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2206.05897
Lin Tian
Lin Tian, Hastings Greer, Fran\c{c}ois-Xavier Vialard, Roland Kwitt, Ra\'ul San Jos\'e Est\'epar, Richard Jarrett Rushmore, Nikolaos Makris, Sylvain Bouix, Marc Niethammer
$\texttt{GradICON}$: Approximate Diffeomorphisms via Gradient Inverse Consistency
29 pages, 16 figures, CVPR 2023
null
null
null
cs.CV eess.IV
http://creativecommons.org/licenses/by-nc-nd/4.0/
We present an approach to learning regular spatial transformations between image pairs in the context of medical image registration. Contrary to optimization-based registration techniques and many modern learning-based methods, we do not directly penalize transformation irregularities but instead promote transformati...
[ { "created": "Mon, 13 Jun 2022 04:03:49 GMT", "version": "v1" }, { "created": "Thu, 1 Dec 2022 19:56:37 GMT", "version": "v2" }, { "created": "Tue, 4 Apr 2023 05:44:39 GMT", "version": "v3" }, { "created": "Tue, 10 Oct 2023 03:42:57 GMT", "version": "v4" } ]
2023-10-11
[ [ "Tian", "Lin", "" ], [ "Greer", "Hastings", "" ], [ "Vialard", "François-Xavier", "" ], [ "Kwitt", "Roland", "" ], [ "Estépar", "Raúl San José", "" ], [ "Rushmore", "Richard Jarrett", "" ], [ "Makris", "Nikolao...
We present an approach to learning regular spatial transformations between image pairs in the context of medical image registration. Contrary to optimization-based registration techniques and many modern learning-based methods, we do not directly penalize transformation irregularities but instead promote transformation...
2311.01717
Zherong Pan
Chen Liang, Xifeng Gao, Kui Wu, Zherong Pan
Second-Order Convergent Collision-Constrained Optimization-Based Planner
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Finding robot poses and trajectories represents a foundational aspect of robot motion planning. Despite decades of research, efficiently and robustly addressing these challenges is still difficult. Existing approaches are often plagued by various limitations, such as intricate geometric approximations, violations of ...
[ { "created": "Fri, 3 Nov 2023 05:21:03 GMT", "version": "v1" } ]
2023-11-06
[ [ "Liang", "Chen", "" ], [ "Gao", "Xifeng", "" ], [ "Wu", "Kui", "" ], [ "Pan", "Zherong", "" ] ]
Finding robot poses and trajectories represents a foundational aspect of robot motion planning. Despite decades of research, efficiently and robustly addressing these challenges is still difficult. Existing approaches are often plagued by various limitations, such as intricate geometric approximations, violations of co...
2309.05133
David Heath
David Heath
Parallel RAM from Cyclic Circuits
null
null
null
null
cs.DS cs.CC
http://creativecommons.org/licenses/by/4.0/
Known simulations of random access machines (RAMs) or parallel RAMs (PRAMs) by Boolean circuits incur significant polynomial blowup, due to the need to repeatedly simulate accesses to a large main memory. Consider a single modification to Boolean circuits that removes the restriction that circuit graphs are acyclic...
[ { "created": "Sun, 10 Sep 2023 20:53:18 GMT", "version": "v1" }, { "created": "Mon, 16 Oct 2023 16:39:37 GMT", "version": "v2" }, { "created": "Fri, 27 Oct 2023 05:04:51 GMT", "version": "v3" } ]
2023-10-30
[ [ "Heath", "David", "" ] ]
Known simulations of random access machines (RAMs) or parallel RAMs (PRAMs) by Boolean circuits incur significant polynomial blowup, due to the need to repeatedly simulate accesses to a large main memory. Consider a single modification to Boolean circuits that removes the restriction that circuit graphs are acyclic. We...
1804.09194
Martin R\"unz
Martin R\"unz, Maud Buffier, Lourdes Agapito
MaskFusion: Real-Time Recognition, Tracking and Reconstruction of Multiple Moving Objects
Presented at IEEE International Symposium on Mixed and Augmented Reality (ISMAR) 2018
null
null
null
cs.CV cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present MaskFusion, a real-time, object-aware, semantic and dynamic RGB-D SLAM system that goes beyond traditional systems which output a purely geometric map of a static scene. MaskFusion recognizes, segments and assigns semantic class labels to different objects in the scene, while tracking and reconstructing th...
[ { "created": "Tue, 24 Apr 2018 18:15:15 GMT", "version": "v1" }, { "created": "Mon, 22 Oct 2018 17:47:27 GMT", "version": "v2" } ]
2018-10-23
[ [ "Rünz", "Martin", "" ], [ "Buffier", "Maud", "" ], [ "Agapito", "Lourdes", "" ] ]
We present MaskFusion, a real-time, object-aware, semantic and dynamic RGB-D SLAM system that goes beyond traditional systems which output a purely geometric map of a static scene. MaskFusion recognizes, segments and assigns semantic class labels to different objects in the scene, while tracking and reconstructing them...
2408.06872
Mike Perkins
Mike Perkins (1), Jasper Roe (2) ((1) British University Vietnam, (2) James Cook University Singapore)
Generative AI Tools in Academic Research: Applications and Implications for Qualitative and Quantitative Research Methodologies
null
null
null
null
cs.HC cs.AI
http://creativecommons.org/licenses/by-sa/4.0/
This study examines the impact of Generative Artificial Intelligence (GenAI) on academic research, focusing on its application to qualitative and quantitative data analysis. As GenAI tools evolve rapidly, they offer new possibilities for enhancing research productivity and democratising complex analytical processes. ...
[ { "created": "Tue, 13 Aug 2024 13:10:03 GMT", "version": "v1" } ]
2024-08-14
[ [ "Perkins", "Mike", "" ], [ "Roe", "Jasper", "" ] ]
This study examines the impact of Generative Artificial Intelligence (GenAI) on academic research, focusing on its application to qualitative and quantitative data analysis. As GenAI tools evolve rapidly, they offer new possibilities for enhancing research productivity and democratising complex analytical processes. Ho...
2310.18011
Kathleen Gregory
Kathleen Gregory, Laura Koesten, Regina Schuster, Torsten M\"oller, Sarah Davies
Data journeys in popular science: Producing climate change and COVID-19 data visualizations at Scientific American
44 pages, 4 figures, 3 boxes
null
10.1162/99608f92.141c99cf
null
cs.DL cs.HC physics.pop-ph
http://creativecommons.org/licenses/by/4.0/
Vast amounts of (open) data are increasingly used to make arguments about crisis topics such as climate change and global pandemics. Data visualizations are central to bringing these viewpoints to broader publics. However, visualizations often conceal the many contexts involved in their production, ranging from decis...
[ { "created": "Fri, 27 Oct 2023 09:39:06 GMT", "version": "v1" }, { "created": "Tue, 26 Mar 2024 08:01:34 GMT", "version": "v2" }, { "created": "Wed, 27 Mar 2024 08:13:14 GMT", "version": "v3" } ]
2024-03-28
[ [ "Gregory", "Kathleen", "" ], [ "Koesten", "Laura", "" ], [ "Schuster", "Regina", "" ], [ "Möller", "Torsten", "" ], [ "Davies", "Sarah", "" ] ]
Vast amounts of (open) data are increasingly used to make arguments about crisis topics such as climate change and global pandemics. Data visualizations are central to bringing these viewpoints to broader publics. However, visualizations often conceal the many contexts involved in their production, ranging from decisio...
1209.4420
Chao Wang
Lan-Ting LI
An Efficient Color Face Verification Based on 2-Directional 2-Dimensional Feature Extraction
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A novel and uniform framework for face verification is presented in this paper. First of all, a 2-directional 2-dimensional feature extraction method is adopted to extract client-specific template - 2D discrimant projection matrix. Then the face skin color information is utilized as an additive feature to enhance dec...
[ { "created": "Thu, 20 Sep 2012 04:20:40 GMT", "version": "v1" } ]
2012-09-21
[ [ "LI", "Lan-Ting", "" ] ]
A novel and uniform framework for face verification is presented in this paper. First of all, a 2-directional 2-dimensional feature extraction method is adopted to extract client-specific template - 2D discrimant projection matrix. Then the face skin color information is utilized as an additive feature to enhance decis...
2101.05623
David Pardo
M. Shahriari, A. Hazra, D. Pardo
Design of borehole resistivity measurement acquisition systems using deep learning
null
null
null
null
cs.LG cs.NA eess.SP math.NA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Borehole resistivity measurements recorded with logging-while-drilling (LWD) instruments are widely used for characterizing the earth's subsurface properties. They facilitate the extraction of natural resources such as oil and gas. LWD instruments require real-time inversions of electromagnetic measurements to estima...
[ { "created": "Tue, 12 Jan 2021 12:49:44 GMT", "version": "v1" } ]
2021-01-15
[ [ "Shahriari", "M.", "" ], [ "Hazra", "A.", "" ], [ "Pardo", "D.", "" ] ]
Borehole resistivity measurements recorded with logging-while-drilling (LWD) instruments are widely used for characterizing the earth's subsurface properties. They facilitate the extraction of natural resources such as oil and gas. LWD instruments require real-time inversions of electromagnetic measurements to estimate...
1604.05603
Wolfgang Dvo\v{r}\'ak
Wolfgang Dvo\v{r}\'ak and Monika Henzinger
Online Ad Assignment with an Ad Exchange
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Ad exchanges are becoming an increasingly popular way to sell advertisement slots on the internet. An ad exchange is basically a spot market for ad impressions. A publisher who has already signed contracts reserving advertisement impressions on his pages can choose between assigning a new ad impression for a new page...
[ { "created": "Tue, 19 Apr 2016 14:44:55 GMT", "version": "v1" } ]
2016-04-20
[ [ "Dvořák", "Wolfgang", "" ], [ "Henzinger", "Monika", "" ] ]
Ad exchanges are becoming an increasingly popular way to sell advertisement slots on the internet. An ad exchange is basically a spot market for ad impressions. A publisher who has already signed contracts reserving advertisement impressions on his pages can choose between assigning a new ad impression for a new page v...
1808.09408
Maximin Coavoux
Maximin Coavoux, Shashi Narayan, Shay B. Cohen
Privacy-preserving Neural Representations of Text
EMNLP 2018
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This article deals with adversarial attacks towards deep learning systems for Natural Language Processing (NLP), in the context of privacy protection. We study a specific type of attack: an attacker eavesdrops on the hidden representations of a neural text classifier and tries to recover information about the input t...
[ { "created": "Tue, 28 Aug 2018 16:57:37 GMT", "version": "v1" } ]
2018-08-29
[ [ "Coavoux", "Maximin", "" ], [ "Narayan", "Shashi", "" ], [ "Cohen", "Shay B.", "" ] ]
This article deals with adversarial attacks towards deep learning systems for Natural Language Processing (NLP), in the context of privacy protection. We study a specific type of attack: an attacker eavesdrops on the hidden representations of a neural text classifier and tries to recover information about the input tex...
2307.05735
Germ\'an Abrevaya
Germ\'an Abrevaya, Mahta Ramezanian-Panahi, Jean-Christophe Gagnon-Audet, Pablo Polosecki, Irina Rish, Silvina Ponce Dawson, Guillermo Cecchi, Guillaume Dumas
Effective Latent Differential Equation Models via Attention and Multiple Shooting
null
null
null
null
cs.LG nlin.CD physics.data-an physics.med-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Scientific Machine Learning (SciML) is a burgeoning field that synergistically combines domain-aware and interpretable models with agnostic machine learning techniques. In this work, we introduce GOKU-UI, an evolution of the SciML generative model GOKU-nets. GOKU-UI not only broadens the original model's spectrum to ...
[ { "created": "Tue, 11 Jul 2023 19:03:17 GMT", "version": "v1" }, { "created": "Wed, 6 Sep 2023 13:23:39 GMT", "version": "v2" }, { "created": "Thu, 14 Sep 2023 16:10:39 GMT", "version": "v3" } ]
2023-09-15
[ [ "Abrevaya", "Germán", "" ], [ "Ramezanian-Panahi", "Mahta", "" ], [ "Gagnon-Audet", "Jean-Christophe", "" ], [ "Polosecki", "Pablo", "" ], [ "Rish", "Irina", "" ], [ "Dawson", "Silvina Ponce", "" ], [ "Cecchi", ...
Scientific Machine Learning (SciML) is a burgeoning field that synergistically combines domain-aware and interpretable models with agnostic machine learning techniques. In this work, we introduce GOKU-UI, an evolution of the SciML generative model GOKU-nets. GOKU-UI not only broadens the original model's spectrum to in...
2303.15676
Niluthpol Chowdhury Mithun
Niluthpol Chowdhury Mithun, Kshitij Minhas, Han-Pang Chiu, Taragay Oskiper, Mikhail Sizintsev, Supun Samarasekera, Rakesh Kumar
Cross-View Visual Geo-Localization for Outdoor Augmented Reality
IEEE VR 2023
null
10.1109/VR55154.2023.00064
null
cs.CV cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Precise estimation of global orientation and location is critical to ensure a compelling outdoor Augmented Reality (AR) experience. We address the problem of geo-pose estimation by cross-view matching of query ground images to a geo-referenced aerial satellite image database. Recently, neural network-based methods ha...
[ { "created": "Tue, 28 Mar 2023 01:58:03 GMT", "version": "v1" } ]
2023-03-30
[ [ "Mithun", "Niluthpol Chowdhury", "" ], [ "Minhas", "Kshitij", "" ], [ "Chiu", "Han-Pang", "" ], [ "Oskiper", "Taragay", "" ], [ "Sizintsev", "Mikhail", "" ], [ "Samarasekera", "Supun", "" ], [ "Kumar", "Rakesh"...
Precise estimation of global orientation and location is critical to ensure a compelling outdoor Augmented Reality (AR) experience. We address the problem of geo-pose estimation by cross-view matching of query ground images to a geo-referenced aerial satellite image database. Recently, neural network-based methods have...
2306.07643
Grischa Liebel
Grischa Liebel and Steinunn Gr\'oa Sigur{\dh}ard\'ottir
Economical Accommodations for Neurodivergent Students in Software Engineering Education: Experiences from an Intervention in Four Undergraduate Courses
null
null
null
null
cs.SE
http://creativecommons.org/licenses/by/4.0/
Neurodiversity is an umbrella term that describes variation in brain function among individuals, including conditions such as Attention deficit hyperactivity disorder (ADHD), or dyslexia. Neurodiversity is common in the general population, with an estimated 5.0% to 7.1% and 7% of the world population being diagnosed ...
[ { "created": "Tue, 13 Jun 2023 09:27:09 GMT", "version": "v1" } ]
2023-06-14
[ [ "Liebel", "Grischa", "" ], [ "Sigurðardóttir", "Steinunn Gróa", "" ] ]
Neurodiversity is an umbrella term that describes variation in brain function among individuals, including conditions such as Attention deficit hyperactivity disorder (ADHD), or dyslexia. Neurodiversity is common in the general population, with an estimated 5.0% to 7.1% and 7% of the world population being diagnosed wi...
2401.03429
Zheng Lian
Zheng Lian, Licai Sun, Yong Ren, Hao Gu, Haiyang Sun, Lan Chen, Bin Liu, Jianhua Tao
MERBench: A Unified Evaluation Benchmark for Multimodal Emotion Recognition
null
null
null
null
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multimodal emotion recognition plays a crucial role in enhancing user experience in human-computer interaction. Over the past few decades, researchers have proposed a series of algorithms and achieved impressive progress. Although each method shows its superior performance, different methods lack a fair comparison du...
[ { "created": "Sun, 7 Jan 2024 09:09:32 GMT", "version": "v1" }, { "created": "Wed, 10 Jan 2024 07:55:16 GMT", "version": "v2" }, { "created": "Sun, 21 Apr 2024 02:18:47 GMT", "version": "v3" } ]
2024-04-23
[ [ "Lian", "Zheng", "" ], [ "Sun", "Licai", "" ], [ "Ren", "Yong", "" ], [ "Gu", "Hao", "" ], [ "Sun", "Haiyang", "" ], [ "Chen", "Lan", "" ], [ "Liu", "Bin", "" ], [ "Tao", "Jianhua", "" ] ]
Multimodal emotion recognition plays a crucial role in enhancing user experience in human-computer interaction. Over the past few decades, researchers have proposed a series of algorithms and achieved impressive progress. Although each method shows its superior performance, different methods lack a fair comparison due ...
1905.00538
Sunghoon Im
Sunghoon Im, Hae-Gon Jeon, Stephen Lin, In So Kweon
DPSNet: End-to-end Deep Plane Sweep Stereo
ICLR2019 accepted
null
null
null
cs.CV cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multiview stereo aims to reconstruct scene depth from images acquired by a camera under arbitrary motion. Recent methods address this problem through deep learning, which can utilize semantic cues to deal with challenges such as textureless and reflective regions. In this paper, we present a convolutional neural netw...
[ { "created": "Thu, 2 May 2019 00:59:31 GMT", "version": "v1" } ]
2019-05-03
[ [ "Im", "Sunghoon", "" ], [ "Jeon", "Hae-Gon", "" ], [ "Lin", "Stephen", "" ], [ "Kweon", "In So", "" ] ]
Multiview stereo aims to reconstruct scene depth from images acquired by a camera under arbitrary motion. Recent methods address this problem through deep learning, which can utilize semantic cues to deal with challenges such as textureless and reflective regions. In this paper, we present a convolutional neural networ...
2308.03415
Christian Huber
Christian Huber, Tu Anh Dinh, Carlos Mullov, Ngoc Quan Pham, Thai Binh Nguyen, Fabian Retkowski, Stefan Constantin, Enes Yavuz Ugan, Danni Liu, Zhaolin Li, Sai Koneru, Jan Niehues and Alexander Waibel
End-to-End Evaluation for Low-Latency Simultaneous Speech Translation
Demo paper at EMNLP 2023
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
The challenge of low-latency speech translation has recently draw significant interest in the research community as shown by several publications and shared tasks. Therefore, it is essential to evaluate these different approaches in realistic scenarios. However, currently only specific aspects of the systems are eval...
[ { "created": "Mon, 7 Aug 2023 09:06:20 GMT", "version": "v1" }, { "created": "Mon, 23 Oct 2023 11:47:04 GMT", "version": "v2" }, { "created": "Wed, 17 Jul 2024 11:29:10 GMT", "version": "v3" } ]
2024-07-18
[ [ "Huber", "Christian", "" ], [ "Dinh", "Tu Anh", "" ], [ "Mullov", "Carlos", "" ], [ "Pham", "Ngoc Quan", "" ], [ "Nguyen", "Thai Binh", "" ], [ "Retkowski", "Fabian", "" ], [ "Constantin", "Stefan", "" ],...
The challenge of low-latency speech translation has recently draw significant interest in the research community as shown by several publications and shared tasks. Therefore, it is essential to evaluate these different approaches in realistic scenarios. However, currently only specific aspects of the systems are evalua...
1907.10206
Jim Buchan
Jim Buchan, Stephen MacDonell, Jennifer Yang
Effective team onboarding in Agile software development: techniques and goals
null
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Context: It is not uncommon for a new team member to join an existing Agile software development team, even after development has started. This new team member faces a number of challenges before they are integrated into the team and can contribute productively to team progress. Ideally, each newcomer should be suppo...
[ { "created": "Wed, 24 Jul 2019 02:04:46 GMT", "version": "v1" } ]
2019-07-25
[ [ "Buchan", "Jim", "" ], [ "MacDonell", "Stephen", "" ], [ "Yang", "Jennifer", "" ] ]
Context: It is not uncommon for a new team member to join an existing Agile software development team, even after development has started. This new team member faces a number of challenges before they are integrated into the team and can contribute productively to team progress. Ideally, each newcomer should be support...
1405.1524
Mohammad Mohammadi
Mohammad Mohammadi, Shahram Jafari
An expert system for recommending suitable ornamental fish addition to an aquarium based on aquarium condition
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Expert systems prove to be suitable replacement for human experts when human experts are unavailable for different reasons. Various expert system has been developed for wide range of application. Although some expert systems in the field of fishery and aquaculture has been developed but a system that aids user in pro...
[ { "created": "Wed, 7 May 2014 07:45:09 GMT", "version": "v1" } ]
2014-05-08
[ [ "Mohammadi", "Mohammad", "" ], [ "Jafari", "Shahram", "" ] ]
Expert systems prove to be suitable replacement for human experts when human experts are unavailable for different reasons. Various expert system has been developed for wide range of application. Although some expert systems in the field of fishery and aquaculture has been developed but a system that aids user in proce...
2405.15080
Tom Goertzen
Tom Goertzen
Constructing Interlocking Assemblies with Crystallographic Symmetries
null
null
null
null
cs.CG math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work presents a construction method for interlocking assemblies based on planar crystallographic symmetries. Planar crystallographic groups, also known as wallpaper groups, correspond to tessellations of the plane with a tile, called a fundamental domain, such that the action of the group can be used to tessella...
[ { "created": "Thu, 23 May 2024 22:05:01 GMT", "version": "v1" } ]
2024-05-27
[ [ "Goertzen", "Tom", "" ] ]
This work presents a construction method for interlocking assemblies based on planar crystallographic symmetries. Planar crystallographic groups, also known as wallpaper groups, correspond to tessellations of the plane with a tile, called a fundamental domain, such that the action of the group can be used to tessellate...
2405.19832
Herman Cappelen
Herman Cappelen, Josh Dever and John Hawthorne
AI Safety: A Climb To Armageddon?
20 page article
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents an argument that certain AI safety measures, rather than mitigating existential risk, may instead exacerbate it. Under certain key assumptions - the inevitability of AI failure, the expected correlation between an AI system's power at the point of failure and the severity of the resulting harm, an...
[ { "created": "Thu, 30 May 2024 08:41:54 GMT", "version": "v1" }, { "created": "Sun, 2 Jun 2024 22:32:46 GMT", "version": "v2" } ]
2024-06-04
[ [ "Cappelen", "Herman", "" ], [ "Dever", "Josh", "" ], [ "Hawthorne", "John", "" ] ]
This paper presents an argument that certain AI safety measures, rather than mitigating existential risk, may instead exacerbate it. Under certain key assumptions - the inevitability of AI failure, the expected correlation between an AI system's power at the point of failure and the severity of the resulting harm, and ...
2401.02804
Yuta Okuyama
Yuta Okuyama, Yuki Endo, Yoshihiro Kanamori
DiffBody: Diffusion-based Pose and Shape Editing of Human Images
Accepted to WACV 2024, project page: https://www.cgg.cs.tsukuba.ac.jp/~okuyama/pub/diffbody/
null
null
null
cs.CV cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Pose and body shape editing in a human image has received increasing attention. However, current methods often struggle with dataset biases and deteriorate realism and the person's identity when users make large edits. We propose a one-shot approach that enables large edits with identity preservation. To enable large...
[ { "created": "Fri, 5 Jan 2024 13:36:19 GMT", "version": "v1" }, { "created": "Mon, 8 Jan 2024 04:41:30 GMT", "version": "v2" } ]
2024-01-09
[ [ "Okuyama", "Yuta", "" ], [ "Endo", "Yuki", "" ], [ "Kanamori", "Yoshihiro", "" ] ]
Pose and body shape editing in a human image has received increasing attention. However, current methods often struggle with dataset biases and deteriorate realism and the person's identity when users make large edits. We propose a one-shot approach that enables large edits with identity preservation. To enable large e...
1910.11911
Ariel Calderon
A. A. Calder\'on, Y. Chen, X. Yang, L. Chang, X.-T. Nguyen, E. K. Singer, and N. O. P\'erez-Arancibia
Control of Flying Robotic Insects: A Perspective and Unifying Approach
ICAR 2019
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We discuss the problem of designing and implementing controllers for insect-scale flapping-wing micro air vehicles (FWMAVs), from a unifying perspective and employing two different experimental platforms; namely, a Harvard RoboBee-like two-winged robot and the four-winged USC Bee+. Through experiments, we demonstrate...
[ { "created": "Fri, 25 Oct 2019 19:36:57 GMT", "version": "v1" } ]
2019-10-29
[ [ "Calderón", "A. A.", "" ], [ "Chen", "Y.", "" ], [ "Yang", "X.", "" ], [ "Chang", "L.", "" ], [ "Nguyen", "X. -T.", "" ], [ "Singer", "E. K.", "" ], [ "Pérez-Arancibia", "N. O.", "" ] ]
We discuss the problem of designing and implementing controllers for insect-scale flapping-wing micro air vehicles (FWMAVs), from a unifying perspective and employing two different experimental platforms; namely, a Harvard RoboBee-like two-winged robot and the four-winged USC Bee+. Through experiments, we demonstrate t...
2210.17367
Yuya Yamamoto
Yuya Yamamoto, Juhan Nam, Hiroko Terasawa
Analysis and Detection of Singing Techniques in Repertoires of J-POP Solo Singers
Accepted at ISMIR 2022, appendix website: https://yamathcy.github.io/ISMIR2022J-POP/
null
null
null
cs.SD cs.DL cs.IR cs.MM eess.AS
http://creativecommons.org/licenses/by/4.0/
In this paper, we focus on singing techniques within the scope of music information retrieval research. We investigate how singers use singing techniques using real-world recordings of famous solo singers in Japanese popular music songs (J-POP). First, we built a new dataset of singing techniques. The dataset consist...
[ { "created": "Mon, 31 Oct 2022 14:45:01 GMT", "version": "v1" }, { "created": "Tue, 15 Nov 2022 19:31:27 GMT", "version": "v2" } ]
2022-11-17
[ [ "Yamamoto", "Yuya", "" ], [ "Nam", "Juhan", "" ], [ "Terasawa", "Hiroko", "" ] ]
In this paper, we focus on singing techniques within the scope of music information retrieval research. We investigate how singers use singing techniques using real-world recordings of famous solo singers in Japanese popular music songs (J-POP). First, we built a new dataset of singing techniques. The dataset consists ...
1912.10764
S\'ebastien Henwood
S\'ebastien Henwood, Fran\c{c}ois Leduc-Primeau and Yvon Savaria
Layerwise Noise Maximisation to Train Low-Energy Deep Neural Networks
To be presented at AICAS 2020
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep neural networks (DNNs) depend on the storage of a large number of parameters, which consumes an important portion of the energy used during inference. This paper considers the case where the energy usage of memory elements can be reduced at the cost of reduced reliability. A training algorithm is proposed to opt...
[ { "created": "Mon, 23 Dec 2019 12:36:51 GMT", "version": "v1" } ]
2019-12-24
[ [ "Henwood", "Sébastien", "" ], [ "Leduc-Primeau", "François", "" ], [ "Savaria", "Yvon", "" ] ]
Deep neural networks (DNNs) depend on the storage of a large number of parameters, which consumes an important portion of the energy used during inference. This paper considers the case where the energy usage of memory elements can be reduced at the cost of reduced reliability. A training algorithm is proposed to optim...
2202.07883
Mohamed Nabeel
Wathsara Daluwatta, Ravindu De Silva, Sanduni Kariyawasam, Mohamed Nabeel, Charith Elvitigala, Kasun De Zoysa, Chamath Keppitiyagama
CGraph: Graph Based Extensible Predictive Domain Threat Intelligence Platform
threat intelligence graph investigation
null
null
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
Ability to effectively investigate indicators of compromise and associated network resources involved in cyber attacks is paramount not only to identify affected network resources but also to detect related malicious resources. Today, most of the cyber threat intelligence platforms are reactive in that they can ident...
[ { "created": "Wed, 16 Feb 2022 06:28:07 GMT", "version": "v1" } ]
2022-02-17
[ [ "Daluwatta", "Wathsara", "" ], [ "De Silva", "Ravindu", "" ], [ "Kariyawasam", "Sanduni", "" ], [ "Nabeel", "Mohamed", "" ], [ "Elvitigala", "Charith", "" ], [ "De Zoysa", "Kasun", "" ], [ "Keppitiyagama", "Cha...
Ability to effectively investigate indicators of compromise and associated network resources involved in cyber attacks is paramount not only to identify affected network resources but also to detect related malicious resources. Today, most of the cyber threat intelligence platforms are reactive in that they can identif...
2107.05146
Alexander Lambert
Alexander Lambert, Byron Boots
Entropy Regularized Motion Planning via Stein Variational Inference
RSS 2021 Workshop on Integrating Planning and Learning
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
Many Imitation and Reinforcement Learning approaches rely on the availability of expert-generated demonstrations for learning policies or value functions from data. Obtaining a reliable distribution of trajectories from motion planners is non-trivial, since it must broadly cover the space of states likely to be encou...
[ { "created": "Sun, 11 Jul 2021 23:39:24 GMT", "version": "v1" } ]
2021-07-13
[ [ "Lambert", "Alexander", "" ], [ "Boots", "Byron", "" ] ]
Many Imitation and Reinforcement Learning approaches rely on the availability of expert-generated demonstrations for learning policies or value functions from data. Obtaining a reliable distribution of trajectories from motion planners is non-trivial, since it must broadly cover the space of states likely to be encount...
2205.02211
Bashar Alhafni
Bashar Alhafni, Nizar Habash, Houda Bouamor
User-Centric Gender Rewriting
Accepted at NAACL 2022
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we define the task of gender rewriting in contexts involving two users (I and/or You) - first and second grammatical persons with independent grammatical gender preferences. We focus on Arabic, a gender-marking morphologically rich language. We develop a multi-step system that combines the positive asp...
[ { "created": "Wed, 4 May 2022 17:46:17 GMT", "version": "v1" } ]
2022-05-05
[ [ "Alhafni", "Bashar", "" ], [ "Habash", "Nizar", "" ], [ "Bouamor", "Houda", "" ] ]
In this paper, we define the task of gender rewriting in contexts involving two users (I and/or You) - first and second grammatical persons with independent grammatical gender preferences. We focus on Arabic, a gender-marking morphologically rich language. We develop a multi-step system that combines the positive aspec...
0710.4815
EDA Publishing Association
Raul Blazquez, Fred Lee, David Wentzloff, Brian Ginsburg, Johnna Powell, Anantha Chandrakasan
Direct Conversion Pulsed UWB Transceiver Architecture
Submitted on behalf of EDAA (http://www.edaa.com/)
Dans Design, Automation and Test in Europe | Designers'Forum - DATE'05, Munich : Allemagne (2005)
null
null
cs.NI
null
Ultra-wideband (UWB) communication is an emerging wireless technology that promises high data rates over short distances and precise locationing. The large available bandwidth and the constraint of a maximum power spectral density drives a unique set of system challenges. This paper addresses these challenges using t...
[ { "created": "Thu, 25 Oct 2007 12:01:54 GMT", "version": "v1" } ]
2011-11-09
[ [ "Blazquez", "Raul", "" ], [ "Lee", "Fred", "" ], [ "Wentzloff", "David", "" ], [ "Ginsburg", "Brian", "" ], [ "Powell", "Johnna", "" ], [ "Chandrakasan", "Anantha", "" ] ]
Ultra-wideband (UWB) communication is an emerging wireless technology that promises high data rates over short distances and precise locationing. The large available bandwidth and the constraint of a maximum power spectral density drives a unique set of system challenges. This paper addresses these challenges using two...
1912.08100
Ning Li
Ning Li, Zhaoxin Zhang, Jose-Fernan Martinez-Ortega, Xin Yuan
Geographical and Topology Control based Opportunistic Routing for Ad Hoc Networks
arXiv admin note: substantial text overlap with arXiv:1709.10317
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The opportunistic routing has great advantages on improving packet delivery probability between the source node and candidate forwarding set. For improving and reducing energy consumption and network interference, in this paper, we propose an efficient and reliable transmission power control based opportunistic routi...
[ { "created": "Mon, 16 Dec 2019 08:44:29 GMT", "version": "v1" } ]
2019-12-18
[ [ "Li", "Ning", "" ], [ "Zhang", "Zhaoxin", "" ], [ "Martinez-Ortega", "Jose-Fernan", "" ], [ "Yuan", "Xin", "" ] ]
The opportunistic routing has great advantages on improving packet delivery probability between the source node and candidate forwarding set. For improving and reducing energy consumption and network interference, in this paper, we propose an efficient and reliable transmission power control based opportunistic routing...
2307.16019
Lia Morra
Francesco Manigrasso and Lia Morra and Fabrizio Lamberti
Fuzzy Logic Visual Network (FLVN): A neuro-symbolic approach for visual features matching
Accepted for publication at ICIAP 2023
null
null
null
cs.CV cs.LG cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Neuro-symbolic integration aims at harnessing the power of symbolic knowledge representation combined with the learning capabilities of deep neural networks. In particular, Logic Tensor Networks (LTNs) allow to incorporate background knowledge in the form of logical axioms by grounding a first order logic language as...
[ { "created": "Sat, 29 Jul 2023 16:21:40 GMT", "version": "v1" } ]
2023-08-01
[ [ "Manigrasso", "Francesco", "" ], [ "Morra", "Lia", "" ], [ "Lamberti", "Fabrizio", "" ] ]
Neuro-symbolic integration aims at harnessing the power of symbolic knowledge representation combined with the learning capabilities of deep neural networks. In particular, Logic Tensor Networks (LTNs) allow to incorporate background knowledge in the form of logical axioms by grounding a first order logic language as d...
2204.00536
Chuhan Wu
Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang
Semi-FairVAE: Semi-supervised Fair Representation Learning with Adversarial Variational Autoencoder
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Adversarial learning is a widely used technique in fair representation learning to remove the biases on sensitive attributes from data representations. It usually requires to incorporate the sensitive attribute labels as prediction targets. However, in many scenarios the sensitive attribute labels of many samples can...
[ { "created": "Fri, 1 Apr 2022 15:57:47 GMT", "version": "v1" } ]
2022-04-04
[ [ "Wu", "Chuhan", "" ], [ "Wu", "Fangzhao", "" ], [ "Qi", "Tao", "" ], [ "Huang", "Yongfeng", "" ] ]
Adversarial learning is a widely used technique in fair representation learning to remove the biases on sensitive attributes from data representations. It usually requires to incorporate the sensitive attribute labels as prediction targets. However, in many scenarios the sensitive attribute labels of many samples can b...
2204.09350
Tiejun Lv
Zhongyu Wang, Tiejun Lv, Jie Zeng, and Wei Ni
Placement and Resource Allocation of Wireless-Powered Multiantenna UAV for Energy-Efficient Multiuser NOMA
15 pages, 11 figures, Accepted by IEEE Transactions on Wireless Communications
null
null
null
cs.IT eess.SP math.IT
http://creativecommons.org/publicdomain/zero/1.0/
This paper investigates a new downlink nonorthogonal multiple access (NOMA) system, where a multiantenna unmanned aerial vehicle (UAV) is powered by wireless power transfer (WPT) and serves as the base station for multiple pairs of ground users (GUs) running NOMA in each pair. An energy efficiency (EE) maximization p...
[ { "created": "Wed, 20 Apr 2022 09:51:28 GMT", "version": "v1" } ]
2022-04-21
[ [ "Wang", "Zhongyu", "" ], [ "Lv", "Tiejun", "" ], [ "Zeng", "Jie", "" ], [ "Ni", "Wei", "" ] ]
This paper investigates a new downlink nonorthogonal multiple access (NOMA) system, where a multiantenna unmanned aerial vehicle (UAV) is powered by wireless power transfer (WPT) and serves as the base station for multiple pairs of ground users (GUs) running NOMA in each pair. An energy efficiency (EE) maximization pro...
1709.08436
Zhijie Zhang
Xiaoming Sun, Jialin Zhang, Zhijie Zhang
A Linear Algorithm for Finding the Sink of Unique Sink Orientations on Grids
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
An orientation of a grid is called unique sink orientation (USO) if each of its nonempty subgrids has a unique sink. Particularly, the original grid itself has a unique global sink. In this work we investigate the problem of how to find the global sink using minimum number of queries to an oracle. There are two diffe...
[ { "created": "Mon, 25 Sep 2017 11:49:16 GMT", "version": "v1" } ]
2017-09-26
[ [ "Sun", "Xiaoming", "" ], [ "Zhang", "Jialin", "" ], [ "Zhang", "Zhijie", "" ] ]
An orientation of a grid is called unique sink orientation (USO) if each of its nonempty subgrids has a unique sink. Particularly, the original grid itself has a unique global sink. In this work we investigate the problem of how to find the global sink using minimum number of queries to an oracle. There are two differe...
1810.01015
Salimeh Yasaei Sekeh
Salimeh Yasaei Sekeh, Morteza Noshad, Kevin R. Moon, Alfred O. Hero
Convergence Rates for Empirical Estimation of Binary Classification Bounds
27 pages, 8 figures
null
null
null
cs.IT cs.LG math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Bounding the best achievable error probability for binary classification problems is relevant to many applications including machine learning, signal processing, and information theory. Many bounds on the Bayes binary classification error rate depend on information divergences between the pair of class distributions....
[ { "created": "Mon, 1 Oct 2018 23:53:54 GMT", "version": "v1" } ]
2018-10-03
[ [ "Sekeh", "Salimeh Yasaei", "" ], [ "Noshad", "Morteza", "" ], [ "Moon", "Kevin R.", "" ], [ "Hero", "Alfred O.", "" ] ]
Bounding the best achievable error probability for binary classification problems is relevant to many applications including machine learning, signal processing, and information theory. Many bounds on the Bayes binary classification error rate depend on information divergences between the pair of class distributions. R...
2407.03821
Bardh Prenkaj
Davide Gabrielli, Bardh Prenkaj, Paola Velardi
Seamless Monitoring of Stress Levels Leveraging a Universal Model for Time Sequences
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Monitoring the stress level in patients with neurodegenerative diseases can help manage symptoms, improve patient's quality of life, and provide insight into disease progression. In the literature, ECG, actigraphy, speech, voice, and facial analysis have proven effective at detecting patients' emotions. On the other ...
[ { "created": "Thu, 4 Jul 2024 10:46:09 GMT", "version": "v1" } ]
2024-07-08
[ [ "Gabrielli", "Davide", "" ], [ "Prenkaj", "Bardh", "" ], [ "Velardi", "Paola", "" ] ]
Monitoring the stress level in patients with neurodegenerative diseases can help manage symptoms, improve patient's quality of life, and provide insight into disease progression. In the literature, ECG, actigraphy, speech, voice, and facial analysis have proven effective at detecting patients' emotions. On the other ha...
2106.07758
Sahil Verma
Sahil Verma, Aditya Lahiri, John P. Dickerson, Su-In Lee
Pitfalls of Explainable ML: An Industry Perspective
Presented at JOURNE workshop at MLSYS 2021 (https://sites.google.com/view/workshop-journe/home)
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As machine learning (ML) systems take a more prominent and central role in contributing to life-impacting decisions, ensuring their trustworthiness and accountability is of utmost importance. Explanations sit at the core of these desirable attributes of a ML system. The emerging field is frequently called ``Explainab...
[ { "created": "Mon, 14 Jun 2021 21:05:05 GMT", "version": "v1" } ]
2021-06-16
[ [ "Verma", "Sahil", "" ], [ "Lahiri", "Aditya", "" ], [ "Dickerson", "John P.", "" ], [ "Lee", "Su-In", "" ] ]
As machine learning (ML) systems take a more prominent and central role in contributing to life-impacting decisions, ensuring their trustworthiness and accountability is of utmost importance. Explanations sit at the core of these desirable attributes of a ML system. The emerging field is frequently called ``Explainable...
2106.09051
Paul Henderson
Paul Henderson, Christoph H. Lampert, Bernd Bickel
Unsupervised Video Prediction from a Single Frame by Estimating 3D Dynamic Scene Structure
null
null
null
null
cs.CV cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Our goal in this work is to generate realistic videos given just one initial frame as input. Existing unsupervised approaches to this task do not consider the fact that a video typically shows a 3D environment, and that this should remain coherent from frame to frame even as the camera and objects move. We address th...
[ { "created": "Wed, 16 Jun 2021 18:00:12 GMT", "version": "v1" } ]
2021-06-18
[ [ "Henderson", "Paul", "" ], [ "Lampert", "Christoph H.", "" ], [ "Bickel", "Bernd", "" ] ]
Our goal in this work is to generate realistic videos given just one initial frame as input. Existing unsupervised approaches to this task do not consider the fact that a video typically shows a 3D environment, and that this should remain coherent from frame to frame even as the camera and objects move. We address this...
2310.09952
Arshia Soltani Moakhar
Arshia Soltani Moakhar, Mohammad Azizmalayeri, Hossein Mirzaei, Mohammad Taghi Manzuri, Mohammad Hossein Rohban
Seeking Next Layer Neurons' Attention for Error-Backpropagation-Like Training in a Multi-Agent Network Framework
null
null
null
null
cs.NE cs.AI cs.GT cs.LG cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Despite considerable theoretical progress in the training of neural networks viewed as a multi-agent system of neurons, particularly concerning biological plausibility and decentralized training, their applicability to real-world problems remains limited due to scalability issues. In contrast, error-backpropagation h...
[ { "created": "Sun, 15 Oct 2023 21:07:09 GMT", "version": "v1" } ]
2023-10-17
[ [ "Moakhar", "Arshia Soltani", "" ], [ "Azizmalayeri", "Mohammad", "" ], [ "Mirzaei", "Hossein", "" ], [ "Manzuri", "Mohammad Taghi", "" ], [ "Rohban", "Mohammad Hossein", "" ] ]
Despite considerable theoretical progress in the training of neural networks viewed as a multi-agent system of neurons, particularly concerning biological plausibility and decentralized training, their applicability to real-world problems remains limited due to scalability issues. In contrast, error-backpropagation has...
2301.00236
Sandipan Sarma
Sandipan Sarma, Arijit Sur
DiRaC-I: Identifying Diverse and Rare Training Classes for Zero-Shot Learning
22 pages, 10 Figures
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Inspired by strategies like Active Learning, it is intuitive that intelligently selecting the training classes from a dataset for Zero-Shot Learning (ZSL) can improve the performance of existing ZSL methods. In this work, we propose a framework called Diverse and Rare Class Identifier (DiRaC-I) which, given an attrib...
[ { "created": "Sat, 31 Dec 2022 16:05:09 GMT", "version": "v1" } ]
2023-01-03
[ [ "Sarma", "Sandipan", "" ], [ "Sur", "Arijit", "" ] ]
Inspired by strategies like Active Learning, it is intuitive that intelligently selecting the training classes from a dataset for Zero-Shot Learning (ZSL) can improve the performance of existing ZSL methods. In this work, we propose a framework called Diverse and Rare Class Identifier (DiRaC-I) which, given an attribut...
2006.15555
Aviad Aberdam
Aviad Aberdam, Dror Simon, Michael Elad
When and How Can Deep Generative Models be Inverted?
null
null
null
null
cs.LG cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep generative models (e.g. GANs and VAEs) have been developed quite extensively in recent years. Lately, there has been an increased interest in the inversion of such a model, i.e. given a (possibly corrupted) signal, we wish to recover the latent vector that generated it. Building upon sparse representation theory...
[ { "created": "Sun, 28 Jun 2020 09:37:52 GMT", "version": "v1" } ]
2020-06-30
[ [ "Aberdam", "Aviad", "" ], [ "Simon", "Dror", "" ], [ "Elad", "Michael", "" ] ]
Deep generative models (e.g. GANs and VAEs) have been developed quite extensively in recent years. Lately, there has been an increased interest in the inversion of such a model, i.e. given a (possibly corrupted) signal, we wish to recover the latent vector that generated it. Building upon sparse representation theory, ...
2308.02560
Robin San Roman
Robin San Roman and Yossi Adi and Antoine Deleforge and Romain Serizel and Gabriel Synnaeve and Alexandre D\'efossez
From Discrete Tokens to High-Fidelity Audio Using Multi-Band Diffusion
10 pages
Thirty-seventh Conference on Neural Information Processing Systems (2023)
null
null
cs.SD cs.LG eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep generative models can generate high-fidelity audio conditioned on various types of representations (e.g., mel-spectrograms, Mel-frequency Cepstral Coefficients (MFCC)). Recently, such models have been used to synthesize audio waveforms conditioned on highly compressed representations. Although such methods produ...
[ { "created": "Wed, 2 Aug 2023 22:14:29 GMT", "version": "v1" }, { "created": "Wed, 8 Nov 2023 10:04:00 GMT", "version": "v2" } ]
2023-11-09
[ [ "Roman", "Robin San", "" ], [ "Adi", "Yossi", "" ], [ "Deleforge", "Antoine", "" ], [ "Serizel", "Romain", "" ], [ "Synnaeve", "Gabriel", "" ], [ "Défossez", "Alexandre", "" ] ]
Deep generative models can generate high-fidelity audio conditioned on various types of representations (e.g., mel-spectrograms, Mel-frequency Cepstral Coefficients (MFCC)). Recently, such models have been used to synthesize audio waveforms conditioned on highly compressed representations. Although such methods produce...
2001.06641
Nikita Polyanskii
Andreas Lenz and Nikita Polyanskii
Optimal Codes Correcting a Burst of Deletions of Variable Length
6 pages
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we present an efficiently encodable and decodable code construction that is capable of correction a burst of deletions of length at most $k$. The redundancy of this code is $\log n + k(k+1)/2\log \log n+c_k$ for some constant $c_k$ that only depends on $k$ and thus is scaling-optimal. The code can be s...
[ { "created": "Sat, 18 Jan 2020 09:59:52 GMT", "version": "v1" } ]
2020-01-22
[ [ "Lenz", "Andreas", "" ], [ "Polyanskii", "Nikita", "" ] ]
In this paper, we present an efficiently encodable and decodable code construction that is capable of correction a burst of deletions of length at most $k$. The redundancy of this code is $\log n + k(k+1)/2\log \log n+c_k$ for some constant $c_k$ that only depends on $k$ and thus is scaling-optimal. The code can be spl...
2209.14401
Kaiyu Wu
Rathish Das, Meng He, Eitan Kondratovsky, J. Ian Munro, Anurag Murty Naredla, Kaiyu Wu
Shortest Beer Path Queries in Interval Graphs
To appear in ISAAC 2022
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Our interest is in paths between pairs of vertices that go through at least one of a subset of the vertices known as beer vertices. Such a path is called a beer path, and the beer distance between two vertices is the length of the shortest beer path. We show that we can represent unweighted interval graphs using $2...
[ { "created": "Wed, 28 Sep 2022 19:56:28 GMT", "version": "v1" } ]
2022-09-30
[ [ "Das", "Rathish", "" ], [ "He", "Meng", "" ], [ "Kondratovsky", "Eitan", "" ], [ "Munro", "J. Ian", "" ], [ "Naredla", "Anurag Murty", "" ], [ "Wu", "Kaiyu", "" ] ]
Our interest is in paths between pairs of vertices that go through at least one of a subset of the vertices known as beer vertices. Such a path is called a beer path, and the beer distance between two vertices is the length of the shortest beer path. We show that we can represent unweighted interval graphs using $2n \l...
2204.07010
Yue Ning
Jiaxuan Li and Yue Ning
Anti-Asian Hate Speech Detection via Data Augmented Semantic Relation Inference
To appear in Proceedings of the 16th International AAAI Conference on Web and Social Media (ICWSM)
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
With the spreading of hate speech on social media in recent years, automatic detection of hate speech is becoming a crucial task and has attracted attention from various communities. This task aims to recognize online posts (e.g., tweets) that contain hateful information. The peculiarities of languages in social medi...
[ { "created": "Thu, 14 Apr 2022 15:03:35 GMT", "version": "v1" } ]
2022-04-15
[ [ "Li", "Jiaxuan", "" ], [ "Ning", "Yue", "" ] ]
With the spreading of hate speech on social media in recent years, automatic detection of hate speech is becoming a crucial task and has attracted attention from various communities. This task aims to recognize online posts (e.g., tweets) that contain hateful information. The peculiarities of languages in social media,...
1110.1687
Chi-Yao Hong
Ankit Singla, Chi-Yao Hong, Lucian Popa, P. Brighten Godfrey
Jellyfish: Networking Data Centers Randomly
14 pages, 12 figures
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Industry experience indicates that the ability to incrementally expand data centers is essential. However, existing high-bandwidth network designs have rigid structure that interferes with incremental expansion. We present Jellyfish, a high-capacity network interconnect, which, by adopting a random graph topology, yi...
[ { "created": "Sat, 8 Oct 2011 01:24:57 GMT", "version": "v1" }, { "created": "Wed, 12 Oct 2011 15:05:52 GMT", "version": "v2" }, { "created": "Fri, 20 Apr 2012 20:38:43 GMT", "version": "v3" } ]
2012-04-24
[ [ "Singla", "Ankit", "" ], [ "Hong", "Chi-Yao", "" ], [ "Popa", "Lucian", "" ], [ "Godfrey", "P. Brighten", "" ] ]
Industry experience indicates that the ability to incrementally expand data centers is essential. However, existing high-bandwidth network designs have rigid structure that interferes with incremental expansion. We present Jellyfish, a high-capacity network interconnect, which, by adopting a random graph topology, yiel...
1601.08059
Nikos Bikakis
Nikos Bikakis, Timos Sellis
Exploration and Visualization in the Web of Big Linked Data: A Survey of the State of the Art
6th International Workshop on Linked Web Data Management (LWDM 2016)
null
null
null
cs.HC cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Data exploration and visualization systems are of great importance in the Big Data era. Exploring and visualizing very large datasets has become a major research challenge, of which scalability is a vital requirement. In this survey, we describe the major prerequisites and challenges that should be addressed by the m...
[ { "created": "Fri, 29 Jan 2016 11:30:44 GMT", "version": "v1" } ]
2016-02-01
[ [ "Bikakis", "Nikos", "" ], [ "Sellis", "Timos", "" ] ]
Data exploration and visualization systems are of great importance in the Big Data era. Exploring and visualizing very large datasets has become a major research challenge, of which scalability is a vital requirement. In this survey, we describe the major prerequisites and challenges that should be addressed by the mod...
1911.12562
Guozhu Meng
Yingzhe He and Guozhu Meng and Kai Chen and Xingbo Hu and Jinwen He
Towards Security Threats of Deep Learning Systems: A Survey
28 pages, 6 figures
IEEE Transactions on Software Engineering 2020
null
null
cs.CR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep learning has gained tremendous success and great popularity in the past few years. However, deep learning systems are suffering several inherent weaknesses, which can threaten the security of learning models. Deep learning's wide use further magnifies the impact and consequences. To this end, lots of research ha...
[ { "created": "Thu, 28 Nov 2019 07:16:05 GMT", "version": "v1" }, { "created": "Tue, 27 Oct 2020 17:27:53 GMT", "version": "v2" } ]
2020-10-28
[ [ "He", "Yingzhe", "" ], [ "Meng", "Guozhu", "" ], [ "Chen", "Kai", "" ], [ "Hu", "Xingbo", "" ], [ "He", "Jinwen", "" ] ]
Deep learning has gained tremendous success and great popularity in the past few years. However, deep learning systems are suffering several inherent weaknesses, which can threaten the security of learning models. Deep learning's wide use further magnifies the impact and consequences. To this end, lots of research has ...
2007.13723
Claudio Santos
Claudio Filipi Goncalves do Santos, Danilo Colombo, Mateus Roder, Jo\~ao Paulo Papa
MaxDropout: Deep Neural Network Regularization Based on Maximum Output Values
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Different techniques have emerged in the deep learning scenario, such as Convolutional Neural Networks, Deep Belief Networks, and Long Short-Term Memory Networks, to cite a few. In lockstep, regularization methods, which aim to prevent overfitting by penalizing the weight connections, or turning off some units, have ...
[ { "created": "Mon, 27 Jul 2020 17:55:54 GMT", "version": "v1" } ]
2020-07-28
[ [ "Santos", "Claudio Filipi Goncalves do", "" ], [ "Colombo", "Danilo", "" ], [ "Roder", "Mateus", "" ], [ "Papa", "João Paulo", "" ] ]
Different techniques have emerged in the deep learning scenario, such as Convolutional Neural Networks, Deep Belief Networks, and Long Short-Term Memory Networks, to cite a few. In lockstep, regularization methods, which aim to prevent overfitting by penalizing the weight connections, or turning off some units, have be...
2002.01218
Eduard Eiben
Eduard Eiben and Daniel Lokshtanov
Removing Connected Obstacles in the Plane is FPT
null
null
null
null
cs.DS cs.CG cs.DM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Given two points in the plane, a set of obstacles defined by closed curves, and an integer $k$, does there exist a path between the two designated points intersecting at most $k$ of the obstacles? This is a fundamental and well-studied problem arising naturally in computational geometry, graph theory, wireless comput...
[ { "created": "Tue, 4 Feb 2020 10:50:28 GMT", "version": "v1" } ]
2020-02-05
[ [ "Eiben", "Eduard", "" ], [ "Lokshtanov", "Daniel", "" ] ]
Given two points in the plane, a set of obstacles defined by closed curves, and an integer $k$, does there exist a path between the two designated points intersecting at most $k$ of the obstacles? This is a fundamental and well-studied problem arising naturally in computational geometry, graph theory, wireless computin...
2110.15701
Chris Reinke
Chris Reinke, Xavier Alameda-Pineda
Successor Feature Representations
published in Transactions on Machine Learning Research (05/2023), source code: https://gitlab.inria.fr/robotlearn/sfr_learning, [v2] added experiments with learned features, [v3] renamed paper and changed scope, [v4] published version
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Transfer in Reinforcement Learning aims to improve learning performance on target tasks using knowledge from experienced source tasks. Successor Representations (SR) and their extension Successor Features (SF) are prominent transfer mechanisms in domains where reward functions change between tasks. They reevaluate th...
[ { "created": "Fri, 29 Oct 2021 12:01:48 GMT", "version": "v1" }, { "created": "Wed, 16 Feb 2022 13:13:18 GMT", "version": "v2" }, { "created": "Fri, 16 Dec 2022 10:11:53 GMT", "version": "v3" }, { "created": "Wed, 2 Aug 2023 09:14:54 GMT", "version": "v4" } ]
2023-08-03
[ [ "Reinke", "Chris", "" ], [ "Alameda-Pineda", "Xavier", "" ] ]
Transfer in Reinforcement Learning aims to improve learning performance on target tasks using knowledge from experienced source tasks. Successor Representations (SR) and their extension Successor Features (SF) are prominent transfer mechanisms in domains where reward functions change between tasks. They reevaluate the ...
1904.02459
Neeru Dubey
Neeru Dubey, Shreya Ghosh, Abhinav Dhall
Unsupervised Learning of Eye Gaze Representation from the Web
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Automatic eye gaze estimation has interested researchers for a while now. In this paper, we propose an unsupervised learning based method for estimating the eye gaze region. To train the proposed network "Ize-Net" in self-supervised manner, we collect a large `in the wild' dataset containing 1,54,251 images from the ...
[ { "created": "Thu, 4 Apr 2019 10:25:13 GMT", "version": "v1" } ]
2019-04-05
[ [ "Dubey", "Neeru", "" ], [ "Ghosh", "Shreya", "" ], [ "Dhall", "Abhinav", "" ] ]
Automatic eye gaze estimation has interested researchers for a while now. In this paper, we propose an unsupervised learning based method for estimating the eye gaze region. To train the proposed network "Ize-Net" in self-supervised manner, we collect a large `in the wild' dataset containing 1,54,251 images from the we...
2405.20495
Amrit Singh Bedi
Souradip Chakraborty, Soumya Suvra Ghosal, Ming Yin, Dinesh Manocha, Mengdi Wang, Amrit Singh Bedi, and Furong Huang
Transfer Q Star: Principled Decoding for LLM Alignment
null
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Aligning foundation models is essential for their safe and trustworthy deployment. However, traditional fine-tuning methods are computationally intensive and require updating billions of model parameters. A promising alternative, alignment via decoding, adjusts the response distribution directly without model updates...
[ { "created": "Thu, 30 May 2024 21:36:12 GMT", "version": "v1" } ]
2024-06-03
[ [ "Chakraborty", "Souradip", "" ], [ "Ghosal", "Soumya Suvra", "" ], [ "Yin", "Ming", "" ], [ "Manocha", "Dinesh", "" ], [ "Wang", "Mengdi", "" ], [ "Bedi", "Amrit Singh", "" ], [ "Huang", "Furong", "" ] ]
Aligning foundation models is essential for their safe and trustworthy deployment. However, traditional fine-tuning methods are computationally intensive and require updating billions of model parameters. A promising alternative, alignment via decoding, adjusts the response distribution directly without model updates t...
2310.13073
Parth Padalkar
Parth Padalkar, Gopal Gupta
Using Logic Programming and Kernel-Grouping for Improving Interpretability of Convolutional Neural Networks
arXiv admin note: text overlap with arXiv:2301.12667
null
null
null
cs.LG cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
Within the realm of deep learning, the interpretability of Convolutional Neural Networks (CNNs), particularly in the context of image classification tasks, remains a formidable challenge. To this end we present a neurosymbolic framework, NeSyFOLD-G that generates a symbolic rule-set using the last layer kernels of th...
[ { "created": "Thu, 19 Oct 2023 18:12:49 GMT", "version": "v1" } ]
2023-10-23
[ [ "Padalkar", "Parth", "" ], [ "Gupta", "Gopal", "" ] ]
Within the realm of deep learning, the interpretability of Convolutional Neural Networks (CNNs), particularly in the context of image classification tasks, remains a formidable challenge. To this end we present a neurosymbolic framework, NeSyFOLD-G that generates a symbolic rule-set using the last layer kernels of the ...
1811.08531
Kamer Vishi
Nils Gruschka, Vasileios Mavroeidis, Kamer Vishi, Meiko Jensen
Privacy Issues and Data Protection in Big Data: A Case Study Analysis under GDPR
7 pages, 1 figure, GDPR, Privacy, Cyber Threat Intelligence, Biometrics. To be appeared in the Proceedings of the 2018 IEEE International Conference on Big Data
null
null
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
Big data has become a great asset for many organizations, promising improved operations and new business opportunities. However, big data has increased access to sensitive information that when processed can directly jeopardize the privacy of individuals and violate data protection laws. As a consequence, data contro...
[ { "created": "Tue, 20 Nov 2018 23:42:12 GMT", "version": "v1" } ]
2018-11-22
[ [ "Gruschka", "Nils", "" ], [ "Mavroeidis", "Vasileios", "" ], [ "Vishi", "Kamer", "" ], [ "Jensen", "Meiko", "" ] ]
Big data has become a great asset for many organizations, promising improved operations and new business opportunities. However, big data has increased access to sensitive information that when processed can directly jeopardize the privacy of individuals and violate data protection laws. As a consequence, data controll...
2105.09217
Gautam K. Das
Pawan K. Mishra and Gautam K. Das
Approximation Algorithms For The Euclidean Dispersion Problems
17
null
null
null
cs.CG cs.DS
http://creativecommons.org/licenses/by/4.0/
In this article, we consider the Euclidean dispersion problems. Let $P=\{p_{1}, p_{2}, \ldots, p_{n}\}$ be a set of $n$ points in $\mathbb{R}^2$. For each point $p \in P$ and $S \subseteq P$, we define $cost_{\gamma}(p,S)$ as the sum of Euclidean distance from $p$ to the nearest $\gamma $ point in $S \setminus \{p\}$...
[ { "created": "Wed, 19 May 2021 15:56:30 GMT", "version": "v1" } ]
2021-05-20
[ [ "Mishra", "Pawan K.", "" ], [ "Das", "Gautam K.", "" ] ]
In this article, we consider the Euclidean dispersion problems. Let $P=\{p_{1}, p_{2}, \ldots, p_{n}\}$ be a set of $n$ points in $\mathbb{R}^2$. For each point $p \in P$ and $S \subseteq P$, we define $cost_{\gamma}(p,S)$ as the sum of Euclidean distance from $p$ to the nearest $\gamma $ point in $S \setminus \{p\}$. ...
2211.05555
Joon-Ha Kim
Joon-Ha Kim
Real time A* Adaptive Action Set Footstep Planning with Human Locomotion Energy Approximations Considering Angle Difference for Heuristic Function
Master's Degree Thesis
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
The problem of navigating a bipedal robot to a desired destination in various environments is very important. However, it is very difficult to solve the navigation problem in real time because the computation time is very long due to the nature of the biped robot having a high degree of freedom. In order to overcome ...
[ { "created": "Wed, 2 Nov 2022 02:28:16 GMT", "version": "v1" } ]
2022-11-11
[ [ "Kim", "Joon-Ha", "" ] ]
The problem of navigating a bipedal robot to a desired destination in various environments is very important. However, it is very difficult to solve the navigation problem in real time because the computation time is very long due to the nature of the biped robot having a high degree of freedom. In order to overcome th...
1304.5213
Hany SalahEldeen
Hany M. SalahEldeen and Michael L. Nelson
Carbon Dating The Web: Estimating the Age of Web Resources
This work is published at TempWeb03 workshop at WWW 2013 conference in Rio de Janeiro, Brazil
null
null
null
cs.IR cs.DL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the course of web research it is often necessary to estimate the creation datetime for web resources (in the general case, this value can only be estimated). While it is feasible to manually establish likely datetime values for small numbers of resources, this becomes infeasible if the collection is large. We pres...
[ { "created": "Thu, 18 Apr 2013 18:42:45 GMT", "version": "v1" } ]
2013-04-19
[ [ "SalahEldeen", "Hany M.", "" ], [ "Nelson", "Michael L.", "" ] ]
In the course of web research it is often necessary to estimate the creation datetime for web resources (in the general case, this value can only be estimated). While it is feasible to manually establish likely datetime values for small numbers of resources, this becomes infeasible if the collection is large. We presen...
2110.11187
Matteo De Carlo
Matteo De Carlo, Eliseo Ferrante, Daan Zeeuwe, Jacintha Ellers, Gerben Meynen and A. E. Eiben
Heritability in Morphological Robot Evolution
null
null
null
null
cs.NE cs.RO
http://creativecommons.org/licenses/by/4.0/
In the field of evolutionary robotics, choosing the correct encoding is very complicated, especially when robots evolve both behaviours and morphologies at the same time. With the objective of improving our understanding of the mapping process from encodings to functional robots, we introduce the biological notion of...
[ { "created": "Thu, 21 Oct 2021 14:58:17 GMT", "version": "v1" } ]
2021-10-22
[ [ "De Carlo", "Matteo", "" ], [ "Ferrante", "Eliseo", "" ], [ "Zeeuwe", "Daan", "" ], [ "Ellers", "Jacintha", "" ], [ "Meynen", "Gerben", "" ], [ "Eiben", "A. E.", "" ] ]
In the field of evolutionary robotics, choosing the correct encoding is very complicated, especially when robots evolve both behaviours and morphologies at the same time. With the objective of improving our understanding of the mapping process from encodings to functional robots, we introduce the biological notion of h...
1806.01106
Alejandro Linares-Barranco A. Linares-Barranco
A. Rios-Navarro, R. Tapiador-Morales, A. Jimenez-Fernandez, M. Dominguez-Morales, C. Amaya and A. Linares-Barranco
Performance evaluation over HW/SW co-design SoC memory transfers for a CNN accelerator
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many FPGAs vendors have recently included embedded processors in their devices, like Xilinx with ARM-Cortex A cores, together with programmable logic cells. These devices are known as Programmable System on Chip (PSoC). Their ARM cores (embedded in the processing system or PS) communicates with the programmable logic...
[ { "created": "Wed, 9 May 2018 08:54:15 GMT", "version": "v1" } ]
2018-06-05
[ [ "Rios-Navarro", "A.", "" ], [ "Tapiador-Morales", "R.", "" ], [ "Jimenez-Fernandez", "A.", "" ], [ "Dominguez-Morales", "M.", "" ], [ "Amaya", "C.", "" ], [ "Linares-Barranco", "A.", "" ] ]
Many FPGAs vendors have recently included embedded processors in their devices, like Xilinx with ARM-Cortex A cores, together with programmable logic cells. These devices are known as Programmable System on Chip (PSoC). Their ARM cores (embedded in the processing system or PS) communicates with the programmable logic c...
2312.13596
Zhixiang Su
Zhixiang Su, Di Wang, Chunyan Miao and Lizhen Cui
Anchoring Path for Inductive Relation Prediction in Knowledge Graphs
null
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Aiming to accurately predict missing edges representing relations between entities, which are pervasive in real-world Knowledge Graphs (KGs), relation prediction plays a critical role in enhancing the comprehensiveness and utility of KGs. Recent research focuses on path-based methods due to their inductive and explai...
[ { "created": "Thu, 21 Dec 2023 06:02:25 GMT", "version": "v1" } ]
2023-12-22
[ [ "Su", "Zhixiang", "" ], [ "Wang", "Di", "" ], [ "Miao", "Chunyan", "" ], [ "Cui", "Lizhen", "" ] ]
Aiming to accurately predict missing edges representing relations between entities, which are pervasive in real-world Knowledge Graphs (KGs), relation prediction plays a critical role in enhancing the comprehensiveness and utility of KGs. Recent research focuses on path-based methods due to their inductive and explaina...
2305.10411
Leonel Rozo
Hanna Ziesche and Leonel Rozo
Wasserstein Gradient Flows for Optimizing Gaussian Mixture Policies
null
null
null
null
cs.LG cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Robots often rely on a repertoire of previously-learned motion policies for performing tasks of diverse complexities. When facing unseen task conditions or when new task requirements arise, robots must adapt their motion policies accordingly. In this context, policy optimization is the \emph{de facto} paradigm to ada...
[ { "created": "Wed, 17 May 2023 17:48:24 GMT", "version": "v1" } ]
2023-05-18
[ [ "Ziesche", "Hanna", "" ], [ "Rozo", "Leonel", "" ] ]
Robots often rely on a repertoire of previously-learned motion policies for performing tasks of diverse complexities. When facing unseen task conditions or when new task requirements arise, robots must adapt their motion policies accordingly. In this context, policy optimization is the \emph{de facto} paradigm to adapt...
1801.09390
Yanning Shen
Yanning Shen, Panagiotis A. Traganitis, Georgios B. Giannakis
Nonlinear Dimensionality Reduction on Graphs
Dimensionality reduction, nonlinear modeling, signal processing over graphs
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this era of data deluge, many signal processing and machine learning tasks are faced with high-dimensional datasets, including images, videos, as well as time series generated from social, commercial and brain network interactions. Their efficient processing calls for dimensionality reduction techniques capable of...
[ { "created": "Mon, 29 Jan 2018 08:11:04 GMT", "version": "v1" }, { "created": "Thu, 29 Mar 2018 06:56:17 GMT", "version": "v2" } ]
2018-03-30
[ [ "Shen", "Yanning", "" ], [ "Traganitis", "Panagiotis A.", "" ], [ "Giannakis", "Georgios B.", "" ] ]
In this era of data deluge, many signal processing and machine learning tasks are faced with high-dimensional datasets, including images, videos, as well as time series generated from social, commercial and brain network interactions. Their efficient processing calls for dimensionality reduction techniques capable of p...
1609.02965
Ali Fatih Demir
A. Fatih Demir, Qammer H. Abbasi, Z. Esad Ankarali, Erchin Serpedin, Huseyin Arslan
Numerical Characterization of In Vivo Wireless Communication Channels
2014 IEEE MTT-S International Microwave Workshop Series on RF and Wireless Technologies for Biomedical and Healthcare Applications (IMWS-Bio)
2014 IEEE MTT-S International Microwave Workshop Series (IMWS-Bio), London, 2014, pp. 1-3
10.1109/IMWS-BIO.2014.7032392
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we numerically investigated the in vivo wireless communication channel for the human male torso at 915 MHz. The results show that in vivo channel is different from the classical communication channel, and location dependency is very critical for link budget calculations. A statistical path loss model b...
[ { "created": "Fri, 9 Sep 2016 22:53:23 GMT", "version": "v1" } ]
2016-09-13
[ [ "Demir", "A. Fatih", "" ], [ "Abbasi", "Qammer H.", "" ], [ "Ankarali", "Z. Esad", "" ], [ "Serpedin", "Erchin", "" ], [ "Arslan", "Huseyin", "" ] ]
In this paper, we numerically investigated the in vivo wireless communication channel for the human male torso at 915 MHz. The results show that in vivo channel is different from the classical communication channel, and location dependency is very critical for link budget calculations. A statistical path loss model bas...
2205.06811
Quanquan Gu
Jiafan He and Dongruo Zhou and Tong Zhang and Quanquan Gu
Nearly Optimal Algorithms for Linear Contextual Bandits with Adversarial Corruptions
25 pages, 1 table. This version simplifies the proof of the regret upper bound in Version 1, and provides a stronger result for the lower bound
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the linear contextual bandit problem in the presence of adversarial corruption, where the reward at each round is corrupted by an adversary, and the corruption level (i.e., the sum of corruption magnitudes over the horizon) is $C\geq 0$. The best-known algorithms in this setting are limited in that they eith...
[ { "created": "Fri, 13 May 2022 17:58:58 GMT", "version": "v1" }, { "created": "Sun, 10 Jul 2022 02:02:58 GMT", "version": "v2" } ]
2022-07-12
[ [ "He", "Jiafan", "" ], [ "Zhou", "Dongruo", "" ], [ "Zhang", "Tong", "" ], [ "Gu", "Quanquan", "" ] ]
We study the linear contextual bandit problem in the presence of adversarial corruption, where the reward at each round is corrupted by an adversary, and the corruption level (i.e., the sum of corruption magnitudes over the horizon) is $C\geq 0$. The best-known algorithms in this setting are limited in that they either...
2312.06581
Stella Biderman
Dashiell Stander and Qinan Yu and Honglu Fan and Stella Biderman
Grokking Group Multiplication with Cosets
null
null
null
null
cs.LG cs.AI math.RT
http://creativecommons.org/licenses/by/4.0/
The complex and unpredictable nature of deep neural networks prevents their safe use in many high-stakes applications. There have been many techniques developed to interpret deep neural networks, but all have substantial limitations. Algorithmic tasks have proven to be a fruitful test ground for interpreting a neural...
[ { "created": "Mon, 11 Dec 2023 18:12:18 GMT", "version": "v1" }, { "created": "Mon, 17 Jun 2024 17:44:44 GMT", "version": "v2" } ]
2024-06-18
[ [ "Stander", "Dashiell", "" ], [ "Yu", "Qinan", "" ], [ "Fan", "Honglu", "" ], [ "Biderman", "Stella", "" ] ]
The complex and unpredictable nature of deep neural networks prevents their safe use in many high-stakes applications. There have been many techniques developed to interpret deep neural networks, but all have substantial limitations. Algorithmic tasks have proven to be a fruitful test ground for interpreting a neural n...
1601.03783
Duygu Altinok
Duygu Altinok
Towards Turkish ASR: Anatomy of a rule-based Turkish g2p
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
This paper describes the architecture and implementation of a rule-based grapheme to phoneme converter for Turkish. The system accepts surface form as input, outputs SAMPA mapping of the all parallel pronounciations according to the morphological analysis together with stress positions. The system has been implemente...
[ { "created": "Fri, 15 Jan 2016 00:09:52 GMT", "version": "v1" } ]
2016-01-18
[ [ "Altinok", "Duygu", "" ] ]
This paper describes the architecture and implementation of a rule-based grapheme to phoneme converter for Turkish. The system accepts surface form as input, outputs SAMPA mapping of the all parallel pronounciations according to the morphological analysis together with stress positions. The system has been implemented ...
1910.05728
Badri Narayana Patro
Badri N. Patro, Shivansh Patel and Vinay P. Namboodiri
Granular Multimodal Attention Networks for Visual Dialog
ICCV Workshop
null
null
null
cs.CV cs.CL cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
Vision and language tasks have benefited from attention. There have been a number of different attention models proposed. However, the scale at which attention needs to be applied has not been well examined. Particularly, in this work, we propose a new method Granular Multi-modal Attention, where we aim to particular...
[ { "created": "Sun, 13 Oct 2019 10:49:41 GMT", "version": "v1" } ]
2019-10-15
[ [ "Patro", "Badri N.", "" ], [ "Patel", "Shivansh", "" ], [ "Namboodiri", "Vinay P.", "" ] ]
Vision and language tasks have benefited from attention. There have been a number of different attention models proposed. However, the scale at which attention needs to be applied has not been well examined. Particularly, in this work, we propose a new method Granular Multi-modal Attention, where we aim to particularly...
1104.4646
Nissim Halabi
Nissim Halabi and Guy Even
Local Optimality Certificates for LP Decoding of Tanner Codes
null
null
null
null
cs.IT math.CO math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a new combinatorial characterization for local optimality of a codeword in an irregular Tanner code. The main novelty in this characterization is that it is based on a linear combination of subtrees in the computation trees. These subtrees may have any degree in the local code nodes and may have any height...
[ { "created": "Sun, 24 Apr 2011 19:27:55 GMT", "version": "v1" } ]
2011-04-26
[ [ "Halabi", "Nissim", "" ], [ "Even", "Guy", "" ] ]
We present a new combinatorial characterization for local optimality of a codeword in an irregular Tanner code. The main novelty in this characterization is that it is based on a linear combination of subtrees in the computation trees. These subtrees may have any degree in the local code nodes and may have any height (...
1804.10188
Sahil Garg
Sahil Garg, Irina Rish, Guillermo Cecchi, Palash Goyal, Sarik Ghazarian, Shuyang Gao, Greg Ver Steeg, Aram Galstyan
Modeling Psychotherapy Dialogues with Kernelized Hashcode Representations: A Nonparametric Information-Theoretic Approach
Response generative based model added, along with human evaluation
null
null
null
cs.LG cs.AI cs.CL cs.IT math.IT stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a novel dialogue modeling framework, the first-ever nonparametric kernel functions based approach for dialogue modeling, which learns kernelized hashcodes as compressed text representations; unlike traditional deep learning models, it handles well relatively small datasets, while also scaling to large ones...
[ { "created": "Thu, 26 Apr 2018 17:39:28 GMT", "version": "v1" }, { "created": "Fri, 18 May 2018 00:32:09 GMT", "version": "v2" }, { "created": "Wed, 30 May 2018 03:58:19 GMT", "version": "v3" }, { "created": "Fri, 6 Jul 2018 14:54:22 GMT", "version": "v4" }, { "cr...
2019-09-11
[ [ "Garg", "Sahil", "" ], [ "Rish", "Irina", "" ], [ "Cecchi", "Guillermo", "" ], [ "Goyal", "Palash", "" ], [ "Ghazarian", "Sarik", "" ], [ "Gao", "Shuyang", "" ], [ "Steeg", "Greg Ver", "" ], [ "Gals...
We propose a novel dialogue modeling framework, the first-ever nonparametric kernel functions based approach for dialogue modeling, which learns kernelized hashcodes as compressed text representations; unlike traditional deep learning models, it handles well relatively small datasets, while also scaling to large ones. ...
2405.14847
Sai Bi
Liwen Wu, Sai Bi, Zexiang Xu, Fujun Luan, Kai Zhang, Iliyan Georgiev, Kalyan Sunkavalli, Ravi Ramamoorthi
Neural Directional Encoding for Efficient and Accurate View-Dependent Appearance Modeling
Accepted to CVPR 2024
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Novel-view synthesis of specular objects like shiny metals or glossy paints remains a significant challenge. Not only the glossy appearance but also global illumination effects, including reflections of other objects in the environment, are critical components to faithfully reproduce a scene. In this paper, we presen...
[ { "created": "Thu, 23 May 2024 17:56:34 GMT", "version": "v1" } ]
2024-05-24
[ [ "Wu", "Liwen", "" ], [ "Bi", "Sai", "" ], [ "Xu", "Zexiang", "" ], [ "Luan", "Fujun", "" ], [ "Zhang", "Kai", "" ], [ "Georgiev", "Iliyan", "" ], [ "Sunkavalli", "Kalyan", "" ], [ "Ramamoorthi", ...
Novel-view synthesis of specular objects like shiny metals or glossy paints remains a significant challenge. Not only the glossy appearance but also global illumination effects, including reflections of other objects in the environment, are critical components to faithfully reproduce a scene. In this paper, we present ...
1909.09248
Wei-Hung Weng
Wei-Hung Weng, Peter Szolovits
Representation Learning for Electronic Health Records
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Information in electronic health records (EHR), such as clinical narratives, examination reports, lab measurements, demographics, and other patient encounter entries, can be transformed into appropriate data representations that can be used for downstream clinical machine learning tasks using representation learning....
[ { "created": "Thu, 19 Sep 2019 22:12:30 GMT", "version": "v1" } ]
2019-09-23
[ [ "Weng", "Wei-Hung", "" ], [ "Szolovits", "Peter", "" ] ]
Information in electronic health records (EHR), such as clinical narratives, examination reports, lab measurements, demographics, and other patient encounter entries, can be transformed into appropriate data representations that can be used for downstream clinical machine learning tasks using representation learning. L...
1409.5583
Mohamed Khalil
Mohamed Amir, Tamer Khattab, Tarek Elfouly, Amr Mohamed
Secure Degrees of Freedom of the Gaussian MIMO Wiretap and MIMO Broadcast Channels with Unknown Eavesdroppers
arXiv admin note: text overlap with arXiv:1404.5007
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the secure degrees of freedom (SDoF) of the wiretap and the K user Gaussian broadcast channels with multiple antennas at the transmitter, the legitimate receivers and an unknown number of eavesdroppers each with a number of antennas less than or equal to a known value NE. The channel matrices between t...
[ { "created": "Fri, 19 Sep 2014 10:29:58 GMT", "version": "v1" }, { "created": "Fri, 26 Sep 2014 11:28:51 GMT", "version": "v2" }, { "created": "Thu, 26 Feb 2015 15:10:00 GMT", "version": "v3" }, { "created": "Wed, 30 Mar 2016 20:38:15 GMT", "version": "v4" } ]
2016-04-01
[ [ "Amir", "Mohamed", "" ], [ "Khattab", "Tamer", "" ], [ "Elfouly", "Tarek", "" ], [ "Mohamed", "Amr", "" ] ]
We investigate the secure degrees of freedom (SDoF) of the wiretap and the K user Gaussian broadcast channels with multiple antennas at the transmitter, the legitimate receivers and an unknown number of eavesdroppers each with a number of antennas less than or equal to a known value NE. The channel matrices between the...
2211.11870
Fengyi Shen
Fengyi Shen, Zador Pataki, Akhil Gurram, Ziyuan Liu, He Wang, Alois Knoll
LoopDA: Constructing Self-loops to Adapt Nighttime Semantic Segmentation
Accepted to WACV2023
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
null
null
cs.CV
http://creativecommons.org/licenses/by-sa/4.0/
Due to the lack of training labels and the difficulty of annotating, dealing with adverse driving conditions such as nighttime has posed a huge challenge to the perception system of autonomous vehicles. Therefore, adapting knowledge from a labelled daytime domain to an unlabelled nighttime domain has been widely rese...
[ { "created": "Mon, 21 Nov 2022 21:46:05 GMT", "version": "v1" } ]
2022-11-23
[ [ "Shen", "Fengyi", "" ], [ "Pataki", "Zador", "" ], [ "Gurram", "Akhil", "" ], [ "Liu", "Ziyuan", "" ], [ "Wang", "He", "" ], [ "Knoll", "Alois", "" ] ]
Due to the lack of training labels and the difficulty of annotating, dealing with adverse driving conditions such as nighttime has posed a huge challenge to the perception system of autonomous vehicles. Therefore, adapting knowledge from a labelled daytime domain to an unlabelled nighttime domain has been widely resear...
1604.07319
Mehrdad Gangeh
Mehrdad J. Gangeh, Safaa M.A. Bedawi, Ali Ghodsi, Fakhri Karray
Semi-supervised Dictionary Learning Based on Hilbert-Schmidt Independence Criterion
Accepted at International conference on Image analysis and Recognition (ICIAR) 2016
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, a novel semi-supervised dictionary learning and sparse representation (SS-DLSR) is proposed. The proposed method benefits from the supervisory information by learning the dictionary in a space where the dependency between the data and class labels is maximized. This maximization is performed using Hilb...
[ { "created": "Mon, 25 Apr 2016 16:25:38 GMT", "version": "v1" } ]
2016-04-26
[ [ "Gangeh", "Mehrdad J.", "" ], [ "Bedawi", "Safaa M. A.", "" ], [ "Ghodsi", "Ali", "" ], [ "Karray", "Fakhri", "" ] ]
In this paper, a novel semi-supervised dictionary learning and sparse representation (SS-DLSR) is proposed. The proposed method benefits from the supervisory information by learning the dictionary in a space where the dependency between the data and class labels is maximized. This maximization is performed using Hilber...
2311.03382
Hangtong Xu
Hangtong Xu and Yuanbo Xu and Yongjian Yang
Causal Structure Representation Learning of Confounders in Latent Space for Recommendation
null
null
null
null
cs.IR cs.AI cs.LG stat.ME
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Inferring user preferences from the historical feedback of users is a valuable problem in recommender systems. Conventional approaches often rely on the assumption that user preferences in the feedback data are equivalent to the real user preferences without additional noise, which simplifies the problem modeling. Ho...
[ { "created": "Thu, 2 Nov 2023 08:46:07 GMT", "version": "v1" } ]
2023-11-08
[ [ "Xu", "Hangtong", "" ], [ "Xu", "Yuanbo", "" ], [ "Yang", "Yongjian", "" ] ]
Inferring user preferences from the historical feedback of users is a valuable problem in recommender systems. Conventional approaches often rely on the assumption that user preferences in the feedback data are equivalent to the real user preferences without additional noise, which simplifies the problem modeling. Howe...
2403.03707
Yajie Liu
Yajie Liu, Pu Ge, Qingjie Liu, Di Huang
Multi-Grained Cross-modal Alignment for Learning Open-vocabulary Semantic Segmentation from Text Supervision
17 pages, 8 figures
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Recently, learning open-vocabulary semantic segmentation from text supervision has achieved promising downstream performance. Nevertheless, current approaches encounter an alignment granularity gap owing to the absence of dense annotations, wherein they learn coarse image/region-text alignment during training yet per...
[ { "created": "Wed, 6 Mar 2024 13:43:36 GMT", "version": "v1" } ]
2024-03-07
[ [ "Liu", "Yajie", "" ], [ "Ge", "Pu", "" ], [ "Liu", "Qingjie", "" ], [ "Huang", "Di", "" ] ]
Recently, learning open-vocabulary semantic segmentation from text supervision has achieved promising downstream performance. Nevertheless, current approaches encounter an alignment granularity gap owing to the absence of dense annotations, wherein they learn coarse image/region-text alignment during training yet perfo...
2104.08899
Decky Aspandi
Decky Aspandi-Latif, Sally Goldin, Preesan Rakwatin, Kurt Rudahl
Texture Based Classification of High Resolution Remotely Sensed Imagery using Weber Local Descriptor
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Traditional image classification techniques often produce unsatisfactory results when applied to high spatial resolution data because classes in high resolution images are not spectrally homogeneous. Texture offers an alternative source of information for classifying these images. This paper evaluates a recently deve...
[ { "created": "Sun, 18 Apr 2021 16:37:34 GMT", "version": "v1" } ]
2021-04-20
[ [ "Aspandi-Latif", "Decky", "" ], [ "Goldin", "Sally", "" ], [ "Rakwatin", "Preesan", "" ], [ "Rudahl", "Kurt", "" ] ]
Traditional image classification techniques often produce unsatisfactory results when applied to high spatial resolution data because classes in high resolution images are not spectrally homogeneous. Texture offers an alternative source of information for classifying these images. This paper evaluates a recently develo...
2211.00519
Yanran Guan
Yanran Guan, Andrei Chubarau, Ruby Rao, Derek Nowrouzezahrai
Learning Neural Implicit Representations with Surface Signal Parameterizations
null
null
null
null
cs.GR cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Neural implicit surface representations have recently emerged as popular alternative to explicit 3D object encodings, such as polygonal meshes, tabulated points, or voxels. While significant work has improved the geometric fidelity of these representations, much less attention is given to their final appearance. Trad...
[ { "created": "Tue, 1 Nov 2022 15:10:58 GMT", "version": "v1" }, { "created": "Mon, 26 Jun 2023 00:32:56 GMT", "version": "v2" } ]
2023-06-27
[ [ "Guan", "Yanran", "" ], [ "Chubarau", "Andrei", "" ], [ "Rao", "Ruby", "" ], [ "Nowrouzezahrai", "Derek", "" ] ]
Neural implicit surface representations have recently emerged as popular alternative to explicit 3D object encodings, such as polygonal meshes, tabulated points, or voxels. While significant work has improved the geometric fidelity of these representations, much less attention is given to their final appearance. Tradit...
1411.3716
Mahmood Mohassel Feghhi
Mahmood Mohassel Feghhi, Mahtab Mirmohseni, Aliazam Abbasfar
Power Allocation in the Energy Harvesting Full-Duplex Gaussian Relay Channels
Accepted for publication in International Journal of Communication Systems (Special Issue on Energy Efficient Wireless Communication Networks with QoS), October 2014
International Journal of Communication Systems, Vol. 30, No. 2, Jan 2017
10.1002/dac.2903
null
cs.NI cs.ET cs.IT math.IT math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a general model to study the full-duplex non-coherent decode-and-forward Gaussian relay channel with energy harvesting (EH) nodes, called NC-EH-$\mathcal{RC}$, in three cases: $i)$ no energy transfer (ET), $ii)$ one-way ET from the source (S) to the relay (R), and $iii)$ two-way ET. We consi...
[ { "created": "Fri, 14 Nov 2014 08:17:31 GMT", "version": "v1" } ]
2021-04-07
[ [ "Feghhi", "Mahmood Mohassel", "" ], [ "Mirmohseni", "Mahtab", "" ], [ "Abbasfar", "Aliazam", "" ] ]
In this paper, we propose a general model to study the full-duplex non-coherent decode-and-forward Gaussian relay channel with energy harvesting (EH) nodes, called NC-EH-$\mathcal{RC}$, in three cases: $i)$ no energy transfer (ET), $ii)$ one-way ET from the source (S) to the relay (R), and $iii)$ two-way ET. We conside...
2008.01558
Yanmin Gong
Rui Hu and Yanmin Gong and Yuanxiong Guo
Federated Learning with Sparsification-Amplified Privacy and Adaptive Optimization
Accepted in IJCAI 2021, this is the full version with appendix
null
null
null
cs.LG cs.CR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Federated learning (FL) enables distributed agents to collaboratively learn a centralized model without sharing their raw data with each other. However, data locality does not provide sufficient privacy protection, and it is desirable to facilitate FL with rigorous differential privacy (DP) guarantee. Existing DP mec...
[ { "created": "Sat, 1 Aug 2020 20:22:57 GMT", "version": "v1" }, { "created": "Tue, 8 Jun 2021 20:18:08 GMT", "version": "v2" } ]
2021-06-15
[ [ "Hu", "Rui", "" ], [ "Gong", "Yanmin", "" ], [ "Guo", "Yuanxiong", "" ] ]
Federated learning (FL) enables distributed agents to collaboratively learn a centralized model without sharing their raw data with each other. However, data locality does not provide sufficient privacy protection, and it is desirable to facilitate FL with rigorous differential privacy (DP) guarantee. Existing DP mecha...
1209.1960
M. Emre Celebi
M. Emre Celebi, Hassan A. Kingravi, Patricio A. Vela
A Comparative Study of Efficient Initialization Methods for the K-Means Clustering Algorithm
17 pages, 1 figure, 7 tables
Expert Systems with Applications 40 (2013) 200-210
10.1016/j.eswa.2012.07.021
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
K-means is undoubtedly the most widely used partitional clustering algorithm. Unfortunately, due to its gradient descent nature, this algorithm is highly sensitive to the initial placement of the cluster centers. Numerous initialization methods have been proposed to address this problem. In this paper, we first prese...
[ { "created": "Mon, 10 Sep 2012 12:22:06 GMT", "version": "v1" } ]
2012-09-11
[ [ "Celebi", "M. Emre", "" ], [ "Kingravi", "Hassan A.", "" ], [ "Vela", "Patricio A.", "" ] ]
K-means is undoubtedly the most widely used partitional clustering algorithm. Unfortunately, due to its gradient descent nature, this algorithm is highly sensitive to the initial placement of the cluster centers. Numerous initialization methods have been proposed to address this problem. In this paper, we first present...
2203.16648
Abigail Lee
Abigail J. Lee, Grace E. Chesmore, Kyle A. Rocha, Amanda Farah, Maryum Sayeed, Justin Myles
Predicting Winners of the Reality TV Dating Show $\textit{The Bachelor}$ Using Machine Learning Algorithms
6 Pages, 5 Figures. Submitted to Acta Prima Aprila. Code used in this work available at http://github.com/chesmore/bach-stats/
null
null
null
cs.LG astro-ph.IM physics.pop-ph
http://creativecommons.org/licenses/by/4.0/
$\textit{The Bachelor}$ is a reality TV dating show in which a single bachelor selects his wife from a pool of approximately 30 female contestants over eight weeks of filming (American Broadcasting Company 2002). We collected the following data on all 422 contestants that participated in seasons 11 through 25: their ...
[ { "created": "Wed, 30 Mar 2022 20:00:31 GMT", "version": "v1" } ]
2022-04-01
[ [ "Lee", "Abigail J.", "" ], [ "Chesmore", "Grace E.", "" ], [ "Rocha", "Kyle A.", "" ], [ "Farah", "Amanda", "" ], [ "Sayeed", "Maryum", "" ], [ "Myles", "Justin", "" ] ]
$\textit{The Bachelor}$ is a reality TV dating show in which a single bachelor selects his wife from a pool of approximately 30 female contestants over eight weeks of filming (American Broadcasting Company 2002). We collected the following data on all 422 contestants that participated in seasons 11 through 25: their Ag...
1801.03595
Junting Chen
Junting Chen and David Gesbert
Efficient Local Map Search Algorithms for the Placement of Flying Relays
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper studies the optimal unmanned aerial vehicle (UAV) placement problem for wireless networking. The UAV operates as a flying wireless relay to provide coverage extension for a base station (BS) and deliver capacity boost to a user shadowed by obstacles. While existing methods rely on statistical models for po...
[ { "created": "Thu, 11 Jan 2018 00:26:11 GMT", "version": "v1" }, { "created": "Thu, 31 Oct 2019 06:33:09 GMT", "version": "v2" } ]
2019-11-01
[ [ "Chen", "Junting", "" ], [ "Gesbert", "David", "" ] ]
This paper studies the optimal unmanned aerial vehicle (UAV) placement problem for wireless networking. The UAV operates as a flying wireless relay to provide coverage extension for a base station (BS) and deliver capacity boost to a user shadowed by obstacles. While existing methods rely on statistical models for pote...
1710.04133
Emanuele Massaro Ph.D.
Umberto Fugiglando, Emanuele Massaro, Paolo Santi, Sebastiano Milardo, Kacem Abida, Rainer Stahlmann, Florian Netter, Carlo Ratti
Driving Behavior Analysis through CAN Bus Data in an Uncontrolled Environment
null
null
null
null
cs.LG cs.CY physics.data-an
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cars can nowadays record several thousands of signals through the CAN bus technology and potentially provide real-time information on the car, the driver and the surrounding environment. This paper proposes a new method for the analysis and classification of driver behavior using a selected subset of CAN bus signals,...
[ { "created": "Mon, 9 Oct 2017 09:58:23 GMT", "version": "v1" } ]
2017-10-12
[ [ "Fugiglando", "Umberto", "" ], [ "Massaro", "Emanuele", "" ], [ "Santi", "Paolo", "" ], [ "Milardo", "Sebastiano", "" ], [ "Abida", "Kacem", "" ], [ "Stahlmann", "Rainer", "" ], [ "Netter", "Florian", "" ...
Cars can nowadays record several thousands of signals through the CAN bus technology and potentially provide real-time information on the car, the driver and the surrounding environment. This paper proposes a new method for the analysis and classification of driver behavior using a selected subset of CAN bus signals, s...
2202.02790
Fabio Ferreira
Fabio Ferreira and Thomas Nierhoff and Andreas Saelinger and Frank Hutter
Learning Synthetic Environments and Reward Networks for Reinforcement Learning
null
International Conference on Learning Representations (ICLR 2022)
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
We introduce Synthetic Environments (SEs) and Reward Networks (RNs), represented by neural networks, as proxy environment models for training Reinforcement Learning (RL) agents. We show that an agent, after being trained exclusively on the SE, is able to solve the corresponding real environment. While an SE acts as a...
[ { "created": "Sun, 6 Feb 2022 14:55:59 GMT", "version": "v1" } ]
2022-02-08
[ [ "Ferreira", "Fabio", "" ], [ "Nierhoff", "Thomas", "" ], [ "Saelinger", "Andreas", "" ], [ "Hutter", "Frank", "" ] ]
We introduce Synthetic Environments (SEs) and Reward Networks (RNs), represented by neural networks, as proxy environment models for training Reinforcement Learning (RL) agents. We show that an agent, after being trained exclusively on the SE, is able to solve the corresponding real environment. While an SE acts as a f...
2405.05736
Shashank Gupta
Shashank Gupta, Olivier Jeunen, Harrie Oosterhuis, and Maarten de Rijke
Optimal Baseline Corrections for Off-Policy Contextual Bandits
null
null
10.1145/3640457.3688105
null
cs.LG cs.IR
http://creativecommons.org/licenses/by/4.0/
The off-policy learning paradigm allows for recommender systems and general ranking applications to be framed as decision-making problems, where we aim to learn decision policies that optimize an unbiased offline estimate of an online reward metric. With unbiasedness comes potentially high variance, and prevalent met...
[ { "created": "Thu, 9 May 2024 12:52:22 GMT", "version": "v1" }, { "created": "Wed, 14 Aug 2024 14:14:02 GMT", "version": "v2" } ]
2024-08-15
[ [ "Gupta", "Shashank", "" ], [ "Jeunen", "Olivier", "" ], [ "Oosterhuis", "Harrie", "" ], [ "de Rijke", "Maarten", "" ] ]
The off-policy learning paradigm allows for recommender systems and general ranking applications to be framed as decision-making problems, where we aim to learn decision policies that optimize an unbiased offline estimate of an online reward metric. With unbiasedness comes potentially high variance, and prevalent metho...
1708.05682
Lu Huang
Lu Huang, Jiasong Sun, Ji Xu and Yi Yang
An Improved Residual LSTM Architecture for Acoustic Modeling
5 pages, 2 figures
null
null
null
cs.CL cs.AI cs.SD
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Long Short-Term Memory (LSTM) is the primary recurrent neural networks architecture for acoustic modeling in automatic speech recognition systems. Residual learning is an efficient method to help neural networks converge easier and faster. In this paper, we propose several types of residual LSTM methods for our acous...
[ { "created": "Thu, 17 Aug 2017 01:37:21 GMT", "version": "v1" } ]
2017-08-21
[ [ "Huang", "Lu", "" ], [ "Sun", "Jiasong", "" ], [ "Xu", "Ji", "" ], [ "Yang", "Yi", "" ] ]
Long Short-Term Memory (LSTM) is the primary recurrent neural networks architecture for acoustic modeling in automatic speech recognition systems. Residual learning is an efficient method to help neural networks converge easier and faster. In this paper, we propose several types of residual LSTM methods for our acousti...
2403.08002
Juan Manuel Zambrano Chaves
Juan Manuel Zambrano Chaves, Shih-Cheng Huang, Yanbo Xu, Hanwen Xu, Naoto Usuyama, Sheng Zhang, Fei Wang, Yujia Xie, Mahmoud Khademi, Ziyi Yang, Hany Awadalla, Julia Gong, Houdong Hu, Jianwei Yang, Chunyuan Li, Jianfeng Gao, Yu Gu, Cliff Wong, Mu Wei, Tristan Naumann, Muhao Chen, Matthew P. Lungren, Akshay Chau...
Towards a clinically accessible radiology foundation model: open-access and lightweight, with automated evaluation
null
null
null
null
cs.CL cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The scaling laws and extraordinary performance of large foundation models motivate the development and utilization of such models in biomedicine. However, despite early promising results on some biomedical benchmarks, there are still major challenges that need to be addressed before these models can be used in real-w...
[ { "created": "Tue, 12 Mar 2024 18:12:02 GMT", "version": "v1" }, { "created": "Wed, 20 Mar 2024 23:31:22 GMT", "version": "v2" }, { "created": "Sat, 4 May 2024 00:35:01 GMT", "version": "v3" }, { "created": "Fri, 10 May 2024 23:46:33 GMT", "version": "v4" }, { "cr...
2024-06-28
[ [ "Chaves", "Juan Manuel Zambrano", "" ], [ "Huang", "Shih-Cheng", "" ], [ "Xu", "Yanbo", "" ], [ "Xu", "Hanwen", "" ], [ "Usuyama", "Naoto", "" ], [ "Zhang", "Sheng", "" ], [ "Wang", "Fei", "" ], [ "...
The scaling laws and extraordinary performance of large foundation models motivate the development and utilization of such models in biomedicine. However, despite early promising results on some biomedical benchmarks, there are still major challenges that need to be addressed before these models can be used in real-wor...
2201.09329
Olga Kononova
Zheren Wang, Kevin Cruse, Yuxing Fei, Ann Chia, Yan Zeng, Haoyan Huo, Tanjin He, Bowen Deng, Olga Kononova and Gerbrand Ceder
ULSA: Unified Language of Synthesis Actions for Representation of Synthesis Protocols
null
null
null
null
cs.LG cond-mat.mtrl-sci
http://creativecommons.org/licenses/by/4.0/
Applying AI power to predict syntheses of novel materials requires high-quality, large-scale datasets. Extraction of synthesis information from scientific publications is still challenging, especially for extracting synthesis actions, because of the lack of a comprehensive labeled dataset using a solid, robust, and w...
[ { "created": "Sun, 23 Jan 2022 17:44:48 GMT", "version": "v1" } ]
2022-01-25
[ [ "Wang", "Zheren", "" ], [ "Cruse", "Kevin", "" ], [ "Fei", "Yuxing", "" ], [ "Chia", "Ann", "" ], [ "Zeng", "Yan", "" ], [ "Huo", "Haoyan", "" ], [ "He", "Tanjin", "" ], [ "Deng", "Bowen", "...
Applying AI power to predict syntheses of novel materials requires high-quality, large-scale datasets. Extraction of synthesis information from scientific publications is still challenging, especially for extracting synthesis actions, because of the lack of a comprehensive labeled dataset using a solid, robust, and wel...
2107.14050
Ali Shahaab
Ali Shahaab, Chaminda Hewage, Imtiaz Khan
Preventing Spoliation of Evidence with Blockchain: A Perspective from South Asia
ICBCT21, March 26-28, 2021, Shanghai, China
null
null
null
cs.CY
http://creativecommons.org/licenses/by/4.0/
Evidence destruction and tempering is a time-tested tactic to protect the powerful perpetrators, criminals, and corrupt officials. Countries where law enforcing institutions and judicial system can be comprised, and evidence destroyed or tampered, ordinary citizens feel disengaged with the investigation or prosecutio...
[ { "created": "Wed, 14 Jul 2021 11:59:12 GMT", "version": "v1" } ]
2021-07-30
[ [ "Shahaab", "Ali", "" ], [ "Hewage", "Chaminda", "" ], [ "Khan", "Imtiaz", "" ] ]
Evidence destruction and tempering is a time-tested tactic to protect the powerful perpetrators, criminals, and corrupt officials. Countries where law enforcing institutions and judicial system can be comprised, and evidence destroyed or tampered, ordinary citizens feel disengaged with the investigation or prosecution ...
1812.04647
Ankur Gandhe
Ankur Gandhe, Ariya Rastrow, Bjorn Hoffmeister
Scalable language model adaptation for spoken dialogue systems
Accepted at SLT 2018
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Language models (LM) for interactive speech recognition systems are trained on large amounts of data and the model parameters are optimized on past user data. New application intents and interaction types are released for these systems over time, imposing challenges to adapt the LMs since the existing training data i...
[ { "created": "Tue, 11 Dec 2018 19:02:05 GMT", "version": "v1" } ]
2018-12-13
[ [ "Gandhe", "Ankur", "" ], [ "Rastrow", "Ariya", "" ], [ "Hoffmeister", "Bjorn", "" ] ]
Language models (LM) for interactive speech recognition systems are trained on large amounts of data and the model parameters are optimized on past user data. New application intents and interaction types are released for these systems over time, imposing challenges to adapt the LMs since the existing training data is ...
0805.0648
Mathieu Bredif
Mathieu Br\'edif, Dider Boldo, Marc Pierrot-Deseilligny, Henri Ma\^itre
3D Building Model Fitting Using A New Kinetic Framework
null
null
null
null
cs.CG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We describe a new approach to fit the polyhedron describing a 3D building model to the point cloud of a Digital Elevation Model (DEM). We introduce a new kinetic framework that hides to its user the combinatorial complexity of determining or maintaining the polyhedron topology, allowing the design of a simple variati...
[ { "created": "Tue, 6 May 2008 06:34:31 GMT", "version": "v1" } ]
2008-12-18
[ [ "Brédif", "Mathieu", "" ], [ "Boldo", "Dider", "" ], [ "Pierrot-Deseilligny", "Marc", "" ], [ "Maître", "Henri", "" ] ]
We describe a new approach to fit the polyhedron describing a 3D building model to the point cloud of a Digital Elevation Model (DEM). We introduce a new kinetic framework that hides to its user the combinatorial complexity of determining or maintaining the polyhedron topology, allowing the design of a simple variation...
2205.10822
Li Du
Li Du, Xiao Ding, Yue Zhang, Kai Xiong, Ting Liu, Bing Qin
A Graph Enhanced BERT Model for Event Prediction
null
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Predicting the subsequent event for an existing event context is an important but challenging task, as it requires understanding the underlying relationship between events. Previous methods propose to retrieve relational features from event graph to enhance the modeling of event correlation. However, the sparsity of ...
[ { "created": "Sun, 22 May 2022 13:37:38 GMT", "version": "v1" } ]
2022-05-24
[ [ "Du", "Li", "" ], [ "Ding", "Xiao", "" ], [ "Zhang", "Yue", "" ], [ "Xiong", "Kai", "" ], [ "Liu", "Ting", "" ], [ "Qin", "Bing", "" ] ]
Predicting the subsequent event for an existing event context is an important but challenging task, as it requires understanding the underlying relationship between events. Previous methods propose to retrieve relational features from event graph to enhance the modeling of event correlation. However, the sparsity of ev...
2108.09604
Lili Su
Lili Su, Quanquan C. Liu, Neha Narula
The Power of Random Symmetry-Breaking in Nakamoto Consensus
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Nakamoto consensus underlies the security of many of the world's largest cryptocurrencies, such as Bitcoin and Ethereum. Common lore is that Nakamoto consensus only achieves consistency and liveness under a regime where the difficulty of its underlying mining puzzle is very high, negatively impacting overall throughp...
[ { "created": "Sun, 22 Aug 2021 00:18:44 GMT", "version": "v1" } ]
2021-08-24
[ [ "Su", "Lili", "" ], [ "Liu", "Quanquan C.", "" ], [ "Narula", "Neha", "" ] ]
Nakamoto consensus underlies the security of many of the world's largest cryptocurrencies, such as Bitcoin and Ethereum. Common lore is that Nakamoto consensus only achieves consistency and liveness under a regime where the difficulty of its underlying mining puzzle is very high, negatively impacting overall throughput...
1808.08573
Zied Elloumi
Zied Elloumi, Laurent Besacier, Olivier Galibert, Benjamin Lecouteux
Analyzing Learned Representations of a Deep ASR Performance Prediction Model
EMNLP 2018 Workshop
null
null
null
cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
This paper addresses a relatively new task: prediction of ASR performance on unseen broadcast programs. In a previous paper, we presented an ASR performance prediction system using CNNs that encode both text (ASR transcript) and speech, in order to predict word error rate. This work is dedicated to the analysis of sp...
[ { "created": "Sun, 26 Aug 2018 15:10:47 GMT", "version": "v1" }, { "created": "Tue, 28 Aug 2018 09:59:05 GMT", "version": "v2" } ]
2018-08-29
[ [ "Elloumi", "Zied", "" ], [ "Besacier", "Laurent", "" ], [ "Galibert", "Olivier", "" ], [ "Lecouteux", "Benjamin", "" ] ]
This paper addresses a relatively new task: prediction of ASR performance on unseen broadcast programs. In a previous paper, we presented an ASR performance prediction system using CNNs that encode both text (ASR transcript) and speech, in order to predict word error rate. This work is dedicated to the analysis of spee...
2407.14108
Florian Chabot
Florian Chabot, Nicolas Granger, Guillaume Lapouge
GaussianBeV: 3D Gaussian Representation meets Perception Models for BeV Segmentation
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Bird's-eye View (BeV) representation is widely used for 3D perception from multi-view camera images. It allows to merge features from different cameras into a common space, providing a unified representation of the 3D scene. The key component is the view transformer, which transforms image views into the BeV. How...
[ { "created": "Fri, 19 Jul 2024 08:24:36 GMT", "version": "v1" } ]
2024-07-22
[ [ "Chabot", "Florian", "" ], [ "Granger", "Nicolas", "" ], [ "Lapouge", "Guillaume", "" ] ]
The Bird's-eye View (BeV) representation is widely used for 3D perception from multi-view camera images. It allows to merge features from different cameras into a common space, providing a unified representation of the 3D scene. The key component is the view transformer, which transforms image views into the BeV. Howev...
cs/0602075
Peter Jonsson
Vladimir Deineko, Peter Jonsson, Mikael Klasson, and Andrei Krokhin
The approximability of MAX CSP with fixed-value constraints
null
null
null
null
cs.CC
null
In the maximum constraint satisfaction problem (MAX CSP), one is given a finite collection of (possibly weighted) constraints on overlapping sets of variables, and the goal is to assign values from a given finite domain to the variables so as to maximize the number (or the total weight, for the weighted case) of sati...
[ { "created": "Tue, 21 Feb 2006 14:13:37 GMT", "version": "v1" } ]
2007-05-23
[ [ "Deineko", "Vladimir", "" ], [ "Jonsson", "Peter", "" ], [ "Klasson", "Mikael", "" ], [ "Krokhin", "Andrei", "" ] ]
In the maximum constraint satisfaction problem (MAX CSP), one is given a finite collection of (possibly weighted) constraints on overlapping sets of variables, and the goal is to assign values from a given finite domain to the variables so as to maximize the number (or the total weight, for the weighted case) of satisf...
2406.07209
Siming Fu
X. Wang, Siming Fu, Qihan Huang, Wanggui He, Hao Jiang
MS-Diffusion: Multi-subject Zero-shot Image Personalization with Layout Guidance
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Recent advancements in text-to-image generation models have dramatically enhanced the generation of photorealistic images from textual prompts, leading to an increased interest in personalized text-to-image applications, particularly in multi-subject scenarios. However, these advances are hindered by two main challen...
[ { "created": "Tue, 11 Jun 2024 12:32:53 GMT", "version": "v1" } ]
2024-06-12
[ [ "Wang", "X.", "" ], [ "Fu", "Siming", "" ], [ "Huang", "Qihan", "" ], [ "He", "Wanggui", "" ], [ "Jiang", "Hao", "" ] ]
Recent advancements in text-to-image generation models have dramatically enhanced the generation of photorealistic images from textual prompts, leading to an increased interest in personalized text-to-image applications, particularly in multi-subject scenarios. However, these advances are hindered by two main challenge...
2203.12647
Nicky Zimmerman
Nicky Zimmerman, Louis Wiesmann, Tiziano Guadagnino, Thomas L\"abe, Jens Behley, Cyrill Stachniss
Robust Onboard Localization in Changing Environments Exploiting Text Spotting
This work has been accepted to IROS 2022. Copyright may be transferred without notice, after which this version may no longer be accessible
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Robust localization in a given map is a crucial component of most autonomous robots. In this paper, we address the problem of localizing in an indoor environment that changes and where prominent structures have no correspondence in the map built at a different point in time. To overcome the discrepancy between the ma...
[ { "created": "Wed, 23 Mar 2022 18:12:48 GMT", "version": "v1" }, { "created": "Sat, 23 Jul 2022 09:40:34 GMT", "version": "v2" } ]
2022-07-26
[ [ "Zimmerman", "Nicky", "" ], [ "Wiesmann", "Louis", "" ], [ "Guadagnino", "Tiziano", "" ], [ "Läbe", "Thomas", "" ], [ "Behley", "Jens", "" ], [ "Stachniss", "Cyrill", "" ] ]
Robust localization in a given map is a crucial component of most autonomous robots. In this paper, we address the problem of localizing in an indoor environment that changes and where prominent structures have no correspondence in the map built at a different point in time. To overcome the discrepancy between the map ...
1606.05675
Chang Liu
Chang Liu, Yu Cao, Yan Luo, Guanling Chen, Vinod Vokkarane and Yunsheng Ma
DeepFood: Deep Learning-Based Food Image Recognition for Computer-Aided Dietary Assessment
12 pages, 2 figures, 6 tables, ICOST 2016
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
Worldwide, in 2014, more than 1.9 billion adults, 18 years and older, were overweight. Of these, over 600 million were obese. Accurately documenting dietary caloric intake is crucial to manage weight loss, but also presents challenges because most of the current methods for dietary assessment must rely on memory to r...
[ { "created": "Fri, 17 Jun 2016 21:03:19 GMT", "version": "v1" } ]
2016-06-21
[ [ "Liu", "Chang", "" ], [ "Cao", "Yu", "" ], [ "Luo", "Yan", "" ], [ "Chen", "Guanling", "" ], [ "Vokkarane", "Vinod", "" ], [ "Ma", "Yunsheng", "" ] ]
Worldwide, in 2014, more than 1.9 billion adults, 18 years and older, were overweight. Of these, over 600 million were obese. Accurately documenting dietary caloric intake is crucial to manage weight loss, but also presents challenges because most of the current methods for dietary assessment must rely on memory to rec...