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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10,981 to 11,040 of 20,135
Handling Missing Data with Graph Representation Learning
Jiaxuan You, Xiaobai Ma, Daisy Yi Ding +2
cs.LGcs.SIstat.MLarXiv:2010.16418v12020Generalization in Adaptive Data Analysis and Holdout Reuse
Cynthia Dwork, Vitaly Feldman, Moritz Hardt +3
cs.LGcs.DSarXiv:1506.02629v22015Quilt-1M: One Million Image-Text Pairs for Histopathology
Wisdom Oluchi Ikezogwo, Mehmet Saygin Seyfioglu, Fatemeh Ghezloo +5
cs.CVcs.CLcs.LGarXiv:2306.11207v42023Neural Abstractive Text Summarization with Sequence-to-Sequence Models
Tian Shi, Yaser Keneshloo, Naren Ramakrishnan +1
cs.CLcs.LGstat.MLarXiv:1812.02303v42018Wasserstein Distance based Deep Adversarial Transfer Learning for Intelligent Fault Diagnosis
Cheng Cheng, Beitong Zhou, Guijun Ma +2
cs.LGeess.SPstat.MLarXiv:1903.06753v12019Affect Analysis in-the-wild: Valence-Arousal, Expressions, Action Units and a Unified Framework
Dimitrios Kollias, Stefanos Zafeiriou
cs.CVcs.AIcs.LGarXiv:2103.15792v12021Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation
Raha Moraffah, Mansooreh Karami, Ruocheng Guo +2
cs.LGstat.MLarXiv:2003.03934v32020Reducing conversational agents' overconfidence through linguistic calibration
Sabrina J. Mielke, Arthur Szlam, Emily Dinan +1
cs.CLcs.AIcs.LGarXiv:2012.14983v22020Personalized Education in the AI Era: What to Expect Next?
Setareh Maghsudi, Andrew Lan, Jie Xu +1
cs.CYcs.AIcs.LGarXiv:2101.10074v12021Adaptive Federated Learning and Digital Twin for Industrial Internet of Things
Wen Sun, Shiyu Lei, Lu Wang +2
cs.LGcs.DCarXiv:2010.13058v22020Gotta Go Fast When Generating Data with Score-Based Models
Alexia Jolicoeur-Martineau, Ke Li, Rémi Piché-Taillefer +2
cs.LGcs.CVmath.OCarXiv:2105.14080v12021DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning
Kevin Ellis, Catherine Wong, Maxwell Nye +6
cs.AIcs.LGarXiv:2006.08381v12020A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics
Seyed Ali Osia, Ali Shahin Shamsabadi, Sina Sajadmanesh +5
cs.LGcs.CVarXiv:1703.02952v72017On the Computational and Statistical Efficiency of the Empirical Maximum Entropy on the Mean Method
Matthew King-Roskamp, Gabriel Rioux, Rustum Choksi +1
math.OCcs.LGstat.MLarXiv:2608.27705v12026SARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked Prefills
Amey Agrawal, Ashish Panwar, Jayashree Mohan +3
cs.LGcs.DCarXiv:2308.16369v12023Unsupervised Continual Learning with Growing Self-Organizing Maps and Synthetic Replay
Pujan Thapa, Alexander Ororbia, Travis Desell
cs.LGarXiv:2608.27662v12026Reinforcement Learning with Parameterized Actions
Warwick Masson, Pravesh Ranchod, George Konidaris
cs.AIcs.LGarXiv:1509.01644v42015Rank Centrality: Ranking from Pair-wise Comparisons
Sahand Negahban, Sewoong Oh, Devavrat Shah
cs.LGstat.MLarXiv:1209.1688v42012Deep Reinforcement Learning with a Natural Language Action Space
Ji He, Jianshu Chen, Xiaodong He +4
cs.AIcs.CLcs.LGarXiv:1511.04636v52015Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction
Huaxiu Yao, Yiding Liu, Ying Wei +2
cs.LGstat.MLarXiv:1901.08518v32019AlphaFold Meets Flow Matching for Generating Protein Ensembles
Bowen Jing, Bonnie Berger, Tommi Jaakkola
q-bio.BMcs.LGarXiv:2402.04845v22024Multi-Game Decision Transformers
Kuang-Huei Lee, Ofir Nachum, Mengjiao Yang +8
cs.AIcs.LGarXiv:2205.15241v22022Simplifying, Stabilizing and Scaling Continuous-Time Consistency Models
Cheng Lu, Yang Song
cs.LGstat.MLarXiv:2410.11081v22024TBT: Targeted Neural Network Attack with Bit Trojan
Adnan Siraj Rakin, Zhezhi He, Deliang Fan
cs.CRcs.LGcs.NEarXiv:1909.05193v32019Speaker-independent Speech Separation with Deep Attractor Network
Yi Luo, Zhuo Chen, Nima Mesgarani
cs.SDcs.LGarXiv:1707.03634v32017From $r$ to $Q^*$: Your Language Model is Secretly a Q-Function
Rafael Rafailov, Joey Hejna, Ryan Park +1
cs.LGarXiv:2404.12358v22024Diffusion-TS: Interpretable Diffusion for General Time Series Generation
Xinyu Yuan, Yan Qiao
cs.LGcs.AIarXiv:2403.01742v32024Conditional Diffusion Models for Energy-Efficient Driving
Hemanth Neelgund Ramesh, André Snoeck, Chyi-Fu Hong +1
cs.LGarXiv:2608.28142v12026Beyond Pairwise Graphs in Science: Hypergraph Adaptive Wavelet Operators for Parametric PDEs
Rajat Sarkar, Venkataramana Runkana, Souvik Chakraborty
cs.LGphysics.comp-pharXiv:2608.27883v12026Self-Chained Image-Language Model for Video Localization and Question Answering
Shoubin Yu, Jaemin Cho, Prateek Yadav +1
cs.CVcs.AIcs.CLarXiv:2305.06988v22023Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing
Zihang Dai, Guokun Lai, Yiming Yang +1
cs.LGcs.CLstat.MLarXiv:2006.03236v12020Federated Graph Classification over Non-IID Graphs
Han Xie, Jing Ma, Li Xiong +1
cs.LGcs.AIcs.DCarXiv:2106.13423v52021On the Convergence Theory of Gradient-Based Model-Agnostic Meta-Learning Algorithms
Alireza Fallah, Aryan Mokhtari, Asuman Ozdaglar
cs.LGmath.OCstat.MLarXiv:1908.10400v42019Self-Play Preference Optimization for Language Model Alignment
Yue Wu, Zhiqing Sun, Huizhuo Yuan +3
cs.LGcs.AIcs.CLarXiv:2405.00675v52024Reward Augmented Maximum Likelihood for Neural Structured Prediction
Mohammad Norouzi, Samy Bengio, Zhifeng Chen +4
cs.LGarXiv:1609.00150v32016Spelling Error Correction with Soft-Masked BERT
Shaohua Zhang, Haoran Huang, Jicong Liu +1
cs.CLcs.LGarXiv:2005.07421v12020FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs
Alekh Agarwal, Sham Kakade, Akshay Krishnamurthy +1
cs.LGstat.MLarXiv:2006.10814v22020Freeform Diffractive Metagrating Design Based on Generative Adversarial Networks
Jiaqi Jiang, David Sell, Stephan Hoyer +3
physics.opticscs.LGarXiv:1811.12436v22018Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition
Ümit Çavuş Büyükşahin, Şeyda Ertekin
cs.LGstat.MLarXiv:1812.11526v12018Towards CRISP-ML(Q): A Machine Learning Process Model with Quality Assurance Methodology
Stefan Studer, Thanh Binh Bui, Christian Drescher +4
cs.LGcs.SEstat.MLarXiv:2003.05155v22020A Principled Approach to Data Valuation for Federated Learning
Tianhao Wang, Johannes Rausch, Ce Zhang +2
cs.LGcs.CYstat.MLarXiv:2009.06192v12020Towards Visually Explaining Variational Autoencoders
Wenqian Liu, Runze Li, Meng Zheng +5
cs.CVcs.LGarXiv:1911.07389v72019Machine Learning in High Energy Physics Community White Paper
Kim Albertsson, Piero Altoe, Dustin Anderson +125
physics.comp-phcs.LGhep-exarXiv:1807.02876v32018Federated Learning for Medical Applications: A Taxonomy, Current Trends, Challenges, and Future Research Directions
Ashish Rauniyar, Desta Haileselassie Hagos, Debesh Jha +4
cs.LGcs.CRcs.CVarXiv:2208.03392v52022HyperDreamBooth: HyperNetworks for Fast Personalization of Text-to-Image Models
Nataniel Ruiz, Yuanzhen Li, Varun Jampani +6
cs.CVcs.AIcs.GRarXiv:2307.06949v22023On weight initialization in deep neural networks
Siddharth Krishna Kumar
cs.LGarXiv:1704.08863v22017The Consciousness Prior
Yoshua Bengio
cs.LGcs.AIstat.MLarXiv:1709.08568v22017Learning to Optimize Domain Specific Normalization for Domain Generalization
Seonguk Seo, Yumin Suh, Dongwan Kim +3
cs.LGstat.MLarXiv:1907.04275v32019Bridging the Gaps Between Residual Learning, Recurrent Neural Networks and Visual Cortex
Qianli Liao, Tomaso Poggio
cs.LGcs.NEarXiv:1604.03640v22016Towards Large-Scale Heterogeneous Data Organization for Scientific Foundation Models: A Nuclear Fusion Case Study
Nathaniel Chen, Kouroche Bouchiat, Peter Steiner +3
physics.plasm-phcs.LGarXiv:2608.27578v12026Variational Recurrent Auto-Encoders
Otto Fabius, Joost R. van Amersfoort
stat.MLcs.LGcs.NEarXiv:1412.6581v62014Data Interpreter: An LLM Agent For Data Science
Sirui Hong, Yizhang Lin, Bang Liu +24
cs.AIcs.LGarXiv:2402.18679v42024Towards a mathematical theory of superposition
Michael I. Ivanitskiy, John Jasper, Emily J. King +1
stat.MLcs.ITcs.LGarXiv:2608.27540v12026MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Brandon McKinzie, Zhe Gan, Jean-Philippe Fauconnier +29
cs.CVcs.CLcs.LGarXiv:2403.09611v42024More Data Cannot Break a Symmetry: Identifiability by Design
Jing Xu, Christopher Kanan
cs.LGarXiv:2608.27651v12026Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks
Blake Bordelon, Abdulkadir Canatar, Cengiz Pehlevan
cs.LGstat.MLarXiv:2002.02561v72020A study on effectiveness of extreme learning machine
Yuguang Wang, Feilong Cao, Yubo Yuan
cs.NEcs.LGarXiv:1409.3924v12014An Explainable Artificial Intelligence Approach for Unsupervised Fault Detection and Diagnosis in Rotating Machinery
Lucas Costa Brito, Gian Antonio Susto, Jorge Nei Brito +1
cs.AIcs.LGarXiv:2102.11848v12021Deep Machine Learning Approach to Develop a New Asphalt Pavement Condition Index
Hamed Majidifard, Yaw Adu-Gyamfi, William G. Buttlar
stat.MLcs.LGstat.COarXiv:2004.13314v12020Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit
Belinda Tzen, Maxim Raginsky
cs.LGstat.MLarXiv:1905.09883v22019