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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14,881 to 14,940 of 20,223

Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods
Derek Lim, Felix Hohne, Xiuyu Li +4
cs.LGcs.SIstat.MLarXiv:2110.14446v12021
DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning
Alex Olsen, Dmitry A. Konovalov, Bronson Philippa +10
cs.CVcs.LGstat.MLarXiv:1810.05726v32018
DDSP: Differentiable Digital Signal Processing
Jesse Engel, Lamtharn Hantrakul, Chenjie Gu +1
cs.LGcs.SDeess.ASarXiv:2001.04643v12020
Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations
Zeming Wei, Yifei Wang, Ang Li +2
cs.LGcs.AIcs.CLarXiv:2310.06387v32023
Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction
Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang +1
cs.LGcs.CLstat.MLarXiv:1911.09419v32019
Bayesian Compression for Deep Learning
Christos Louizos, Karen Ullrich, Max Welling
stat.MLcs.LGarXiv:1705.08665v42017
Challenges and Applications of Large Language Models
Jean Kaddour, Joshua Harris, Maximilian Mozes +3
cs.CLcs.AIcs.LGarXiv:2307.10169v12023
CoverNet: Multimodal Behavior Prediction using Trajectory Sets
Tung Phan-Minh, Elena Corina Grigore, Freddy A. Boulton +2
cs.LGcs.ROstat.MLarXiv:1911.10298v22019
Deep Fruit Detection in Orchards
Suchet Bargoti, James Underwood
cs.ROcs.AIcs.CVarXiv:1610.03677v22016
Universal Guidance for Diffusion Models
Arpit Bansal, Hong-Min Chu, Avi Schwarzschild +4
cs.CVcs.LGarXiv:2302.07121v12023
Temporal Generative Adversarial Nets with Singular Value Clipping
Masaki Saito, Eiichi Matsumoto, Shunta Saito
cs.LGcs.CVarXiv:1611.06624v32016
12-in-1: Multi-Task Vision and Language Representation Learning
Jiasen Lu, Vedanuj Goswami, Marcus Rohrbach +2
cs.CVcs.CLcs.LGarXiv:1912.02315v22019
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner +2
cs.LGstat.MLarXiv:1706.08500v62017
Combinatorial optimization and reasoning with graph neural networks
Quentin Cappart, Didier Chételat, Elias Khalil +3
cs.LGcs.DScs.NEarXiv:2102.09544v32021
Measuring Emotional Contagion in Social Media
Emilio Ferrara, Zeyao Yang
cs.SIcs.LGphysics.soc-pharXiv:1506.06021v12015
Time2Vec: Learning a Vector Representation of Time
Seyed Mehran Kazemi, Rishab Goel, Sepehr Eghbali +7
cs.LGarXiv:1907.05321v12019
PDEBENCH: An Extensive Benchmark for Scientific Machine Learning
Makoto Takamoto, Timothy Praditia, Raphael Leiteritz +4
cs.LGcs.CVphysics.flu-dynarXiv:2210.07182v72022
Hello Edge: Keyword Spotting on Microcontrollers
Yundong Zhang, Naveen Suda, Liangzhen Lai +1
cs.SDcs.CLcs.LGarXiv:1711.07128v32017
Multi-Stage Document Ranking with BERT
Rodrigo Nogueira, Wei Yang, Kyunghyun Cho +1
cs.IRcs.LGarXiv:1910.14424v12019
Neural Belief Tracker: Data-Driven Dialogue State Tracking
Nikola Mrkšić, Diarmuid Ó Séaghdha, Tsung-Hsien Wen +2
cs.CLcs.AIcs.LGarXiv:1606.03777v22016
Towards Understanding and Mitigating Social Biases in Language Models
Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency +1
cs.CLcs.AIcs.CYarXiv:2106.13219v12021
Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA
Aapo Hyvarinen, Hiroshi Morioka
stat.MLcs.LGarXiv:1605.06336v12016
The KIT Motion-Language Dataset
Matthias Plappert, Christian Mandery, Tamim Asfour
cs.ROcs.CLcs.CVarXiv:1607.03827v22016
YOLACT++: Better Real-time Instance Segmentation
Daniel Bolya, Chong Zhou, Fanyi Xiao +1
cs.CVcs.LGeess.IVarXiv:1912.06218v22019
Dawn of the transformer era in speech emotion recognition: closing the valence gap
Johannes Wagner, Andreas Triantafyllopoulos, Hagen Wierstorf +4
eess.AScs.LGcs.SDarXiv:2203.07378v42022
Linear Transformers Are Secretly Fast Weight Programmers
Imanol Schlag, Kazuki Irie, Jürgen Schmidhuber
cs.LGarXiv:2102.11174v32021
Improving Adversarial Robustness via Promoting Ensemble Diversity
Tianyu Pang, Kun Xu, Chao Du +2
cs.LGstat.MLarXiv:1901.08846v32019
Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics
Mark Weber, Giacomo Domeniconi, Jie Chen +4
cs.SIcs.CYcs.LGarXiv:1908.02591v12019
Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networks
Stephen James, Paul Wohlhart, Mrinal Kalakrishnan +6
cs.ROcs.CVcs.LGarXiv:1812.07252v32018
Applications of Unsupervised Deep Transfer Learning to Intelligent Fault Diagnosis: A Survey and Comparative Study
Zhibin Zhao, Qiyang Zhang, Xiaolei Yu +4
eess.SPcs.LGarXiv:1912.12528v22019
Data Augmentation for Graph Neural Networks
Tong Zhao, Yozen Liu, Leonardo Neves +3
cs.LGstat.MLarXiv:2006.06830v22020
Learning by Playing - Solving Sparse Reward Tasks from Scratch
Martin Riedmiller, Roland Hafner, Thomas Lampe +6
cs.LGcs.ROstat.MLarXiv:1802.10567v12018
Sensitivity and Generalization in Neural Networks: an Empirical Study
Roman Novak, Yasaman Bahri, Daniel A. Abolafia +2
stat.MLcs.AIcs.LGarXiv:1802.08760v32018
Stealing Hyperparameters in Machine Learning
Binghui Wang, Neil Zhenqiang Gong
cs.CRcs.LGstat.MLarXiv:1802.05351v32018
WHAM!: Extending Speech Separation to Noisy Environments
Gordon Wichern, Joe Antognini, Michael Flynn +5
cs.SDcs.CLcs.LGarXiv:1907.01160v12019
Asymmetric LSH (ALSH) for Sublinear Time Maximum Inner Product Search (MIPS)
Anshumali Shrivastava, Ping Li
stat.MLcs.DScs.IRarXiv:1405.5869v12014
Gated Linear Attention Transformers with Hardware-Efficient Training
Songlin Yang, Bailin Wang, Yikang Shen +2
cs.LGcs.CLarXiv:2312.06635v62023
Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and Beyond
Xuhong Li, Haoyi Xiong, Xingjian Li +5
cs.LGarXiv:2103.10689v32021
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs
Weihua Hu, Matthias Fey, Hongyu Ren +3
cs.LGarXiv:2103.09430v32021
Deep Transfer Network with Joint Distribution Adaptation: A New Intelligent Fault Diagnosis Framework for Industry Application
Te Han, Chao Liu, Wenguang Yang +1
cs.LGstat.MLarXiv:1804.07265v12018
Learning to Optimize Tensor Programs
Tianqi Chen, Lianmin Zheng, Eddie Yan +5
cs.LGstat.MLarXiv:1805.08166v42018
Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing
Ke Gong, Xiaodan Liang, Dongyu Zhang +2
cs.CVcs.AIcs.LGarXiv:1703.05446v22017
Efficient Algorithms for t-distributed Stochastic Neighborhood Embedding
George C. Linderman, Manas Rachh, Jeremy G. Hoskins +2
cs.LGstat.MLarXiv:1712.09005v12017
Frequency-domain MLPs are More Effective Learners in Time Series Forecasting
Kun Yi, Qi Zhang, Wei Fan +7
cs.LGcs.AIarXiv:2311.06184v12023
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design
Jonathan Ho, Xi Chen, Aravind Srinivas +2
cs.LGcs.NEstat.MLarXiv:1902.00275v22019
Reducing Activation Recomputation in Large Transformer Models
Vijay Korthikanti, Jared Casper, Sangkug Lym +4
cs.LGcs.CLarXiv:2205.05198v12022
TinyStories: How Small Can Language Models Be and Still Speak Coherent English?
Ronen Eldan, Yuanzhi Li
cs.CLcs.AIcs.LGarXiv:2305.07759v22023
Adapting Neural Networks for the Estimation of Treatment Effects
Claudia Shi, David M. Blei, Victor Veitch
stat.MLcs.LGstat.MEarXiv:1906.02120v22019
Multimodal Generative Models for Scalable Weakly-Supervised Learning
Mike Wu, Noah Goodman
cs.LGstat.MLarXiv:1802.05335v32018
The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning
Nathaniel Li, Alexander Pan, Anjali Gopal +54
cs.LGcs.AIcs.CLarXiv:2403.03218v72024
Deep Reinforcement Learning for Traffic Light Control in Vehicular Networks
Xiaoyuan Liang, Xunsheng Du, Guiling Wang +1
cs.LGcs.AIstat.MLarXiv:1803.11115v12018
VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training
Yecheng Jason Ma, Shagun Sodhani, Dinesh Jayaraman +3
cs.ROcs.AIcs.CVarXiv:2210.00030v22022
Modular Multitask Reinforcement Learning with Policy Sketches
Jacob Andreas, Dan Klein, Sergey Levine
cs.LGcs.NEarXiv:1611.01796v22016
Local, Private, Efficient Protocols for Succinct Histograms
Raef Bassily, Adam Smith
cs.CRcs.DScs.LGarXiv:1504.04686v12015
FedALA: Adaptive Local Aggregation for Personalized Federated Learning
Jianqing Zhang, Yang Hua, Hao Wang +4
cs.LGcs.AIarXiv:2212.01197v42022
Learning Activation Functions to Improve Deep Neural Networks
Forest Agostinelli, Matthew Hoffman, Peter Sadowski +1
cs.NEcs.CVcs.LGarXiv:1412.6830v32014
Machine Learning at the Network Edge: A Survey
M. G. Sarwar Murshed, Christopher Murphy, Daqing Hou +3
cs.LGcs.CVcs.NIarXiv:1908.00080v42019
Neighborhood Attention Transformer
Ali Hassani, Steven Walton, Jiachen Li +2
cs.CVcs.AIcs.LGarXiv:2204.07143v52022
Evaluating Real-time Anomaly Detection Algorithms - the Numenta Anomaly Benchmark
Alexander Lavin, Subutai Ahmad
cs.AIcs.LGarXiv:1510.03336v42015
Systematic Evaluation of Privacy Risks of Machine Learning Models
Liwei Song, Prateek Mittal
cs.CRcs.LGstat.MLarXiv:2003.10595v22020

Machine Learning

Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods

DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning

DDSP: Differentiable Digital Signal Processing

Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations

Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction

Bayesian Compression for Deep Learning

Challenges and Applications of Large Language Models

CoverNet: Multimodal Behavior Prediction using Trajectory Sets

Deep Fruit Detection in Orchards

Universal Guidance for Diffusion Models

Temporal Generative Adversarial Nets with Singular Value Clipping

12-in-1: Multi-Task Vision and Language Representation Learning

GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium

Combinatorial optimization and reasoning with graph neural networks

Measuring Emotional Contagion in Social Media

Time2Vec: Learning a Vector Representation of Time

PDEBENCH: An Extensive Benchmark for Scientific Machine Learning

Hello Edge: Keyword Spotting on Microcontrollers

Multi-Stage Document Ranking with BERT

Neural Belief Tracker: Data-Driven Dialogue State Tracking

Towards Understanding and Mitigating Social Biases in Language Models

Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA

The KIT Motion-Language Dataset

YOLACT++: Better Real-time Instance Segmentation

Dawn of the transformer era in speech emotion recognition: closing the valence gap

Linear Transformers Are Secretly Fast Weight Programmers

Improving Adversarial Robustness via Promoting Ensemble Diversity

Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics

Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networks

Applications of Unsupervised Deep Transfer Learning to Intelligent Fault Diagnosis: A Survey and Comparative Study

Data Augmentation for Graph Neural Networks

Learning by Playing - Solving Sparse Reward Tasks from Scratch

Sensitivity and Generalization in Neural Networks: an Empirical Study

Stealing Hyperparameters in Machine Learning

WHAM!: Extending Speech Separation to Noisy Environments

Asymmetric LSH (ALSH) for Sublinear Time Maximum Inner Product Search (MIPS)

Gated Linear Attention Transformers with Hardware-Efficient Training

Interpretable Deep Learning: Interpretation, Interpretability, Trustworthiness, and Beyond

OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Deep Transfer Network with Joint Distribution Adaptation: A New Intelligent Fault Diagnosis Framework for Industry Application

Learning to Optimize Tensor Programs

Look into Person: Self-supervised Structure-sensitive Learning and A New Benchmark for Human Parsing

Efficient Algorithms for t-distributed Stochastic Neighborhood Embedding

Frequency-domain MLPs are More Effective Learners in Time Series Forecasting

Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design

Reducing Activation Recomputation in Large Transformer Models

TinyStories: How Small Can Language Models Be and Still Speak Coherent English?

Adapting Neural Networks for the Estimation of Treatment Effects

Multimodal Generative Models for Scalable Weakly-Supervised Learning

The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning

Deep Reinforcement Learning for Traffic Light Control in Vehicular Networks

VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training

Modular Multitask Reinforcement Learning with Policy Sketches

Local, Private, Efficient Protocols for Succinct Histograms

FedALA: Adaptive Local Aggregation for Personalized Federated Learning

Learning Activation Functions to Improve Deep Neural Networks

Machine Learning at the Network Edge: A Survey

Neighborhood Attention Transformer

Evaluating Real-time Anomaly Detection Algorithms - the Numenta Anomaly Benchmark

Systematic Evaluation of Privacy Risks of Machine Learning Models