Machine Learning (stat)

Papers filed under stat.ML 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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7,021 to 7,080 of 9,718

Understanding Negative Sampling in Graph Representation Learning
Zhen Yang, Ming Ding, Chang Zhou +3
cs.LGstat.MLarXiv:2005.09863v22020
Distill-and-Compare: Auditing Black-Box Models Using Transparent Model Distillation
Sarah Tan, Rich Caruana, Giles Hooker +1
stat.MLcs.AIcs.LGarXiv:1710.06169v42017
Neural Combinatorial Optimization with Reinforcement Learning
Irwan Bello, Hieu Pham, Quoc V. Le +2
cs.AIcs.LGstat.MLarXiv:1611.09940v32016
word2ket: Space-efficient Word Embeddings inspired by Quantum Entanglement
Aliakbar Panahi, Seyran Saeedi, Tom Arodz
cs.LGstat.MLarXiv:1911.04975v32019
Sever: A Robust Meta-Algorithm for Stochastic Optimization
Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane +3
cs.LGcs.AIcs.DSarXiv:1803.02815v22018
Machine Learning by Unitary Tensor Network of Hierarchical Tree Structure
Ding Liu, Shi-Ju Ran, Peter Wittek +4
stat.MLcond-mat.str-elphysics.comp-pharXiv:1710.04833v42017
Conditional Restricted Boltzmann Machines for Structured Output Prediction
Volodymyr Mnih, Hugo Larochelle, Geoffrey E. Hinton
cs.LGstat.MLarXiv:1202.3748v12012
Spectral Method and Regularized MLE Are Both Optimal for Top-$K$ Ranking
Yuxin Chen, Jianqing Fan, Cong Ma +1
stat.MLcs.ITcs.LGarXiv:1707.09971v32017
Monte Carlo Gradient Estimation in Machine Learning
Shakir Mohamed, Mihaela Rosca, Michael Figurnov +1
stat.MLcs.LGmath.OCarXiv:1906.10652v22019
Enhancing Observability in Distribution Grids using Smart Meter Data
Siddharth Bhela, Vassilis Kekatos, Sriharsha Veeramachaneni
math.OCcs.LGstat.MLarXiv:1612.06669v12016
DeepArchitect: Automatically Designing and Training Deep Architectures
Renato Negrinho, Geoff Gordon
stat.MLcs.LGarXiv:1704.08792v12017
Scalable Learning of Determinantal Point Processes with Kernel-Structured Interactions
Takahiro Kawashima, Hideitsu Hino
stat.MLcs.LGarXiv:2610.12829v12026
Representation Learning on Graphs with Jumping Knowledge Networks
Keyulu Xu, Chengtao Li, Yonglong Tian +3
cs.LGcs.AIcs.CVarXiv:1806.03536v22018
High-dimensional dynamics of generalization error in neural networks
Madhu S. Advani, Andrew M. Saxe
stat.MLcs.LGphysics.data-anarXiv:1710.03667v12017
full-FORCE: A Target-Based Method for Training Recurrent Networks
Brian DePasquale, Christopher J. Cueva, Kanaka Rajan +2
cs.NEcs.LGq-bio.NCarXiv:1710.03070v12017
Deep Learning-Based Channel Estimation
Mehran Soltani, Vahid Pourahmadi, Ali Mirzaei +1
cs.ITcs.LGeess.SParXiv:1810.05893v42018
Augmenting Self-attention with Persistent Memory
Sainbayar Sukhbaatar, Edouard Grave, Guillaume Lample +2
cs.LGcs.CLstat.MLarXiv:1907.01470v12019
Exploratory Combinatorial Optimization with Reinforcement Learning
Thomas D. Barrett, William R. Clements, Jakob N. Foerster +1
cs.LGcs.AIstat.MLarXiv:1909.04063v22019
Avoiding the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adversarial Training
Joe Stacey, Pasquale Minervini, Haim Dubossarsky +2
cs.LGcs.AIcs.CLarXiv:2004.07790v52020
Domain Generalization by Marginal Transfer Learning
Gilles Blanchard, Aniket Anand Deshmukh, Urun Dogan +2
stat.MLarXiv:1711.07910v32017
Learning Convolutional Neural Networks for Graphs
Mathias Niepert, Mohamed Ahmed, Konstantin Kutzkov
cs.LGcs.AIstat.MLarXiv:1605.05273v42016
SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging
Huy Phan, Fernando Andreotti, Navin Cooray +2
cs.LGeess.SPstat.MLarXiv:1809.10932v32018
GRAPE: Gradient Refinement and Progress-Aware Exploitation for Query-Efficient High-Dimensional Bayesian Optimization
Richard Cornelius Suwandi, Feng Yin
cs.LGcs.AIstat.MLarXiv:2608.25116v12026
Meta-Learning Representations for Continual Learning
Khurram Javed, Martha White
cs.LGcs.AIstat.MLarXiv:1905.12588v22019
Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs
W. James Murdoch, Peter J. Liu, Bin Yu
cs.CLcs.LGstat.MLarXiv:1801.05453v22018
Provably efficient RL with Rich Observations via Latent State Decoding
Simon S. Du, Akshay Krishnamurthy, Nan Jiang +3
cs.LGstat.MLarXiv:1901.09018v32019
Large-scale Interactive Recommendation with Tree-structured Policy Gradient
Haokun Chen, Xinyi Dai, Han Cai +5
cs.LGcs.AIstat.MLarXiv:1811.05869v12018
Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition
Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi
cs.LGmath.DSstat.MLarXiv:1710.04340v22017
Accelerating Federated Learning via Momentum Gradient Descent
Wei Liu, Li Chen, Yunfei Chen +1
cs.LGstat.MLarXiv:1910.03197v22019
The Surprising Power of Graph Neural Networks with Random Node Initialization
Ralph Abboud, İsmail İlkan Ceylan, Martin Grohe +1
cs.LGcs.AIstat.MLarXiv:2010.01179v22020
ICON Decomposition: Multivariate Concept-Level Explanations of Deep Representations for Model Auditing
Roshan Prakash Rane, Marco Simnacher, Manuel Pfeuffer +7
cs.LGcs.AIcs.CVarXiv:2608.26083v12026
The Uncertainty Bellman Equation and Exploration
Brendan O'Donoghue, Ian Osband, Remi Munos +1
cs.AIcs.LGmath.OCarXiv:1709.05380v42017
Bayesian Batch Active Learning as Sparse Subset Approximation
Robert Pinsler, Jonathan Gordon, Eric Nalisnick +1
stat.MLcs.LGarXiv:1908.02144v42019
The Unreasonable Ineffectiveness of the Deeper Layers
Andrey Gromov, Kushal Tirumala, Hassan Shapourian +2
cs.CLcs.LGstat.MLarXiv:2403.17887v22024
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware
Florian Tramèr, Dan Boneh
stat.MLcs.CRcs.LGarXiv:1806.03287v22018
CardioState-JEPA: Delay-Aware Cross-Modal Learning of a Shared Cardiac Representation
Hamza Shafiq, Hung Manh Pham, Bin Zhu +3
cs.LGeess.IVstat.MLarXiv:2608.12944v12026
CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training
Murat Kocaoglu, Christopher Snyder, Alexandros G. Dimakis +1
cs.LGcs.AIcs.ITarXiv:1709.02023v22017
Adversarial Evaluation of Autonomous Vehicles in Lane-Change Scenarios
Baiming Chen, Xiang Chen, Wu Qiong +1
cs.ROcs.LGstat.MLarXiv:2004.06531v22020
Automated Directed Fairness Testing
Sakshi Udeshi, Pryanshu Arora, Sudipta Chattopadhyay
cs.LGcs.AIcs.SEarXiv:1807.00468v22018
Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation
Yuan Shi, Fei Sha
cs.LGstat.MLarXiv:1206.6438v12012
FluxDisco: Symbolic Regression for Stoichiometric Dynamical Systems via Monte Carlo Graph Search
Cassandra Durr, Alvaro Köhn-Luque, Chris Jewell +1
stat.MLcs.LGphysics.data-anarXiv:2609.05207v12026
Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model
Alex X. Lee, Anusha Nagabandi, Pieter Abbeel +1
cs.LGcs.AIstat.MLarXiv:1907.00953v42019
A DIRT-T Approach to Unsupervised Domain Adaptation
Rui Shu, Hung H. Bui, Hirokazu Narui +1
stat.MLcs.CVcs.LGarXiv:1802.08735v22018
Practical One-Shot Federated Learning for Cross-Silo Setting
Qinbin Li, Bingsheng He, Dawn Song
cs.LGstat.MLarXiv:2010.01017v22020
Practical Coreset Constructions for Machine Learning
Olivier Bachem, Mario Lucic, Andreas Krause
stat.MLarXiv:1703.06476v22017
Maxout Networks
Ian J. Goodfellow, David Warde-Farley, Mehdi Mirza +2
stat.MLcs.LGarXiv:1302.4389v42013
Summaries:한국어
Categorizing Variants of Goodhart's Law
David Manheim, Scott Garrabrant
cs.AIq-fin.GNstat.MLarXiv:1803.04585v42018
One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control
Wenlong Huang, Igor Mordatch, Deepak Pathak
cs.LGcs.CVstat.MLarXiv:2007.04976v12020
Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy Evaluation
Yunhao Tang, Tadashi Kozuno, Mark Rowland +2
cs.LGstat.MLarXiv:2106.13125v22021
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions
Sara Magliacane, Thijs van Ommen, Tom Claassen +3
cs.LGstat.MLarXiv:1707.06422v32017
Convex Optimization in Julia
Madeleine Udell, Karanveer Mohan, David Zeng +3
math.OCcs.MSstat.MLarXiv:1410.4821v12014
A Fourier Space Perspective on Diffusion Models
Fabian Falck, Teodora Pandeva, Kiarash Zahirnia +5
stat.MLcs.CVcs.LGarXiv:2505.11278v12025
Robust conditional dimension reduction for dissimilarity data
Xiao Ling, Anh Bui
stat.MLcs.LGmath.OCarXiv:2609.06284v12026
Causal Foundation Models
Christopher Stith, Hossein Rahmani, Jesse C. Cresswell
cs.LGstat.MLarXiv:2609.03003v12026
Energy Flow Networks: Deep Sets for Particle Jets
Patrick T. Komiske, Eric M. Metodiev, Jesse Thaler
hep-phhep-exstat.MLarXiv:1810.05165v22018
Prediction-Powered Data Fusion for Treatment Effect Estimation
Yonghan Jung, Shu Yang
stat.MLcs.AIcs.LGarXiv:2610.12332v12026
Policy Gradient for Coherent Risk Measures
Aviv Tamar, Yinlam Chow, Mohammad Ghavamzadeh +1
cs.AIcs.LGstat.MLarXiv:1502.03919v22015
A review of mean-shift algorithms for clustering
Miguel Á. Carreira-Perpiñán
cs.LGcs.CVstat.MLarXiv:1503.00687v12015
Subject-Aware Contrastive Learning for Biosignals
Joseph Y. Cheng, Hanlin Goh, Kaan Dogrusoz +2
cs.LGeess.SPstat.MLarXiv:2007.04871v12020
CASTER: Predicting Drug Interactions with Chemical Substructure Representation
Kexin Huang, Cao Xiao, Trong Nghia Hoang +2
cs.LGq-bio.QMstat.MLarXiv:1911.06446v22019

Machine Learning (stat)

Understanding Negative Sampling in Graph Representation Learning

Distill-and-Compare: Auditing Black-Box Models Using Transparent Model Distillation

Neural Combinatorial Optimization with Reinforcement Learning

word2ket: Space-efficient Word Embeddings inspired by Quantum Entanglement

Sever: A Robust Meta-Algorithm for Stochastic Optimization

Machine Learning by Unitary Tensor Network of Hierarchical Tree Structure

Conditional Restricted Boltzmann Machines for Structured Output Prediction

Spectral Method and Regularized MLE Are Both Optimal for Top-$K$ Ranking

Monte Carlo Gradient Estimation in Machine Learning

Enhancing Observability in Distribution Grids using Smart Meter Data

DeepArchitect: Automatically Designing and Training Deep Architectures

Scalable Learning of Determinantal Point Processes with Kernel-Structured Interactions

Representation Learning on Graphs with Jumping Knowledge Networks

High-dimensional dynamics of generalization error in neural networks

full-FORCE: A Target-Based Method for Training Recurrent Networks

Deep Learning-Based Channel Estimation

Augmenting Self-attention with Persistent Memory

Exploratory Combinatorial Optimization with Reinforcement Learning

Avoiding the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adversarial Training

Domain Generalization by Marginal Transfer Learning

Learning Convolutional Neural Networks for Graphs

SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging

GRAPE: Gradient Refinement and Progress-Aware Exploitation for Query-Efficient High-Dimensional Bayesian Optimization

Meta-Learning Representations for Continual Learning

Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs

Provably efficient RL with Rich Observations via Latent State Decoding

Large-scale Interactive Recommendation with Tree-structured Policy Gradient

Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition

Accelerating Federated Learning via Momentum Gradient Descent

The Surprising Power of Graph Neural Networks with Random Node Initialization

ICON Decomposition: Multivariate Concept-Level Explanations of Deep Representations for Model Auditing

The Uncertainty Bellman Equation and Exploration

Bayesian Batch Active Learning as Sparse Subset Approximation

The Unreasonable Ineffectiveness of the Deeper Layers

Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware

CardioState-JEPA: Delay-Aware Cross-Modal Learning of a Shared Cardiac Representation

CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training

Adversarial Evaluation of Autonomous Vehicles in Lane-Change Scenarios

Automated Directed Fairness Testing

Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation

FluxDisco: Symbolic Regression for Stoichiometric Dynamical Systems via Monte Carlo Graph Search

Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model

A DIRT-T Approach to Unsupervised Domain Adaptation

Practical One-Shot Federated Learning for Cross-Silo Setting

Practical Coreset Constructions for Machine Learning

Maxout Networks

Categorizing Variants of Goodhart's Law

One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control

Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy Evaluation

Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions

Convex Optimization in Julia

A Fourier Space Perspective on Diffusion Models

Robust conditional dimension reduction for dissimilarity data

Causal Foundation Models

Energy Flow Networks: Deep Sets for Particle Jets

Prediction-Powered Data Fusion for Treatment Effect Estimation

Policy Gradient for Coherent Risk Measures

A review of mean-shift algorithms for clustering

Subject-Aware Contrastive Learning for Biosignals

CASTER: Predicting Drug Interactions with Chemical Substructure Representation