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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3,061 to 3,120 of 6,790

Deep Survival Analysis
Rajesh Ranganath, Adler Perotte, Noémie Elhadad +1
stat.MLcs.AIstat.MEarXiv:1608.02158v22016
Nonnegative Matrix Factorization for Signal and Data Analytics: Identifiability, Algorithms, and Applications
Xiao Fu, Kejun Huang, Nicholas D. Sidiropoulos +1
eess.SPcs.LGstat.MLarXiv:1803.01257v42018
word2vec, node2vec, graph2vec, X2vec: Towards a Theory of Vector Embeddings of Structured Data
Martin Grohe
cs.LGcs.DBcs.DMarXiv:2003.12590v12020
Communication-efficient distributed SGD with Sketching
Nikita Ivkin, Daniel Rothchild, Enayat Ullah +3
cs.LGcs.DCmath.OCarXiv:1903.04488v32019
Optimizing the CVaR via Sampling
Aviv Tamar, Yonatan Glassner, Shie Mannor
stat.MLcs.AIcs.LGarXiv:1404.3862v42014
Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients
Lukas Balles, Philipp Hennig
cs.LGstat.MLarXiv:1705.07774v42017
Point Cloud GAN
Chun-Liang Li, Manzil Zaheer, Yang Zhang +2
cs.LGstat.MLarXiv:1810.05795v12018
Variational Fourier features for Gaussian processes
James Hensman, Nicolas Durrande, Arno Solin
stat.MLarXiv:1611.06740v22016
Flow-based Network Traffic Generation using Generative Adversarial Networks
Markus Ring, Daniel Schlör, Dieter Landes +1
cs.NIstat.MLarXiv:1810.07795v12018
Structured Neural Summarization
Patrick Fernandes, Miltiadis Allamanis, Marc Brockschmidt
cs.LGcs.CLcs.SEarXiv:1811.01824v42018
BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling
Lars Maaløe, Marco Fraccaro, Valentin Liévin +1
stat.MLcs.CVcs.LGarXiv:1902.02102v32019
Smoothing proximal gradient method for general structured sparse regression
Xi Chen, Qihang Lin, Seyoung Kim +2
stat.MLcs.LGmath.OCarXiv:1005.4717v42010
PathGuide: Dynamic Classifier-Free Guidance via On-Policy Transport Alignment
Avishag Nevo, Tamir Hazan
cs.LGstat.MLarXiv:2608.29107v12026
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training
Cong Fang, Hangfeng He, Qi Long +1
cs.LGcs.CVmath.OCarXiv:2101.12699v32021
Filtering Variational Objectives
Chris J. Maddison, Dieterich Lawson, George Tucker +5
cs.LGcs.AIcs.NEarXiv:1705.09279v32017
Private Stochastic Convex Optimization: Optimal Rates in Linear Time
Vitaly Feldman, Tomer Koren, Kunal Talwar
cs.LGcs.CRmath.OCarXiv:2005.04763v12020
Stochastic Optimization of Sorting Networks via Continuous Relaxations
Aditya Grover, Eric Wang, Aaron Zweig +1
stat.MLcs.LGcs.NEarXiv:1903.08850v22019
Learning Deep Kernels for Non-Parametric Two-Sample Tests
Feng Liu, Wenkai Xu, Jie Lu +3
stat.MLcs.LGstat.MEarXiv:2002.09116v32020
Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading
Jaakko Sahlsten, Joel Jaskari, Jyri Kivinen +4
eess.IVcs.CVcs.LGarXiv:1904.08764v12019
Discovering Graphical Granger Causality Using the Truncating Lasso Penalty
Ali Shojaie, George Michailidis
stat.MLq-bio.MNarXiv:1007.0499v12010
GraphNVP: An Invertible Flow Model for Generating Molecular Graphs
Kaushalya Madhawa, Katushiko Ishiguro, Kosuke Nakago +1
stat.MLcs.AIcs.LGarXiv:1905.11600v12019
Automatic Relevance Determination in Nonnegative Matrix Factorization with the β-Divergence
Vincent Y. F. Tan, Cédric Févotte
stat.MLstat.MEarXiv:1111.6085v32011
Learning a Driving Simulator
Eder Santana, George Hotz
cs.LGstat.MLarXiv:1608.01230v12016
Mixture Proportion Estimation via Kernel Embedding of Distributions
Harish G. Ramaswamy, Clayton Scott, Ambuj Tewari
cs.LGstat.MLarXiv:1603.02501v22016
Stochastic bandits robust to adversarial corruptions
Thodoris Lykouris, Vahab Mirrokni, Renato Paes Leme
cs.LGcs.DScs.GTarXiv:1803.09353v12018
Survey on Deep Neural Networks in Speech and Vision Systems
Mahbubul Alam, Manar D. Samad, Lasitha Vidyaratne +2
cs.CVcs.LGcs.NEarXiv:1908.07656v22019
Collaborative Learning for Deep Neural Networks
Guocong Song, Wei Chai
stat.MLcs.CVcs.LGarXiv:1805.11761v22018
On the Impact of the Activation Function on Deep Neural Networks Training
Soufiane Hayou, Arnaud Doucet, Judith Rousseau
stat.MLcs.AIcs.LGarXiv:1902.06853v22019
GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy Efficient Inference
Ali Hadi Zadeh, Isak Edo, Omar Mohamed Awad +1
cs.LGcs.ARstat.MLarXiv:2005.03842v22020
Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse
James Lucas, George Tucker, Roger Grosse +1
cs.LGstat.MLarXiv:1911.02469v12019
Restricting the Flow: Information Bottlenecks for Attribution
Karl Schulz, Leon Sixt, Federico Tombari +1
stat.MLcs.CVcs.LGarXiv:2001.00396v42020
A network approach to topic models
Martin Gerlach, Tiago P. Peixoto, Eduardo G. Altmann
stat.MLcs.CLphysics.data-anarXiv:1708.01677v22017
Revisiting Model Stitching to Compare Neural Representations
Yamini Bansal, Preetum Nakkiran, Boaz Barak
cs.LGstat.MLarXiv:2106.07682v12021
Towards Automated Machine Learning: Evaluation and Comparison of AutoML Approaches and Tools
Anh Truong, Austin Walters, Jeremy Goodsitt +3
cs.LGstat.MLarXiv:1908.05557v22019
Toward Intelligent Vehicular Networks: A Machine Learning Framework
Le Liang, Hao Ye, Geoffrey Ye Li
cs.ITcs.LGstat.MLarXiv:1804.00338v32018
Failures of Gradient-Based Deep Learning
Shai Shalev-Shwartz, Ohad Shamir, Shaked Shammah
cs.LGcs.NEstat.MLarXiv:1703.07950v22017
Uncertainty-aware Short-term Motion Prediction of Traffic Actors for Autonomous Driving
Nemanja Djuric, Vladan Radosavljevic, Henggang Cui +5
cs.LGcs.CVcs.ROarXiv:1808.05819v32018
Signed random Fourier features for fast density estimation with indefinite kernels
Xie Wang, Nicolas Langrené, Wen Chen
stat.COcs.LGmath.PRarXiv:2608.29265v12026
Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control
Sanket Kamthe, Marc Peter Deisenroth
eess.SYstat.MLarXiv:1706.06491v22017
AdaGAN: Boosting Generative Models
Ilya Tolstikhin, Sylvain Gelly, Olivier Bousquet +2
stat.MLcs.LGarXiv:1701.02386v22017
Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging
Luis Muñoz-González, Kenneth T. Co, Emil C. Lupu
stat.MLcs.DCcs.LGarXiv:1909.05125v12019
Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings
Feiyang Pan, Shuokai Li, Xiang Ao +2
cs.LGcs.IRstat.MLarXiv:1904.11547v12019
Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder
Zhisheng Xiao, Qing Yan, Yali Amit
cs.LGcs.CVstat.MLarXiv:2003.02977v32020
Poisoning Attacks to Graph-Based Recommender Systems
Minghong Fang, Guolei Yang, Neil Zhenqiang Gong +1
cs.IRcs.CRcs.LGarXiv:1809.04127v12018
Deep Successor Reinforcement Learning
Tejas D. Kulkarni, Ardavan Saeedi, Simanta Gautam +1
stat.MLcs.AIcs.LGarXiv:1606.02396v12016
Dynamic Model Pruning with Feedback
Tao Lin, Sebastian U. Stich, Luis Barba +2
cs.LGstat.MLarXiv:2006.07253v12020
Spectral Methods for Data Science: A Statistical Perspective
Yuxin Chen, Yuejie Chi, Jianqing Fan +1
stat.MLcs.ITcs.LGarXiv:2012.08496v22020
Graph Backdoor
Zhaohan Xi, Ren Pang, Shouling Ji +1
cs.LGcs.CRstat.MLarXiv:2006.11890v52020
Bayesian Optimization with Gradients
Jian Wu, Matthias Poloczek, Andrew Gordon Wilson +1
stat.MLcs.AIcs.LGarXiv:1703.04389v32017
Adaptive Quantization for Deep Neural Network
Yiren Zhou, Seyed-Mohsen Moosavi-Dezfooli, Ngai-Man Cheung +1
cs.LGstat.MLarXiv:1712.01048v12017
General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models
Christoph Molnar, Gunnar König, Julia Herbinger +6
stat.MLcs.LGarXiv:2007.04131v22020
Machine Unlearning for Random Forests
Jonathan Brophy, Daniel Lowd
cs.LGstat.MLarXiv:2009.05567v22020
MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies
Xue Bin Peng, Michael Chang, Grace Zhang +2
cs.LGstat.MLarXiv:1905.09808v12019
Implementing neural network mixed-effects models in Template Model Builder (TMB)
Nan Zheng, Hoi Yiu Cheung, Vibhu Sharma +2
stat.MLcs.LGarXiv:2608.31133v12026
An Intersectional Definition of Fairness
James Foulds, Rashidul Islam, Kamrun Naher Keya +1
cs.LGcs.CYstat.MLarXiv:1807.08362v32018
Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study
Aditya Siddhant, Zachary C. Lipton
cs.CLcs.LGstat.MLarXiv:1808.05697v32018
Over-the-Air Federated Learning from Heterogeneous Data
Tomer Sery, Nir Shlezinger, Kobi Cohen +1
cs.LGcs.ITstat.MLarXiv:2009.12787v22020
Fit without fear: remarkable mathematical phenomena of deep learning through the prism of interpolation
Mikhail Belkin
stat.MLcs.LGmath.STarXiv:2105.14368v12021
Learning the Geometry of Admissible Hypotheses through Inductive Bias in Training Distributions
James Crowley, Faez Ahmed, Anton van Beek
stat.MLcs.LGarXiv:2608.31028v12026
The Nonparanormal SKEPTIC
Han Liu, Fang Han, Ming Yuan +2
stat.MEcs.LGstat.MLarXiv:1206.6488v12012

Machine Learning (stat)

Deep Survival Analysis

Nonnegative Matrix Factorization for Signal and Data Analytics: Identifiability, Algorithms, and Applications

word2vec, node2vec, graph2vec, X2vec: Towards a Theory of Vector Embeddings of Structured Data

Communication-efficient distributed SGD with Sketching

Optimizing the CVaR via Sampling

Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients

Point Cloud GAN

Variational Fourier features for Gaussian processes

Flow-based Network Traffic Generation using Generative Adversarial Networks

Structured Neural Summarization

BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling

Smoothing proximal gradient method for general structured sparse regression

PathGuide: Dynamic Classifier-Free Guidance via On-Policy Transport Alignment

Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training

Filtering Variational Objectives

Private Stochastic Convex Optimization: Optimal Rates in Linear Time

Stochastic Optimization of Sorting Networks via Continuous Relaxations

Learning Deep Kernels for Non-Parametric Two-Sample Tests

Deep Learning Fundus Image Analysis for Diabetic Retinopathy and Macular Edema Grading

Discovering Graphical Granger Causality Using the Truncating Lasso Penalty

GraphNVP: An Invertible Flow Model for Generating Molecular Graphs

Automatic Relevance Determination in Nonnegative Matrix Factorization with the β-Divergence

Learning a Driving Simulator

Mixture Proportion Estimation via Kernel Embedding of Distributions

Stochastic bandits robust to adversarial corruptions

Survey on Deep Neural Networks in Speech and Vision Systems

Collaborative Learning for Deep Neural Networks

On the Impact of the Activation Function on Deep Neural Networks Training

GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy Efficient Inference

Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse

Restricting the Flow: Information Bottlenecks for Attribution

A network approach to topic models

Revisiting Model Stitching to Compare Neural Representations

Towards Automated Machine Learning: Evaluation and Comparison of AutoML Approaches and Tools

Toward Intelligent Vehicular Networks: A Machine Learning Framework

Failures of Gradient-Based Deep Learning

Uncertainty-aware Short-term Motion Prediction of Traffic Actors for Autonomous Driving

Signed random Fourier features for fast density estimation with indefinite kernels

Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control

AdaGAN: Boosting Generative Models

Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging

Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings

Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder

Poisoning Attacks to Graph-Based Recommender Systems

Deep Successor Reinforcement Learning

Dynamic Model Pruning with Feedback

Spectral Methods for Data Science: A Statistical Perspective

Graph Backdoor

Bayesian Optimization with Gradients

Adaptive Quantization for Deep Neural Network

General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models

Machine Unlearning for Random Forests

MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies

Implementing neural network mixed-effects models in Template Model Builder (TMB)

An Intersectional Definition of Fairness

Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study

Over-the-Air Federated Learning from Heterogeneous Data

Fit without fear: remarkable mathematical phenomena of deep learning through the prism of interpolation

Learning the Geometry of Admissible Hypotheses through Inductive Bias in Training Distributions

The Nonparanormal SKEPTIC