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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1,141 to 1,200 of 6,792

Revisiting Membership Inference Under Realistic Assumptions
Bargav Jayaraman, Lingxiao Wang, Katherine Knipmeyer +2
cs.CRcs.LGstat.MLarXiv:2005.10881v52020
Graph-Coupled Oscillator Networks
T. Konstantin Rusch, Benjamin P. Chamberlain, James Rowbottom +2
cs.LGmath.DSstat.MLarXiv:2202.02296v22022
The Total Variation on Hypergraphs - Learning on Hypergraphs Revisited
Matthias Hein, Simon Setzer, Leonardo Jost +1
stat.MLcs.LGmath.OCarXiv:1312.5179v12013
Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems
Hyungjin Chung, Suhyeon Lee, Jong Chul Ye
cs.LGcs.AIcs.CVarXiv:2303.05754v32023
Learning to Optimize under Non-Stationarity
Wang Chi Cheung, David Simchi-Levi, Ruihao Zhu
cs.LGstat.MLarXiv:1810.03024v62018
Monotone operator equilibrium networks
Ezra Winston, J. Zico Kolter
cs.LGstat.MLarXiv:2006.08591v22020
Parallel Diffusion Models of Operator and Image for Blind Inverse Problems
Hyungjin Chung, Jeongsol Kim, Sehui Kim +1
cs.CVcs.LGstat.MLarXiv:2211.10656v12022
Spectral Clustering of Graphs with the Bethe Hessian
Alaa Saade, Florent Krzakala, Lenka Zdeborová
cond-mat.dis-nncs.SIphysics.soc-pharXiv:1406.1880v22014
Autonomous discovery in the chemical sciences part II: Outlook
Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen
q-bio.QMcs.AIcs.ROarXiv:2003.13755v12020
Bayesian Network Enhanced with Structural Reliability Methods: Methodology
Daniel Straub, Armen Der Kiureghian
stat.APstat.MEstat.MLarXiv:1203.5986v12012
Reconciling Universal and Uniform Learning with $Q$-Aggregation
Mikael Møller Høgsgaard, Patrick Rebeschini, Tobias Wegel
math.STstat.MLarXiv:2609.05041v12026
Faster Learning under Relaxed Local Differential Privacy
Cristina Butucea, Huiyun Tang, Marie-Luce Taupin
math.STstat.MLarXiv:2609.05034v12026
Deep ensemble learning for Alzheimers disease classification
Ning An, Huitong Ding, Jiaoyun Yang +2
cs.LGstat.MLarXiv:1905.12827v12019
Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments
Yi Sun, Faustino Gomez, Juergen Schmidhuber
cs.AIstat.MLarXiv:1103.5708v12011
Predictive Entropy Search for Bayesian Optimization with Unknown Constraints
José Miguel Hernández-Lobato, Michael A. Gelbart, Matthew W. Hoffman +2
stat.MLarXiv:1502.05312v22015
Hashing Algorithms for Large-Scale Learning
Ping Li, Anshumali Shrivastava, Joshua Moore +1
stat.MLcs.LGarXiv:1106.0967v12011
Bayesian State Estimation for Unobservable Distribution Systems via Deep Learning
Kursat Rasim Mestav, Jaime Luengo-Rozas, Lang Tong
stat.MLcs.LGstat.AParXiv:1811.02756v42018
When Are Nonconvex Problems Not Scary?
Ju Sun, Qing Qu, John Wright
math.OCcs.ITstat.MLarXiv:1510.06096v22015
Hidden Fluid Mechanics: A Navier-Stokes Informed Deep Learning Framework for Assimilating Flow Visualization Data
Maziar Raissi, Alireza Yazdani, George Em Karniadakis
cs.CEcs.LGphysics.flu-dynarXiv:1808.04327v12018
Sparse Signal Estimation by Maximally Sparse Convex Optimization
Ivan W. Selesnick, Ilker Bayram
cs.LGstat.MLarXiv:1302.5729v32013
ETHOS: an Online Hate Speech Detection Dataset
Ioannis Mollas, Zoe Chrysopoulou, Stamatis Karlos +1
cs.CLcs.LGstat.MLarXiv:2006.08328v22020
Efficient Algorithms and Lower Bounds for Robust Linear Regression
Ilias Diakonikolas, Weihao Kong, Alistair Stewart
cs.LGcs.CCcs.DSarXiv:1806.00040v12018
Differentially Private Fair Learning
Matthew Jagielski, Michael Kearns, Jieming Mao +4
cs.LGcs.DScs.GTarXiv:1812.02696v32018
iTAML: An Incremental Task-Agnostic Meta-learning Approach
Jathushan Rajasegaran, Salman Khan, Munawar Hayat +2
cs.LGcs.CVstat.MLarXiv:2003.11652v12020
Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise
Xuanqing Liu, Tesi Xiao, Si Si +3
cs.LGcs.AIcs.CVarXiv:1906.02355v12019
Hybrid Models for Learning to Branch
Prateek Gupta, Maxime Gasse, Elias B. Khalil +3
cs.LGmath.OCstat.MLarXiv:2006.15212v32020
Memory Limited, Streaming PCA
Ioannis Mitliagkas, Constantine Caramanis, Prateek Jain
stat.MLcs.ITcs.LGarXiv:1307.0032v12013
Robust LogitBoost and Adaptive Base Class (ABC) LogitBoost
Ping Li
cs.LGstat.MLarXiv:1203.3491v12012
Dynamics of Deep Neural Networks and Neural Tangent Hierarchy
Jiaoyang Huang, Horng-Tzer Yau
cs.LGstat.MLarXiv:1909.08156v12019
Graph Attention Auto-Encoders
Amin Salehi, Hasan Davulcu
cs.LGcs.SIstat.MLarXiv:1905.10715v12019
Excessive Invariance Causes Adversarial Vulnerability
Jörn-Henrik Jacobsen, Jens Behrmann, Richard Zemel +1
cs.LGcs.AIcs.CVarXiv:1811.00401v42018
Discrete Flow Maps
Peter Potaptchik, Jason Yim, Adhi Saravanan +3
stat.MLcs.LGarXiv:2604.09784v22026
Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process
Guy Blanc, Neha Gupta, Gregory Valiant +1
cs.LGstat.MLarXiv:1904.09080v22019
MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics
Xinchen Yan, Akash Rastogi, Ruben Villegas +5
cs.LGcs.AIcs.CVarXiv:1808.04545v12018
Learning towards Minimum Hyperspherical Energy
Weiyang Liu, Rongmei Lin, Zhen Liu +4
cs.LGcs.CVstat.MLarXiv:1805.09298v92018
Guaranteed Tensor Recovery Fused Low-rankness and Smoothness
Hailin Wang, Jiangjun Peng, Wenjin Qin +2
cs.LGcs.AIcs.CVarXiv:2302.02155v12023
Kernel-based methods for bandit convex optimization
Sébastien Bubeck, Ronen Eldan, Yin Tat Lee
cs.LGcs.DSmath.OCarXiv:1607.03084v12016
Optimal Approximation Rate of ReLU Networks in terms of Width and Depth
Zuowei Shen, Haizhao Yang, Shijun Zhang
cs.LGstat.MLarXiv:2103.00502v52021
Low-Rank Autoregressive Tensor Completion for Spatiotemporal Traffic Data Imputation
Xinyu Chen, Mengying Lei, Nicolas Saunier +1
cs.LGstat.MLarXiv:2104.14936v12021
Finite-Sample Analysis for SARSA with Linear Function Approximation
Shaofeng Zou, Tengyu Xu, Yingbin Liang
cs.LGstat.MLarXiv:1902.02234v32019
Distributed Clustering of Linear Bandits in Peer to Peer Networks
Nathan Korda, Balazs Szorenyi, Shuai Li
cs.LGcs.AIstat.MLarXiv:1604.07706v32016
Attention-Based Models for Text-Dependent Speaker Verification
F A Rezaur Rahman Chowdhury, Quan Wang, Ignacio Lopez Moreno +1
eess.AScs.LGcs.SDarXiv:1710.10470v32017
Spectral methods: crucial for machine learning, natural for quantum computers?
Vasilis Belis, Joseph Bowles, Rishabh Gupta +2
quant-phcs.LGstat.MLarXiv:2603.24654v22026
LSTM-MSNet: Leveraging Forecasts on Sets of Related Time Series with Multiple Seasonal Patterns
Kasun Bandara, Christoph Bergmeir, Hansika Hewamalage
stat.APcs.LGcs.NEarXiv:1909.04293v22019
Stop using the elbow criterion for k-means and how to choose the number of clusters instead
Erich Schubert
stat.MLcs.LGarXiv:2212.12189v12022
Data augmentation approaches for improving animal audio classification
Loris Nanni, Gianluca Maguolo, Michelangelo Paci
cs.LGcs.SDeess.ASarXiv:1912.07756v22019
Implicit Regularization in Deep Learning May Not Be Explainable by Norms
Noam Razin, Nadav Cohen
cs.LGcs.NEstat.MLarXiv:2005.06398v22020
Attention Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images
Aleksandar Vakanski, Min Xian, Phoebe Freer
eess.IVcs.LGstat.MLarXiv:1910.08978v22019
A convex model for non-negative matrix factorization and dimensionality reduction on physical space
Ernie Esser, Michael Möller, Stanley Osher +2
stat.MLarXiv:1102.0844v12011
On the Robustness of the CVPR 2018 White-Box Adversarial Example Defenses
Anish Athalye, Nicholas Carlini
cs.CVcs.CRcs.LGarXiv:1804.03286v12018
Identifiability of Causal Graphs using Functional Models
Jonas Peters, Joris Mooij, Dominik Janzing +1
cs.LGstat.MLarXiv:1202.3757v12012
Tag-Aware Ordinal Sparse Factor Analysis for Learning and Content Analytics
Andrew S. Lan, Christoph Studer, Andrew E. Waters +1
stat.MLcs.LGarXiv:1412.5967v12014
FedDANE: A Federated Newton-Type Method
Tian Li, Anit Kumar Sahu, Manzil Zaheer +3
cs.LGstat.MLarXiv:2001.01920v12020
Structured Generative Models of Natural Source Code
Chris J. Maddison, Daniel Tarlow
cs.PLcs.LGstat.MLarXiv:1401.0514v22014
Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data
Ethan Steinberg, Ken Jung, Jason A. Fries +3
cs.CLcs.LGstat.MLarXiv:2001.05295v22020
Global Convergence of Online Limited Memory BFGS
Aryan Mokhtari, Alejandro Ribeiro
math.OCcs.LGstat.MLarXiv:1409.2045v12014
CollaGAN : Collaborative GAN for Missing Image Data Imputation
Dongwook Lee, Junyoung Kim, Won-Jin Moon +1
cs.CVcs.LGstat.MLarXiv:1901.09764v32019
StarGAN-VC2: Rethinking Conditional Methods for StarGAN-Based Voice Conversion
Takuhiro Kaneko, Hirokazu Kameoka, Kou Tanaka +1
cs.SDcs.LGeess.ASarXiv:1907.12279v22019
Node Embedding over Temporal Graphs
Uriel Singer, Ido Guy, Kira Radinsky
cs.LGcs.SIstat.MLarXiv:1903.08889v32019
Continual Deep Learning by Functional Regularisation of Memorable Past
Pingbo Pan, Siddharth Swaroop, Alexander Immer +3
stat.MLcs.LGarXiv:2004.14070v42020

Machine Learning (stat)

Revisiting Membership Inference Under Realistic Assumptions

Graph-Coupled Oscillator Networks

The Total Variation on Hypergraphs - Learning on Hypergraphs Revisited

Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems

Learning to Optimize under Non-Stationarity

Monotone operator equilibrium networks

Parallel Diffusion Models of Operator and Image for Blind Inverse Problems

Spectral Clustering of Graphs with the Bethe Hessian

Autonomous discovery in the chemical sciences part II: Outlook

Bayesian Network Enhanced with Structural Reliability Methods: Methodology

Reconciling Universal and Uniform Learning with $Q$-Aggregation

Faster Learning under Relaxed Local Differential Privacy

Deep ensemble learning for Alzheimers disease classification

Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments

Predictive Entropy Search for Bayesian Optimization with Unknown Constraints

Hashing Algorithms for Large-Scale Learning

Bayesian State Estimation for Unobservable Distribution Systems via Deep Learning

When Are Nonconvex Problems Not Scary?

Hidden Fluid Mechanics: A Navier-Stokes Informed Deep Learning Framework for Assimilating Flow Visualization Data

Sparse Signal Estimation by Maximally Sparse Convex Optimization

ETHOS: an Online Hate Speech Detection Dataset

Efficient Algorithms and Lower Bounds for Robust Linear Regression

Differentially Private Fair Learning

iTAML: An Incremental Task-Agnostic Meta-learning Approach

Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise

Hybrid Models for Learning to Branch

Memory Limited, Streaming PCA

Robust LogitBoost and Adaptive Base Class (ABC) LogitBoost

Dynamics of Deep Neural Networks and Neural Tangent Hierarchy

Graph Attention Auto-Encoders

Excessive Invariance Causes Adversarial Vulnerability

Discrete Flow Maps

Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process

MT-VAE: Learning Motion Transformations to Generate Multimodal Human Dynamics

Learning towards Minimum Hyperspherical Energy

Guaranteed Tensor Recovery Fused Low-rankness and Smoothness

Kernel-based methods for bandit convex optimization

Optimal Approximation Rate of ReLU Networks in terms of Width and Depth

Low-Rank Autoregressive Tensor Completion for Spatiotemporal Traffic Data Imputation

Finite-Sample Analysis for SARSA with Linear Function Approximation

Distributed Clustering of Linear Bandits in Peer to Peer Networks

Attention-Based Models for Text-Dependent Speaker Verification

Spectral methods: crucial for machine learning, natural for quantum computers?

LSTM-MSNet: Leveraging Forecasts on Sets of Related Time Series with Multiple Seasonal Patterns

Stop using the elbow criterion for k-means and how to choose the number of clusters instead

Data augmentation approaches for improving animal audio classification

Implicit Regularization in Deep Learning May Not Be Explainable by Norms

Attention Enriched Deep Learning Model for Breast Tumor Segmentation in Ultrasound Images

A convex model for non-negative matrix factorization and dimensionality reduction on physical space

On the Robustness of the CVPR 2018 White-Box Adversarial Example Defenses

Identifiability of Causal Graphs using Functional Models

Tag-Aware Ordinal Sparse Factor Analysis for Learning and Content Analytics

FedDANE: A Federated Newton-Type Method

Structured Generative Models of Natural Source Code

Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Data

Global Convergence of Online Limited Memory BFGS

CollaGAN : Collaborative GAN for Missing Image Data Imputation

StarGAN-VC2: Rethinking Conditional Methods for StarGAN-Based Voice Conversion

Node Embedding over Temporal Graphs

Continual Deep Learning by Functional Regularisation of Memorable Past