { "created": "Thu, 25 Apr 2024 06:16:48 GMT", "version": "v2" } ]
2024-04-26
[ [ "Bannai", "Hideo", "" ], [ "Funakoshi", "Mitsuru", "" ], [ "Hendrian", "Diptarama", "" ], [ "Matsuda", "Myuji", "" ], [ "Puglisi", "Simon J.", "" ] ]
We introduce height-bounded LZ encodings (LZHB), a new family of compressed representations that are variants of Lempel-Ziv parsings with a focus on bounding the worst-case access time to arbitrary positions in the text directly via the compressed representation. An LZ-like encoding is a partitioning of the string into...
2306.15661
Navindu Leelarathna
Navindu Leelarathna, Andrei Margeloiu, Mateja Jamnik, Nikola Simidjievski
Enhancing Representation Learning on High-Dimensional, Small-Size Tabular Data: A Divide and Conquer Method with Ensembled VAEs
null
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Variational Autoencoders and their many variants have displayed impressive ability to perform dimensionality reduction, often achieving state-of-the-art performance. Many current methods however, struggle to learn good representations in High Dimensional, Low Sample Size (HDLSS) tasks, which is an inherently challeng...
[ { "created": "Tue, 27 Jun 2023 17:55:31 GMT", "version": "v1" } ]
2023-06-28
[ [ "Leelarathna", "Navindu", "" ], [ "Margeloiu", "Andrei", "" ], [ "Jamnik", "Mateja", "" ], [ "Simidjievski", "Nikola", "" ] ]
Variational Autoencoders and their many variants have displayed impressive ability to perform dimensionality reduction, often achieving state-of-the-art performance. Many current methods however, struggle to learn good representations in High Dimensional, Low Sample Size (HDLSS) tasks, which is an inherently challengin...
2010.03484
Richard Harang
Younghoo Lee, Joshua Saxe, Richard Harang
CATBERT: Context-Aware Tiny BERT for Detecting Social Engineering Emails
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Targeted phishing emails are on the rise and facilitate the theft of billions of dollars from organizations a year. While malicious signals from attached files or malicious URLs in emails can be detected by conventional malware signatures or machine learning technologies, it is challenging to identify hand-crafted so...
[ { "created": "Wed, 7 Oct 2020 15:40:36 GMT", "version": "v1" } ]
2020-10-08
[ [ "Lee", "Younghoo", "" ], [ "Saxe", "Joshua", "" ], [ "Harang", "Richard", "" ] ]
Targeted phishing emails are on the rise and facilitate the theft of billions of dollars from organizations a year. While malicious signals from attached files or malicious URLs in emails can be detected by conventional malware signatures or machine learning technologies, it is challenging to identify hand-crafted soci...
2304.00685
Jingyi Zhang
Jingyi Zhang, Jiaxing Huang, Sheng Jin and Shijian Lu
Vision-Language Models for Vision Tasks: A Survey
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Most visual recognition studies rely heavily on crowd-labelled data in deep neural networks (DNNs) training, and they usually train a DNN for each single visual recognition task, leading to a laborious and time-consuming visual recognition paradigm. To address the two challenges, Vision-Language Models (VLMs) have be...
[ { "created": "Mon, 3 Apr 2023 02:17:05 GMT", "version": "v1" }, { "created": "Fri, 16 Feb 2024 10:28:12 GMT", "version": "v2" } ]
2024-02-19
[ [ "Zhang", "Jingyi", "" ], [ "Huang", "Jiaxing", "" ], [ "Jin", "Sheng", "" ], [ "Lu", "Shijian", "" ] ]
Most visual recognition studies rely heavily on crowd-labelled data in deep neural networks (DNNs) training, and they usually train a DNN for each single visual recognition task, leading to a laborious and time-consuming visual recognition paradigm. To address the two challenges, Vision-Language Models (VLMs) have been...
2103.05214
Xinwen Liu
Xinwen Liu, Jing Wang, Feng Liu, and S.Kevin Zhou
Universal Undersampled MRI Reconstruction
null
null
null
null
cs.CV eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep neural networks have been extensively studied for undersampled MRI reconstruction. While achieving state-of-the-art performance, they are trained and deployed specifically for one anatomy with limited generalization ability to another anatomy. Rather than building multiple models, a universal model that reconstr...
[ { "created": "Tue, 9 Mar 2021 04:25:22 GMT", "version": "v1" } ]
2021-03-10
[ [ "Liu", "Xinwen", "" ], [ "Wang", "Jing", "" ], [ "Liu", "Feng", "" ], [ "Zhou", "S. Kevin", "" ] ]
Deep neural networks have been extensively studied for undersampled MRI reconstruction. While achieving state-of-the-art performance, they are trained and deployed specifically for one anatomy with limited generalization ability to another anatomy. Rather than building multiple models, a universal model that reconstruc...
1705.06628
Youngjun Cho
Youngjun Cho, Simon J. Julier, Nicolai Marquardt and Nadia Bianchi-Berthouze
Robust tracking of respiratory rate in high-dynamic range scenes using mobile thermal imaging
Vol. 8, No. 10, 1 Oct 2017, Biomedical Optics Express 4480 - Full abstract can be found in this journal article (due to limited word counts of 'arXiv abstract')
Biomedical Optics Express, 2017
10.1364/BOE.8.004480
null
cs.CV physics.med-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The ability to monitor respiratory rate is extremely important for medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake every day activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts o...
[ { "created": "Mon, 8 May 2017 17:49:03 GMT", "version": "v1" }, { "created": "Wed, 20 Sep 2017 21:06:05 GMT", "version": "v2" } ]
2017-09-22
[ [ "Cho", "Youngjun", "" ], [ "Julier", "Simon J.", "" ], [ "Marquardt", "Nicolai", "" ], [ "Bianchi-Berthouze", "Nadia", "" ] ]
The ability to monitor respiratory rate is extremely important for medical treatment, healthcare and fitness sectors. In many situations, mobile methods, which allow users to undertake every day activities, are required. However, current monitoring systems can be obtrusive, requiring users to wear respiration belts or ...
2302.05166
Marco Alfano
Marco Alfano, Viviana Bastidas, Paul Heynen, Markus Helfert
An Assessment Methodology and Instrument for Cybersecurity: The Ireland Use Case
52 pages, 3 figures, IVI White Paper
null
null
null
cs.CR
http://creativecommons.org/licenses/by-nc-sa/4.0/
Governments around the world are required to strengthen their national cybersecurity capabilities to respond effectively to the growing, changing, and sophisticated cyber threats and attacks, thus protecting society and the way of life as a whole. Responsible government institutions need to revise, evaluate, and bols...
[ { "created": "Fri, 10 Feb 2023 10:47:29 GMT", "version": "v1" } ]
2023-02-13
[ [ "Alfano", "Marco", "" ], [ "Bastidas", "Viviana", "" ], [ "Heynen", "Paul", "" ], [ "Helfert", "Markus", "" ] ]
Governments around the world are required to strengthen their national cybersecurity capabilities to respond effectively to the growing, changing, and sophisticated cyber threats and attacks, thus protecting society and the way of life as a whole. Responsible government institutions need to revise, evaluate, and bolste...
2201.11324
Haidong Li
Haidong Li, Anzhi Sheng, Yijie Peng, Long Wang
Efficient Distributed Learning in Stochastic Non-cooperative Games without Information Exchange
null
null
null
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, we study stochastic non-cooperative games, where only noisy black-box function evaluations are available to estimate the cost function for each player. Since each player's cost function depends on both its own decision variables and its rivals' decision variables, local information needs to be exchanged...
[ { "created": "Thu, 27 Jan 2022 04:55:13 GMT", "version": "v1" }, { "created": "Wed, 16 Feb 2022 06:15:22 GMT", "version": "v2" } ]
2022-02-17
[ [ "Li", "Haidong", "" ], [ "Sheng", "Anzhi", "" ], [ "Peng", "Yijie", "" ], [ "Wang", "Long", "" ] ]
In this work, we study stochastic non-cooperative games, where only noisy black-box function evaluations are available to estimate the cost function for each player. Since each player's cost function depends on both its own decision variables and its rivals' decision variables, local information needs to be exchanged t...
1510.06486
Rajkumar Buyya
Rajkumar Buyya, Kotagiri Ramamohanarao, Chris Leckie, Rodrigo N. Calheiros, Amir Vahid Dastjerdi, and Steve Versteeg
Big Data Analytics-Enhanced Cloud Computing: Challenges, Architectural Elements, and Future Directions
10 pages, 2 figures, conference paper in Proceedings of the 21st IEEE International Conference on Parallel and Distributed Systems (ICPADS 2015, IEEE Press, USA), Melbourne, Australia, December 14-17, 2015
null
10.1109/ICPADS.2015.18
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The emergence of cloud computing has made dynamic provisioning of elastic capacity to applications on-demand. Cloud data centers contain thousands of physical servers hosting orders of magnitude more virtual machines that can be allocated on demand to users in a pay-as-you-go model. However, not all systems are able ...
[ { "created": "Thu, 22 Oct 2015 04:07:55 GMT", "version": "v1" } ]
2016-11-17
[ [ "Buyya", "Rajkumar", "" ], [ "Ramamohanarao", "Kotagiri", "" ], [ "Leckie", "Chris", "" ], [ "Calheiros", "Rodrigo N.", "" ], [ "Dastjerdi", "Amir Vahid", "" ], [ "Versteeg", "Steve", "" ] ]
The emergence of cloud computing has made dynamic provisioning of elastic capacity to applications on-demand. Cloud data centers contain thousands of physical servers hosting orders of magnitude more virtual machines that can be allocated on demand to users in a pay-as-you-go model. However, not all systems are able to...
1703.06368
Alexander J. Summers
Alexander J. Summers and Peter M\"uller
Automating Deductive Verification for Weak-Memory Programs
Extended version of TACAS 2018 publication
null
null
null
cs.PL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Writing correct programs for weak memory models such as the C11 memory model is challenging because of the weak consistency guarantees these models provide. The first program logics for the verification of such programs have recently been proposed, but their usage has been limited thus far to manual proofs. Automatin...
[ { "created": "Sat, 18 Mar 2017 23:51:15 GMT", "version": "v1" }, { "created": "Mon, 19 Feb 2018 18:46:30 GMT", "version": "v2" } ]
2018-02-20
[ [ "Summers", "Alexander J.", "" ], [ "Müller", "Peter", "" ] ]
Writing correct programs for weak memory models such as the C11 memory model is challenging because of the weak consistency guarantees these models provide. The first program logics for the verification of such programs have recently been proposed, but their usage has been limited thus far to manual proofs. Automating ...
2407.02361
Hozaifa Kassab
Hozaifa Kassab, Mohamed Bahaa and Ali Hamdi
GCF: Graph Convolutional Networks for Facial Expression Recognition
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by-sa/4.0/
Facial Expression Recognition (FER) is vital for understanding interpersonal communication. However, existing classification methods often face challenges such as vulnerability to noise, imbalanced datasets, overfitting, and generalization issues. In this paper, we propose GCF, a novel approach that utilizes Graph Co...
[ { "created": "Tue, 2 Jul 2024 15:27:33 GMT", "version": "v1" } ]
2024-07-03
[ [ "Kassab", "Hozaifa", "" ], [ "Bahaa", "Mohamed", "" ], [ "Hamdi", "Ali", "" ] ]
Facial Expression Recognition (FER) is vital for understanding interpersonal communication. However, existing classification methods often face challenges such as vulnerability to noise, imbalanced datasets, overfitting, and generalization issues. In this paper, we propose GCF, a novel approach that utilizes Graph Conv...
2103.07011
Liang Qiu
Liang Qiu, Yizhou Zhao, Yuan Liang, Pan Lu, Weiyan Shi, Zhou Yu, Song-Chun Zhu
Towards Socially Intelligent Agents with Mental State Transition and Human Utility
Long paper accepted by SIGDIAL 2022
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Building a socially intelligent agent involves many challenges. One of which is to track the agent's mental state transition and teach the agent to make decisions guided by its value like a human. Towards this end, we propose to incorporate mental state simulation and value modeling into dialogue agents. First, we bu...
[ { "created": "Fri, 12 Mar 2021 00:06:51 GMT", "version": "v1" }, { "created": "Fri, 22 Jul 2022 17:28:53 GMT", "version": "v2" } ]
2022-07-25
[ [ "Qiu", "Liang", "" ], [ "Zhao", "Yizhou", "" ], [ "Liang", "Yuan", "" ], [ "Lu", "Pan", "" ], [ "Shi", "Weiyan", "" ], [ "Yu", "Zhou", "" ], [ "Zhu", "Song-Chun", "" ] ]
Building a socially intelligent agent involves many challenges. One of which is to track the agent's mental state transition and teach the agent to make decisions guided by its value like a human. Towards this end, we propose to incorporate mental state simulation and value modeling into dialogue agents. First, we buil...
2201.05910
Samaa Elnagar
Samaa Elnagar, Victoria Yoon and Manoj A.Thomas
An Automatic Ontology Generation Framework with An Organizational Perspective
Proceedings of the 53rd Hawaii International Conference on System Sciences | 2020
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
Ontologies have been known for their semantic representation of knowledge. ontologies cannot automatically evolve to reflect updates that occur in respective domains. To address this limitation, researchers have called for automatic ontology generation from unstructured text corpus. Unfortunately, systems that aim to...
[ { "created": "Sat, 15 Jan 2022 18:54:22 GMT", "version": "v1" } ]
2022-01-19
[ [ "Elnagar", "Samaa", "" ], [ "Yoon", "Victoria", "" ], [ "Thomas", "Manoj A.", "" ] ]
Ontologies have been known for their semantic representation of knowledge. ontologies cannot automatically evolve to reflect updates that occur in respective domains. To address this limitation, researchers have called for automatic ontology generation from unstructured text corpus. Unfortunately, systems that aim to g...
2112.03257
Alexander Li
Alexander C. Li, Deepak Pathak
Functional Regularization for Reinforcement Learning via Learned Fourier Features
Accepted at NeurIPS 2021. Website at https://alexanderli.com/learned-fourier-features
null
null
null
cs.LG cs.AI cs.CV cs.NE cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a simple architecture for deep reinforcement learning by embedding inputs into a learned Fourier basis and show that it improves the sample efficiency of both state-based and image-based RL. We perform infinite-width analysis of our architecture using the Neural Tangent Kernel and theoretically show that t...
[ { "created": "Mon, 6 Dec 2021 18:59:52 GMT", "version": "v1" } ]
2021-12-07
[ [ "Li", "Alexander C.", "" ], [ "Pathak", "Deepak", "" ] ]
We propose a simple architecture for deep reinforcement learning by embedding inputs into a learned Fourier basis and show that it improves the sample efficiency of both state-based and image-based RL. We perform infinite-width analysis of our architecture using the Neural Tangent Kernel and theoretically show that tun...
2109.07348
Evangelia Gogoulou
Evangelia Gogoulou, Ariel Ekgren, Tim Isbister, Magnus Sahlgren
Cross-lingual Transfer of Monolingual Models
Accepted to LREC 2022
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent studies in zero-shot cross-lingual learning using multilingual models have falsified the previous hypothesis that shared vocabulary and joint pre-training are the keys to cross-lingual generalization. Inspired by this advancement, we introduce a cross-lingual transfer method for monolingual models based on dom...
[ { "created": "Wed, 15 Sep 2021 15:00:53 GMT", "version": "v1" }, { "created": "Thu, 19 May 2022 15:02:20 GMT", "version": "v2" } ]
2022-05-20
[ [ "Gogoulou", "Evangelia", "" ], [ "Ekgren", "Ariel", "" ], [ "Isbister", "Tim", "" ], [ "Sahlgren", "Magnus", "" ] ]
Recent studies in zero-shot cross-lingual learning using multilingual models have falsified the previous hypothesis that shared vocabulary and joint pre-training are the keys to cross-lingual generalization. Inspired by this advancement, we introduce a cross-lingual transfer method for monolingual models based on domai...
1807.02684
Nabil Ibtehaz
Nabil Ibtehaz, M. Saifur Rahman, M. Sohel Rahman
VFPred: A Fusion of Signal Processing and Machine Learning techniques in Detecting Ventricular Fibrillation from ECG Signals
null
null
10.1016/j.bspc.2018.12.016
null
cs.LG eess.SP stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Ventricular Fibrillation (VF), one of the most dangerous arrhythmias, is responsible for sudden cardiac arrests. Thus, various algorithms have been developed to predict VF from Electrocardiogram (ECG), which is a binary classification problem. In the literature, we find a number of algorithms based on signal processi...
[ { "created": "Sat, 7 Jul 2018 16:09:40 GMT", "version": "v1" }, { "created": "Tue, 24 Jul 2018 11:48:41 GMT", "version": "v2" }, { "created": "Thu, 15 Nov 2018 19:04:22 GMT", "version": "v3" } ]
2019-03-13
[ [ "Ibtehaz", "Nabil", "" ], [ "Rahman", "M. Saifur", "" ], [ "Rahman", "M. Sohel", "" ] ]
Ventricular Fibrillation (VF), one of the most dangerous arrhythmias, is responsible for sudden cardiac arrests. Thus, various algorithms have been developed to predict VF from Electrocardiogram (ECG), which is a binary classification problem. In the literature, we find a number of algorithms based on signal processing...
2203.14031
Daniele Pannone
Danilo Avola, Luigi Cinque, Alessio Fagioli, Gian Luca Foresti, Marco Raoul Marini, Alessio Mecca, Daniele Pannone
Medicinal Boxes Recognition on a Deep Transfer Learning Augmented Reality Mobile Application
12 pages, 7 figures
null
null
null
cs.CV
http://creativecommons.org/licenses/by-sa/4.0/
Taking medicines is a fundamental aspect to cure illnesses. However, studies have shown that it can be hard for patients to remember the correct posology. More aggravating, a wrong dosage generally causes the disease to worsen. Although, all relevant instructions for a medicine are summarized in the corresponding pat...
[ { "created": "Sat, 26 Mar 2022 09:21:56 GMT", "version": "v1" } ]
2022-03-29
[ [ "Avola", "Danilo", "" ], [ "Cinque", "Luigi", "" ], [ "Fagioli", "Alessio", "" ], [ "Foresti", "Gian Luca", "" ], [ "Marini", "Marco Raoul", "" ], [ "Mecca", "Alessio", "" ], [ "Pannone", "Daniele", "" ] ...
Taking medicines is a fundamental aspect to cure illnesses. However, studies have shown that it can be hard for patients to remember the correct posology. More aggravating, a wrong dosage generally causes the disease to worsen. Although, all relevant instructions for a medicine are summarized in the corresponding patie...