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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1,081 to 1,140 of 6,792

Inhomogeneous Hypergraph Clustering with Applications
Pan Li, Olgica Milenkovic
cs.LGstat.MLarXiv:1709.01249v42017
Attention-based Convolutional Neural Network for Weakly Labeled Human Activities Recognition with Wearable Sensors
Kun Wang, Jun He, Lei Zhang
cs.LGstat.MLarXiv:1903.10909v22019
Contrastive Learning for Debiased Candidate Generation in Large-Scale Recommender Systems
Chang Zhou, Jianxin Ma, Jianwei Zhang +2
cs.IRcs.LGcs.SIarXiv:2005.12964v92020
Deep-IRT: Make Deep Learning Based Knowledge Tracing Explainable Using Item Response Theory
Chun-Kit Yeung
cs.LGcs.AIstat.MLarXiv:1904.11738v12019
On the Effectiveness of Least Squares Generative Adversarial Networks
Xudong Mao, Qing Li, Haoran Xie +3
cs.CVcs.LGstat.MLarXiv:1712.06391v22017
Causal Inference on Discrete Data using Additive Noise Models
Jonas Peters, Dominik Janzing, Bernhard Schölkopf
stat.MLarXiv:0911.0280v12009
Accident Risk Prediction based on Heterogeneous Sparse Data: New Dataset and Insights
Sobhan Moosavi, Mohammad Hossein Samavatian, Srinivasan Parthasarathy +2
cs.LGcs.DBstat.MLarXiv:1909.09638v12019
Bayesian Neural Network Priors Revisited
Vincent Fortuin, Adrià Garriga-Alonso, Sebastian W. Ober +5
stat.MLcs.LGarXiv:2102.06571v32021
Interpreting Adversarially Trained Convolutional Neural Networks
Tianyuan Zhang, Zhanxing Zhu
cs.LGcs.CVstat.MLarXiv:1905.09797v12019
A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum
Prashant Khanduri, Siliang Zeng, Mingyi Hong +3
math.OCcs.LGstat.MLarXiv:2102.07367v32021
Low-rank Matrix Recovery from Errors and Erasures
Yudong Chen, Ali Jalali, Sujay Sanghavi +1
cs.ITstat.MLarXiv:1104.0354v22011
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks
Sanjeev Arora, Simon S. Du, Zhiyuan Li +3
cs.LGstat.MLarXiv:1910.01663v32019
Causal Transformer for Estimating Counterfactual Outcomes
Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel
cs.LGstat.MLarXiv:2204.07258v22022
Fashion-Gen: The Generative Fashion Dataset and Challenge
Negar Rostamzadeh, Seyedarian Hosseini, Thomas Boquet +4
stat.MLcs.LGarXiv:1806.08317v22018
Constraining Effective Field Theories with Machine Learning
Johann Brehmer, Kyle Cranmer, Gilles Louppe +1
hep-phphysics.data-anstat.MLarXiv:1805.00013v42018
Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach
Grant M. Rotskoff, Eric Vanden-Eijnden
stat.MLcond-mat.stat-mechcs.LGarXiv:1805.00915v32018
Deeptime: a Python library for machine learning dynamical models from time series data
Moritz Hoffmann, Martin Scherer, Tim Hempel +8
math.DScs.LGmath-pharXiv:2110.15013v22021
Stochastic Variance Reduction Methods for Policy Evaluation
Simon S. Du, Jianshu Chen, Lihong Li +2
cs.LGcs.AIeess.SYarXiv:1702.07944v22017
Deep Learning without Weight Transport
Mohamed Akrout, Collin Wilson, Peter C. Humphreys +2
cs.LGstat.MLarXiv:1904.05391v52019
Fair Generative Modeling via Weak Supervision
Kristy Choi, Aditya Grover, Trisha Singh +2
cs.LGcs.CVstat.MLarXiv:1910.12008v22019
Learning Determinantal Point Processes
Alex Kulesza, Ben Taskar
cs.LGcs.AIstat.MLarXiv:1202.3738v12012
Batched Multi-armed Bandits Problem
Zijun Gao, Yanjun Han, Zhimei Ren +1
stat.MLcs.ITcs.LGarXiv:1904.01763v32019
A GAMP Based Low Complexity Sparse Bayesian Learning Algorithm
Maher Al-Shoukairi, Philip Schniter, Bhaskar D. Rao
cs.LGstat.MLarXiv:1703.03044v22017
Pufferfish Privacy Mechanisms for Correlated Data
Shuang Song, Yizhen Wang, Kamalika Chaudhuri
cs.LGcs.CRstat.MLarXiv:1603.03977v32016
Fast Deep Learning for Automatic Modulation Classification
Sharan Ramjee, Shengtai Ju, Diyu Yang +3
eess.SPcs.AIcs.LGarXiv:1901.05850v12019
Interpretable and Steerable Sequence Learning via Prototypes
Yao Ming, Panpan Xu, Huamin Qu +1
cs.LGcs.HCstat.MLarXiv:1907.09728v12019
Measuring Compositionality in Representation Learning
Jacob Andreas
cs.LGcs.CLstat.MLarXiv:1902.07181v22019
Discovering and Achieving Goals via World Models
Russell Mendonca, Oleh Rybkin, Kostas Daniilidis +2
cs.LGcs.AIcs.CVarXiv:2110.09514v12021
Unsupervised learning of object landmarks by factorized spatial embeddings
James Thewlis, Hakan Bilen, Andrea Vedaldi
cs.CVstat.MLarXiv:1705.02193v22017
Algorithms for Approximate Minimization of the Difference Between Submodular Functions, with Applications
Rishabh Iyer, Jeff A. Bilmes
cs.LGstat.MLarXiv:1408.2051v12014
Improper Learning for Non-Stochastic Control
Max Simchowitz, Karan Singh, Elad Hazan
cs.LGmath.OCstat.MLarXiv:2001.09254v32020
Multi-Agent Connected Autonomous Driving using Deep Reinforcement Learning
Praveen Palanisamy
cs.LGcs.AIcs.MAarXiv:1911.04175v12019
Finito: A Faster, Permutable Incremental Gradient Method for Big Data Problems
Aaron J. Defazio, Tibério S. Caetano, Justin Domke
cs.LGstat.MLarXiv:1407.2710v12014
Provably Faster Algorithms for Bilevel Optimization
Junjie Yang, Kaiyi Ji, Yingbin Liang
cs.LGmath.OCstat.MLarXiv:2106.04692v22021
Better Algorithms for Stochastic Bandits with Adversarial Corruptions
Anupam Gupta, Tomer Koren, Kunal Talwar
cs.LGstat.MLarXiv:1902.08647v22019
Variational Autoencoder with Arbitrary Conditioning
Oleg Ivanov, Michael Figurnov, Dmitry Vetrov
stat.MLcs.LGarXiv:1806.02382v32018
A survey on policy search algorithms for learning robot controllers in a handful of trials
Konstantinos Chatzilygeroudis, Vassilis Vassiliades, Freek Stulp +2
cs.ROcs.AIcs.LGarXiv:1807.02303v52018
On Binscatter
Matias D. Cattaneo, Richard K. Crump, Max H. Farrell +1
econ.EMstat.MEstat.MLarXiv:1902.09608v52019
Self-Attention Based Molecule Representation for Predicting Drug-Target Interaction
Bonggun Shin, Sungsoo Park, Keunsoo Kang +1
cs.LGstat.MLarXiv:1908.06760v12019
Knowledge Matters: Importance of Prior Information for Optimization
Çağlar Gülçehre, Yoshua Bengio
cs.LGcs.CVcs.NEarXiv:1301.4083v62013
Early detection of sepsis utilizing deep learning on electronic health record event sequences
Simon Meyer Lauritsen, Mads Ellersgaard Kalør, Emil Lund Kongsgaard +4
cs.LGstat.APstat.MLarXiv:1906.02956v12019
Machine Unlearning: Linear Filtration for Logit-based Classifiers
Thomas Baumhauer, Pascal Schöttle, Matthias Zeppelzauer
cs.LGstat.MLarXiv:2002.02730v22020
Learning Collaborative Policies to Solve NP-hard Routing Problems
Minsu Kim, Jinkyoo Park, Joungho Kim
cs.LGstat.MLarXiv:2110.13987v12021
Best sources forward: domain generalization through source-specific nets
Massimiliano Mancini, Samuel Rota Bulò, Barbara Caputo +1
cs.CVcs.LGstat.MLarXiv:1806.05810v12018
Classification vs regression in overparameterized regimes: Does the loss function matter?
Vidya Muthukumar, Adhyyan Narang, Vignesh Subramanian +3
cs.LGcs.ITstat.MLarXiv:2005.08054v22020
Robust, Deep and Inductive Anomaly Detection
Raghavendra Chalapathy, Aditya Krishna Menon, Sanjay Chawla
cs.LGcs.CVstat.MLarXiv:1704.06743v32017
Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View
Shen Wang, Jibing Gong, Jinlong Wang +4
cs.LGcs.CYcs.IRarXiv:2006.13257v12020
Black-box Adversarial Attacks on Video Recognition Models
Linxi Jiang, Xingjun Ma, Shaoxiang Chen +2
cs.LGcs.CRcs.CVarXiv:1904.05181v22019
NeRF-VAE: A Geometry Aware 3D Scene Generative Model
Adam R. Kosiorek, Heiko Strathmann, Daniel Zoran +4
stat.MLcs.LGarXiv:2104.00587v12021
A statistical interpretation of spectral embedding: the generalised random dot product graph
Patrick Rubin-Delanchy, Joshua Cape, Minh Tang +1
stat.MLcs.LGarXiv:1709.05506v52017
Deep Policy Dynamic Programming for Vehicle Routing Problems
Wouter Kool, Herke van Hoof, Joaquim Gromicho +1
cs.LGstat.MLarXiv:2102.11756v22021
Graph Neural Networks: Architectures, Stability and Transferability
Luana Ruiz, Fernando Gama, Alejandro Ribeiro
cs.LGstat.MLarXiv:2008.01767v32020
Model-Based Offline Planning
Arthur Argenson, Gabriel Dulac-Arnold
cs.LGcs.AIcs.ROarXiv:2008.05556v32020
Provable Robustness of ReLU networks via Maximization of Linear Regions
Francesco Croce, Maksym Andriushchenko, Matthias Hein
cs.LGstat.MLarXiv:1810.07481v22018
Sparse High-Dimensional Regression: Exact Scalable Algorithms and Phase Transitions
Dimitris Bertsimas, Bart Van Parys
math.OCstat.MLarXiv:1709.10029v12017
AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration
Liantao Ma, Junyi Gao, Yasha Wang +6
cs.LGstat.MLarXiv:1911.12205v12019
Nesterov's Accelerated Gradient and Momentum as approximations to Regularised Update Descent
Aleksandar Botev, Guy Lever, David Barber
stat.MLcs.LGarXiv:1607.01981v22016
Reactive Soft Prototype Computing for Concept Drift Streams
Christoph Raab, Moritz Heusinger, Frank-Michael Schleif
cs.LGstat.MLarXiv:2007.05432v12020
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates
Jeffrey Negrea, Mahdi Haghifam, Gintare Karolina Dziugaite +2
stat.MLcs.ITcs.LGarXiv:1911.02151v32019
Greedy Feature Selection for Subspace Clustering
Eva L. Dyer, Aswin C. Sankaranarayanan, Richard G. Baraniuk
cs.LGmath.NAstat.MLarXiv:1303.4778v22013

Machine Learning (stat)

Inhomogeneous Hypergraph Clustering with Applications

Attention-based Convolutional Neural Network for Weakly Labeled Human Activities Recognition with Wearable Sensors

Contrastive Learning for Debiased Candidate Generation in Large-Scale Recommender Systems

Deep-IRT: Make Deep Learning Based Knowledge Tracing Explainable Using Item Response Theory

On the Effectiveness of Least Squares Generative Adversarial Networks

Causal Inference on Discrete Data using Additive Noise Models

Accident Risk Prediction based on Heterogeneous Sparse Data: New Dataset and Insights

Bayesian Neural Network Priors Revisited

Interpreting Adversarially Trained Convolutional Neural Networks

A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum

Low-rank Matrix Recovery from Errors and Erasures

Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks

Causal Transformer for Estimating Counterfactual Outcomes

Fashion-Gen: The Generative Fashion Dataset and Challenge

Constraining Effective Field Theories with Machine Learning

Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

Deeptime: a Python library for machine learning dynamical models from time series data

Stochastic Variance Reduction Methods for Policy Evaluation

Deep Learning without Weight Transport

Fair Generative Modeling via Weak Supervision

Learning Determinantal Point Processes

Batched Multi-armed Bandits Problem

A GAMP Based Low Complexity Sparse Bayesian Learning Algorithm

Pufferfish Privacy Mechanisms for Correlated Data

Fast Deep Learning for Automatic Modulation Classification

Interpretable and Steerable Sequence Learning via Prototypes

Measuring Compositionality in Representation Learning

Discovering and Achieving Goals via World Models

Unsupervised learning of object landmarks by factorized spatial embeddings

Algorithms for Approximate Minimization of the Difference Between Submodular Functions, with Applications

Improper Learning for Non-Stochastic Control

Multi-Agent Connected Autonomous Driving using Deep Reinforcement Learning

Finito: A Faster, Permutable Incremental Gradient Method for Big Data Problems

Provably Faster Algorithms for Bilevel Optimization

Better Algorithms for Stochastic Bandits with Adversarial Corruptions

Variational Autoencoder with Arbitrary Conditioning

A survey on policy search algorithms for learning robot controllers in a handful of trials

On Binscatter

Self-Attention Based Molecule Representation for Predicting Drug-Target Interaction

Knowledge Matters: Importance of Prior Information for Optimization

Early detection of sepsis utilizing deep learning on electronic health record event sequences

Machine Unlearning: Linear Filtration for Logit-based Classifiers

Learning Collaborative Policies to Solve NP-hard Routing Problems

Best sources forward: domain generalization through source-specific nets

Classification vs regression in overparameterized regimes: Does the loss function matter?

Robust, Deep and Inductive Anomaly Detection

Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View

Black-box Adversarial Attacks on Video Recognition Models

NeRF-VAE: A Geometry Aware 3D Scene Generative Model

A statistical interpretation of spectral embedding: the generalised random dot product graph

Deep Policy Dynamic Programming for Vehicle Routing Problems

Graph Neural Networks: Architectures, Stability and Transferability

Model-Based Offline Planning

Provable Robustness of ReLU networks via Maximization of Linear Regions

Sparse High-Dimensional Regression: Exact Scalable Algorithms and Phase Transitions

AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration

Nesterov's Accelerated Gradient and Momentum as approximations to Regularised Update Descent

Reactive Soft Prototype Computing for Concept Drift Streams

Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates

Greedy Feature Selection for Subspace Clustering