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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781 to 840 of 6,775

Controlling false discoveries in high-dimensional situations: Boosting with stability selection
Benjamin Hofner, Luigi Boccuto, Markus Göker
stat.MLstat.APstat.COarXiv:1411.1285v12014
How Powerful are Performance Predictors in Neural Architecture Search?
Colin White, Arber Zela, Binxin Ru +2
cs.LGcs.NEstat.MLarXiv:2104.01177v22021
Invariant Causal Prediction for Block MDPs
Amy Zhang, Clare Lyle, Shagun Sodhani +5
cs.LGcs.AIstat.MLarXiv:2003.06016v22020
Faster Wasserstein Distance Estimation with the Sinkhorn Divergence
Lenaic Chizat, Pierre Roussillon, Flavien Léger +2
math.OCmath.STstat.MLarXiv:2006.08172v22020
ClustGeo: an R package for hierarchical clustering with spatial constraints
Marie Chavent, Vanessa Kuentz-Simonet, Amaury Labenne +1
stat.COstat.MLarXiv:1707.03897v22017
NAOMI: Non-Autoregressive Multiresolution Sequence Imputation
Yukai Liu, Rose Yu, Stephan Zheng +2
cs.LGstat.MLarXiv:1901.10946v32019
Continuum limit of total variation on point clouds
Nicolás García Trillos, Dejan Slepčev
math.STmath.APstat.MLarXiv:1403.6355v32014
Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors
Rico Jonschkowski, Divyam Rastogi, Oliver Brock
cs.LGcs.AIcs.ROarXiv:1805.11122v22018
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints
Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson
cs.LGmath.DSphysics.comp-pharXiv:2010.13581v12020
Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space
Nikolas Nüsken, Lorenz Richter
math.OCcs.LGmath.NAarXiv:2005.05409v22020
TokenCut: Segmenting Objects in Images and Videos with Self-supervised Transformer and Normalized Cut
Yangtao Wang, Xi Shen, Yuan Yuan +5
cs.CVstat.MLarXiv:2209.00383v32022
Neural Thompson Sampling
Weitong Zhang, Dongruo Zhou, Lihong Li +1
cs.LGstat.MLarXiv:2010.00827v22020
Semantic Human Matting
Quan Chen, Tiezheng Ge, Yanyu Xu +3
cs.CVcs.GRcs.LGarXiv:1809.01354v22018
Stochastic reconstruction of an oolitic limestone by generative adversarial networks
Lukas Mosser, Olivier Dubrule, Martin J. Blunt
cs.CVphysics.geo-phstat.MLarXiv:1712.02854v12017
Vision-based Navigation with Language-based Assistance via Imitation Learning with Indirect Intervention
Khanh Nguyen, Debadeepta Dey, Chris Brockett +1
cs.LGcs.CLcs.CVarXiv:1812.04155v42018
Neural networks for option pricing and hedging: a literature review
Johannes Ruf, Weiguan Wang
q-fin.CPcs.LGq-fin.RMarXiv:1911.05620v22019
Active Semi-Supervised Learning Using Sampling Theory for Graph Signals
Akshay Gadde, Aamir Anis, Antonio Ortega
cs.LGstat.MLarXiv:1405.4324v12014
A Survey of Complex-Valued Neural Networks
Joshua Bassey, Lijun Qian, Xianfang Li
stat.MLcs.LGarXiv:2101.12249v12021
A Sociotechnical View of Algorithmic Fairness
Mateusz Dolata, Stefan Feuerriegel, Gerhard Schwabe
cs.CYcs.LGstat.MLarXiv:2110.09253v12021
Invariant Information Bottleneck for Domain Generalization
Bo Li, Yifei Shen, Yezhen Wang +6
cs.LGstat.MLarXiv:2106.06333v62021
Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates
Ilija Ilievski, Taimoor Akhtar, Jiashi Feng +1
cs.AIcs.LGstat.MLarXiv:1607.08316v22016
Evaluation of ChatGPT-Generated Medical Responses: A Systematic Review and Meta-Analysis
Qiuhong Wei, Zhengxiong Yao, Ying Cui +3
stat.MEstat.MLarXiv:2310.08410v12023
A survey on domain adaptation theory: learning bounds and theoretical guarantees
Ievgen Redko, Emilie Morvant, Amaury Habrard +2
cs.LGstat.MLarXiv:2004.11829v62020
Hybrid-FL for Wireless Networks: Cooperative Learning Mechanism Using Non-IID Data
Naoya Yoshida, Takayuki Nishio, Masahiro Morikura +2
cs.LGcs.DCstat.MLarXiv:1905.07210v32019
FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning
Felix Sattler, Tim Korjakow, Roman Rischke +1
cs.LGcs.DCstat.MLarXiv:2102.02514v12021
Balanced Policy Evaluation and Learning
Nathan Kallus
stat.MLcs.LGmath.OCarXiv:1705.07384v22017
Communication-Computation Trade-Off in Resource-Constrained Edge Inference
Jiawei Shao, Jun Zhang
cs.LGeess.SPstat.MLarXiv:2006.02166v22020
A Conformal Prediction Approach to Explore Functional Data
Jing Lei, Alessandro Rinaldo, Larry Wasserman
stat.MLcs.LGarXiv:1302.6452v12013
A Method for Finding Structured Sparse Solutions to Non-negative Least Squares Problems with Applications
Ernie Esser, Yifei Lou, Jack Xin
stat.MLstat.APstat.COarXiv:1301.0413v12013
Efficient Learning and Symmetry Discovery under Exact Invariances
Ashkan Soleymani, Behrooz Tahmasebi, Patrick Jaillet +1
cs.LGstat.MLarXiv:2609.07031v12026
Transformer-based World Models Are Happy With 100k Interactions
Jan Robine, Marc Höftmann, Tobias Uelwer +1
cs.LGcs.AIstat.MLarXiv:2303.07109v12023
Ensemble Kalman Inversion: A Derivative-Free Technique For Machine Learning Tasks
Nikola B. Kovachki, Andrew M. Stuart
cs.LGmath.OCstat.MLarXiv:1808.03620v12018
Avoiding pathologies in very deep networks
David Duvenaud, Oren Rippel, Ryan P. Adams +1
stat.MLcs.LGarXiv:1402.5836v32014
Relational Message Passing for Knowledge Graph Completion
Hongwei Wang, Hongyu Ren, Jure Leskovec
cs.LGstat.MLarXiv:2002.06757v22020
One-Pass Incomplete Multi-view Clustering
Menglei Hu, Songcan Chen
cs.LGstat.MLarXiv:1903.00637v12019
Iterative Reweighted Minimization Methods for $l_p$ Regularized Unconstrained Nonlinear Programming
Zhaosong Lu
math.OCcs.LGstat.COarXiv:1210.0066v12012
EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis
Chaoqi Wang, Roger Grosse, Sanja Fidler +1
cs.LGstat.MLarXiv:1905.05934v12019
Mumford-Shah Loss Functional for Image Segmentation with Deep Learning
Boah Kim, Jong Chul Ye
cs.CVcs.LGstat.MLarXiv:1904.02872v22019
Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks
Andrey Malinin, Neil Band, Ganshin +15
cs.LGcs.AIstat.MLarXiv:2107.07455v32021
Modeling Irregular Time Series with Continuous Recurrent Units
Mona Schirmer, Mazin Eltayeb, Stefan Lessmann +1
cs.LGstat.MLarXiv:2111.11344v32021
Do We Need Zero Training Loss After Achieving Zero Training Error?
Takashi Ishida, Ikko Yamane, Tomoya Sakai +2
cs.LGstat.MLarXiv:2002.08709v22020
Robust Training under Label Noise by Over-parameterization
Sheng Liu, Zhihui Zhu, Qing Qu +1
cs.LGcs.AIcs.CVarXiv:2202.14026v22022
Sinkformers: Transformers with Doubly Stochastic Attention
Michael E. Sander, Pierre Ablin, Mathieu Blondel +1
cs.LGstat.MLarXiv:2110.11773v22021
Subspace Inference for Bayesian Deep Learning
Pavel Izmailov, Wesley J. Maddox, Polina Kirichenko +3
cs.LGstat.MLarXiv:1907.07504v12019
Changepoint Detection in the Presence of Outliers
Paul Fearnhead, Guillem Rigaill
stat.MEstat.APstat.COarXiv:1609.07363v22016
Sample-efficient Cross-Entropy Method for Real-time Planning
Cristina Pinneri, Shambhuraj Sawant, Sebastian Blaes +4
cs.LGcs.ROstat.MLarXiv:2008.06389v12020
Finite-Sample Analysis of Proximal Gradient TD Algorithms
Bo Liu, Ji Liu, Mohammad Ghavamzadeh +2
cs.LGstat.MLarXiv:2006.14364v22020
Learning with Bounded Instance- and Label-dependent Label Noise
Jiacheng Cheng, Tongliang Liu, Kotagiri Ramamohanarao +1
stat.MLcs.LGarXiv:1709.03768v32017
Improving the Performance of Unimodal Dynamic Hand-Gesture Recognition with Multimodal Training
Mahdi Abavisani, Hamid Reza Vaezi Joze, Vishal M. Patel
cs.CVcs.AIcs.HCarXiv:1812.06145v22018
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding
David Klindt, Lukas Schott, Yash Sharma +4
stat.MLcs.CVcs.LGarXiv:2007.10930v22020
Deep Video Generation, Prediction and Completion of Human Action Sequences
Haoye Cai, Chunyan Bai, Yu-Wing Tai +1
cs.CVstat.MLarXiv:1711.08682v32017
The deterministic information bottleneck
DJ Strouse, David J Schwab
q-bio.NCcond-mat.stat-mechcs.ITarXiv:1604.00268v22016
Deep Barycentric Regression for Optimal Transport Map Estimation and its Statistical Optimality
Kunwoong Kim, Insung Kong, Yongdai Kim
cs.LGcs.AIstat.MLarXiv:2609.06598v12026
Can we trust deep learning models diagnosis? The impact of domain shift in chest radiograph classification
Eduardo H. P. Pooch, Pedro L. Ballester, Rodrigo C. Barros
eess.IVcs.AIcs.CVarXiv:1909.01940v22019
Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems
Sami Khairy, Ruslan Shaydulin, Lukasz Cincio +2
cs.LGquant-phstat.MLarXiv:1911.11071v12019
Visual Explanations From Deep 3D Convolutional Neural Networks for Alzheimer's Disease Classification
Chengliang Yang, Anand Rangarajan, Sanjay Ranka
cs.CVcs.AIcs.LGarXiv:1803.02544v32018
Few-Shot Learning with Metric-Agnostic Conditional Embeddings
Nathan Hilliard, Lawrence Phillips, Scott Howland +3
cs.LGstat.MLarXiv:1802.04376v12018
On the generalization of GAN image forensics
Xinsheng Xuan, Bo Peng, Wei Wang +1
cs.CVcs.LGstat.MLarXiv:1902.11153v22019
Multi-Stage Multi-Task Feature Learning
Pinghua Gong, Jieping Ye, Changshui Zhang
stat.MLarXiv:1210.5806v12012
Quantum Perceptron Models
Nathan Wiebe, Ashish Kapoor, Krysta M Svore
quant-phcs.LGstat.MLarXiv:1602.04799v12016

Machine Learning (stat)

Controlling false discoveries in high-dimensional situations: Boosting with stability selection

How Powerful are Performance Predictors in Neural Architecture Search?

Invariant Causal Prediction for Block MDPs

Faster Wasserstein Distance Estimation with the Sinkhorn Divergence

ClustGeo: an R package for hierarchical clustering with spatial constraints

NAOMI: Non-Autoregressive Multiresolution Sequence Imputation

Continuum limit of total variation on point clouds

Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors

Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints

Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space

TokenCut: Segmenting Objects in Images and Videos with Self-supervised Transformer and Normalized Cut

Neural Thompson Sampling

Semantic Human Matting

Stochastic reconstruction of an oolitic limestone by generative adversarial networks

Vision-based Navigation with Language-based Assistance via Imitation Learning with Indirect Intervention

Neural networks for option pricing and hedging: a literature review

Active Semi-Supervised Learning Using Sampling Theory for Graph Signals

A Survey of Complex-Valued Neural Networks

A Sociotechnical View of Algorithmic Fairness

Invariant Information Bottleneck for Domain Generalization

Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates

Evaluation of ChatGPT-Generated Medical Responses: A Systematic Review and Meta-Analysis

A survey on domain adaptation theory: learning bounds and theoretical guarantees

Hybrid-FL for Wireless Networks: Cooperative Learning Mechanism Using Non-IID Data

FedAUX: Leveraging Unlabeled Auxiliary Data in Federated Learning

Balanced Policy Evaluation and Learning

Communication-Computation Trade-Off in Resource-Constrained Edge Inference

A Conformal Prediction Approach to Explore Functional Data

A Method for Finding Structured Sparse Solutions to Non-negative Least Squares Problems with Applications

Efficient Learning and Symmetry Discovery under Exact Invariances

Transformer-based World Models Are Happy With 100k Interactions

Ensemble Kalman Inversion: A Derivative-Free Technique For Machine Learning Tasks

Avoiding pathologies in very deep networks

Relational Message Passing for Knowledge Graph Completion

One-Pass Incomplete Multi-view Clustering

Iterative Reweighted Minimization Methods for $l_p$ Regularized Unconstrained Nonlinear Programming

EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis

Mumford-Shah Loss Functional for Image Segmentation with Deep Learning

Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks

Modeling Irregular Time Series with Continuous Recurrent Units

Do We Need Zero Training Loss After Achieving Zero Training Error?

Robust Training under Label Noise by Over-parameterization

Sinkformers: Transformers with Doubly Stochastic Attention

Subspace Inference for Bayesian Deep Learning

Changepoint Detection in the Presence of Outliers

Sample-efficient Cross-Entropy Method for Real-time Planning

Finite-Sample Analysis of Proximal Gradient TD Algorithms

Learning with Bounded Instance- and Label-dependent Label Noise

Improving the Performance of Unimodal Dynamic Hand-Gesture Recognition with Multimodal Training

Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding

Deep Video Generation, Prediction and Completion of Human Action Sequences

The deterministic information bottleneck

Deep Barycentric Regression for Optimal Transport Map Estimation and its Statistical Optimality

Can we trust deep learning models diagnosis? The impact of domain shift in chest radiograph classification

Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems

Visual Explanations From Deep 3D Convolutional Neural Networks for Alzheimer's Disease Classification

Few-Shot Learning with Metric-Agnostic Conditional Embeddings

On the generalization of GAN image forensics

Multi-Stage Multi-Task Feature Learning

Quantum Perceptron Models