Machine Learning

Papers filed under cs.LG on arXiv, each one already summarized by Paperlayer. Open any of them to read the summary beside the original PDF, with every point linked to the line, figure, or table it came from.

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12,001 to 12,060 of 20,193

Challenges and Opportunities in Quantum Machine Learning
M. Cerezo, Guillaume Verdon, Hsin-Yuan Huang +2
quant-phcs.LGstat.MLarXiv:2303.09491v12023
Quantum advantage in learning from experiments
Hsin-Yuan Huang, Michael Broughton, Jordan Cotler +8
quant-phcs.ITcs.LGarXiv:2112.00778v12021
Noise-Induced Barren Plateaus in Variational Quantum Algorithms
Samson Wang, Enrico Fontana, M. Cerezo +4
quant-phcs.LGarXiv:2007.14384v62020
Layerwise learning for quantum neural networks
Andrea Skolik, Jarrod R. McClean, Masoud Mohseni +2
quant-phcs.LGarXiv:2006.14904v12020
Physical reservoir computing -- An introductory perspective
Kohei Nakajima
nlin.AOcs.LGphysics.app-pharXiv:2005.00992v12020
Robust data encodings for quantum classifiers
Ryan LaRose, Brian Coyle
quant-phcs.LGarXiv:2003.01695v12020
AnatomyNet: Deep Learning for Fast and Fully Automated Whole-volume Segmentation of Head and Neck Anatomy
Wentao Zhu, Yufang Huang, Liang Zeng +6
cs.CVcs.LGcs.NEarXiv:1808.05238v22018
Quantum generative adversarial networks
Pierre-Luc Dallaire-Demers, Nathan Killoran
quant-phcs.LGarXiv:1804.08641v22018
Towards Quantum Machine Learning with Tensor Networks
William Huggins, Piyush Patel, K. Birgitta Whaley +1
quant-phcond-mat.str-elcs.LGarXiv:1803.11537v22018
CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks
Michela Paganini, Luke de Oliveira, Benjamin Nachman
hep-excs.LGhep-pharXiv:1712.10321v12017
Entity Embeddings of Categorical Variables
Cheng Guo, Felix Berkhahn
cs.LGarXiv:1604.06737v12016
An Efficiency-boosting Client Selection Scheme for Federated Learning with Fairness Guarantee
Tiansheng Huang, Weiwei Lin, Wentai Wu +3
cs.LGcs.DCarXiv:2011.01783v52020
Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks
Dongkun Zhang, Ling Guo, George Em Karniadakis
cs.LGmath.NAphysics.comp-pharXiv:1905.01205v22019
Neural Logic Machines
Honghua Dong, Jiayuan Mao, Tian Lin +3
cs.AIcs.LGstat.MLarXiv:1904.11694v12019
Augmentation-Free Self-Supervised Learning on Graphs
Namkyeong Lee, Junseok Lee, Chanyoung Park
cs.LGcs.AIarXiv:2112.02472v22021
Adaptive Graph Encoder for Attributed Graph Embedding
Ganqu Cui, Jie Zhou, Cheng Yang +1
cs.LGstat.MLarXiv:2007.01594v12020
Everything is Connected: Graph Neural Networks
Petar Veličković
cs.LGcs.AIcs.SIarXiv:2301.08210v12023
TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning
Sung Whan Yoon, Jun Seo, Jaekyun Moon
cs.LGstat.MLarXiv:1905.06549v22019
Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMs
Oded Ovadia, Menachem Brief, Moshik Mishaeli +1
cs.AIcs.CLcs.LGarXiv:2312.05934v32023
Invariant Risk Minimization Games
Kartik Ahuja, Karthikeyan Shanmugam, Kush R. Varshney +1
cs.LGstat.MLarXiv:2002.04692v22020
Semantic Relation Classification via Convolutional Neural Networks with Simple Negative Sampling
Kun Xu, Yansong Feng, Songfang Huang +1
cs.CLcs.LGarXiv:1506.07650v12015
Dash: Semi-Supervised Learning with Dynamic Thresholding
Yi Xu, Lei Shang, Jinxing Ye +5
cs.LGcs.CVstat.MLarXiv:2109.00650v12021
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks
Hadi Salman, Greg Yang, Huan Zhang +2
cs.LGcs.AIcs.CRarXiv:1902.08722v52019
Does Knowledge Distillation Really Work?
Samuel Stanton, Pavel Izmailov, Polina Kirichenko +2
cs.LGstat.MLarXiv:2106.05945v22021
Learning Visual Commonsense for Robust Scene Graph Generation
Alireza Zareian, Zhecan Wang, Haoxuan You +1
cs.CVcs.LGarXiv:2006.09623v22020
Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces
Garrett Warnell, Nicholas Waytowich, Vernon Lawhern +1
cs.AIcs.LGarXiv:1709.10163v22017
Understanding and Improving Early Stopping for Learning with Noisy Labels
Yingbin Bai, Erkun Yang, Bo Han +5
cs.LGarXiv:2106.15853v22021
Unsupervised Learning by Predicting Noise
Piotr Bojanowski, Armand Joulin
stat.MLcs.CVcs.LGarXiv:1704.05310v12017
Enhancing Adversarial Example Transferability with an Intermediate Level Attack
Qian Huang, Isay Katsman, Horace He +3
cs.LGcs.CRcs.CVarXiv:1907.10823v32019
CycleMorph: Cycle Consistent Unsupervised Deformable Image Registration
Boah Kim, Dong Hwan Kim, Seong Ho Park +3
cs.CVcs.LGeess.IVarXiv:2008.05772v12020
Graph HyperNetworks for Neural Architecture Search
Chris Zhang, Mengye Ren, Raquel Urtasun
cs.LGcs.CVstat.MLarXiv:1810.05749v32018
Low Latency Privacy Preserving Inference
Alon Brutzkus, Oren Elisha, Ran Gilad-Bachrach
cs.LGstat.MLarXiv:1812.10659v22018
LEEP: A New Measure to Evaluate Transferability of Learned Representations
Cuong V. Nguyen, Tal Hassner, Matthias Seeger +1
cs.LGcs.CVstat.MLarXiv:2002.12462v22020
Jailbreak Attacks and Defenses Against Large Language Models: A Survey
Sibo Yi, Yule Liu, Zhen Sun +5
cs.CRcs.AIcs.CLarXiv:2407.04295v22024
Recent Advances in Reinforcement Learning in Finance
Ben Hambly, Renyuan Xu, Huining Yang
q-fin.MFcs.LGq-fin.CParXiv:2112.04553v42021
Pretraining Language Models with Human Preferences
Tomasz Korbak, Kejian Shi, Angelica Chen +5
cs.CLcs.LGarXiv:2302.08582v22023
LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities
Yuqi Zhu, Xiaohan Wang, Jing Chen +6
cs.CLcs.AIcs.DBarXiv:2305.13168v42023
A Time-dependent SIR model for COVID-19 with Undetectable Infected Persons
Yi-Cheng Chen, Ping-En Lu, Cheng-Shang Chang +1
q-bio.PEcs.LGstat.MLarXiv:2003.00122v62020
"What is Relevant in a Text Document?": An Interpretable Machine Learning Approach
Leila Arras, Franziska Horn, Grégoire Montavon +2
cs.CLcs.IRcs.LGarXiv:1612.07843v12016
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices
Till Speicher, Hoda Heidari, Nina Grgic-Hlaca +4
cs.LGcs.CYstat.MLarXiv:1807.00787v12018
Gradient descent aligns the layers of deep linear networks
Ziwei Ji, Matus Telgarsky
cs.LGmath.OCstat.MLarXiv:1810.02032v22018
MUREL: Multimodal Relational Reasoning for Visual Question Answering
Remi Cadene, Hedi Ben-younes, Matthieu Cord +1
cs.CVcs.AIcs.CLarXiv:1902.09487v12019
Unit Test Case Generation with Transformers and Focal Context
Michele Tufano, Dawn Drain, Alexey Svyatkovskiy +2
cs.SEcs.CLcs.LGarXiv:2009.05617v22020
Domain Agnostic Learning with Disentangled Representations
Xingchao Peng, Zijun Huang, Ximeng Sun +1
cs.CVcs.LGarXiv:1904.12347v12019
Learning Phase Competition for Traffic Signal Control
Guanjie Zheng, Yuanhao Xiong, Xinshi Zang +6
cs.LGcs.AIstat.MLarXiv:1905.04722v12019
A Large-Scale Study on Unsupervised Spatiotemporal Representation Learning
Christoph Feichtenhofer, Haoqi Fan, Bo Xiong +2
cs.CVcs.AIcs.LGarXiv:2104.14558v12021
Machine Learning for Synthetic Data Generation: A Review
Yingzhou Lu, Lulu Chen, Yuanyuan Zhang +6
cs.LGarXiv:2302.04062v102023
Are adversarial examples inevitable?
Ali Shafahi, W. Ronny Huang, Christoph Studer +2
cs.LGcs.CVstat.MLarXiv:1809.02104v32018
Deep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification
Wentao Zhu, Qi Lou, Yeeleng Scott Vang +1
cs.CVcs.LGarXiv:1612.05968v12016
Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
Xiang Li, Renyu Zhu, Yao Cheng +4
cs.LGcs.AIarXiv:2205.07308v12022
Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization
Rajkumar Ramamurthy, Prithviraj Ammanabrolu, Kianté Brantley +5
cs.CLcs.LGarXiv:2210.01241v32022
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
George Tucker, Andriy Mnih, Chris J. Maddison +2
cs.LGstat.MLarXiv:1703.07370v42017
Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets
Tong Wu, Qingqiu Huang, Ziwei Liu +2
cs.CVcs.LGarXiv:2007.09654v42020
New Insights on Reducing Abrupt Representation Change in Online Continual Learning
Lucas Caccia, Rahaf Aljundi, Nader Asadi +3
cs.LGarXiv:2104.05025v32021
Approximated and User Steerable tSNE for Progressive Visual Analytics
Nicola Pezzotti, Boudewijn P. F. Lelieveldt, Laurens van der Maaten +3
cs.CVcs.LGarXiv:1512.01655v32015
Which Neural Net Architectures Give Rise To Exploding and Vanishing Gradients?
Boris Hanin
stat.MLcs.LGmath.PRarXiv:1801.03744v32018
Recent Trends in Deep Learning Based Personality Detection
Yash Mehta, Navonil Majumder, Alexander Gelbukh +1
cs.LGcs.AIcs.HCarXiv:1908.03628v22019
Towards Theoretically Understanding Why SGD Generalizes Better Than ADAM in Deep Learning
Pan Zhou, Jiashi Feng, Chao Ma +3
cs.LGcs.AImath.OCarXiv:2010.05627v22020
SGD on Neural Networks Learns Functions of Increasing Complexity
Preetum Nakkiran, Gal Kaplun, Dimitris Kalimeris +4
cs.LGcs.NEstat.MLarXiv:1905.11604v12019
Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection
Nicolae-Catalin Ristea, Neelu Madan, Radu Tudor Ionescu +4
cs.CVcs.LGarXiv:2111.09099v62021

Machine Learning

Challenges and Opportunities in Quantum Machine Learning

Quantum advantage in learning from experiments

Noise-Induced Barren Plateaus in Variational Quantum Algorithms

Layerwise learning for quantum neural networks

Physical reservoir computing -- An introductory perspective

Robust data encodings for quantum classifiers

AnatomyNet: Deep Learning for Fast and Fully Automated Whole-volume Segmentation of Head and Neck Anatomy

Quantum generative adversarial networks

Towards Quantum Machine Learning with Tensor Networks

CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks

Entity Embeddings of Categorical Variables

An Efficiency-boosting Client Selection Scheme for Federated Learning with Fairness Guarantee

Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks

Neural Logic Machines

Augmentation-Free Self-Supervised Learning on Graphs

Adaptive Graph Encoder for Attributed Graph Embedding

Everything is Connected: Graph Neural Networks

TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning

Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMs

Invariant Risk Minimization Games

Semantic Relation Classification via Convolutional Neural Networks with Simple Negative Sampling

Dash: Semi-Supervised Learning with Dynamic Thresholding

A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks

Does Knowledge Distillation Really Work?

Learning Visual Commonsense for Robust Scene Graph Generation

Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces

Understanding and Improving Early Stopping for Learning with Noisy Labels

Unsupervised Learning by Predicting Noise

Enhancing Adversarial Example Transferability with an Intermediate Level Attack

CycleMorph: Cycle Consistent Unsupervised Deformable Image Registration

Graph HyperNetworks for Neural Architecture Search

Low Latency Privacy Preserving Inference

LEEP: A New Measure to Evaluate Transferability of Learned Representations

Jailbreak Attacks and Defenses Against Large Language Models: A Survey

Recent Advances in Reinforcement Learning in Finance

Pretraining Language Models with Human Preferences

LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities

A Time-dependent SIR model for COVID-19 with Undetectable Infected Persons

"What is Relevant in a Text Document?": An Interpretable Machine Learning Approach

A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices

Gradient descent aligns the layers of deep linear networks

MUREL: Multimodal Relational Reasoning for Visual Question Answering

Unit Test Case Generation with Transformers and Focal Context

Domain Agnostic Learning with Disentangled Representations

Learning Phase Competition for Traffic Signal Control

A Large-Scale Study on Unsupervised Spatiotemporal Representation Learning

Machine Learning for Synthetic Data Generation: A Review

Are adversarial examples inevitable?

Deep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification

Finding Global Homophily in Graph Neural Networks When Meeting Heterophily

Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization

REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models

Distribution-Balanced Loss for Multi-Label Classification in Long-Tailed Datasets

New Insights on Reducing Abrupt Representation Change in Online Continual Learning

Approximated and User Steerable tSNE for Progressive Visual Analytics

Which Neural Net Architectures Give Rise To Exploding and Vanishing Gradients?

Recent Trends in Deep Learning Based Personality Detection

Towards Theoretically Understanding Why SGD Generalizes Better Than ADAM in Deep Learning

SGD on Neural Networks Learns Functions of Increasing Complexity

Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection