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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4,321 to 4,380 of 6,775

Compressed Sensing for Energy-Efficient Wireless Telemonitoring of Noninvasive Fetal ECG via Block Sparse Bayesian Learning
Zhilin Zhang, Tzyy-Ping Jung, Scott Makeig +1
stat.MLcs.LGstat.AParXiv:1205.1287v72012
SPoC: Search-based Pseudocode to Code
Sumith Kulal, Panupong Pasupat, Kartik Chandra +4
cs.LGcs.CLcs.PLarXiv:1906.04908v12019
The Vendi Score: A Diversity Evaluation Metric for Machine Learning
Dan Friedman, Adji Bousso Dieng
cs.LGcond-mat.mtrl-scistat.MLarXiv:2210.02410v22022
Transformer Dissection: A Unified Understanding of Transformer's Attention via the Lens of Kernel
Yao-Hung Hubert Tsai, Shaojie Bai, Makoto Yamada +2
cs.LGstat.MLarXiv:1908.11775v42019
Proving the Lottery Ticket Hypothesis: Pruning is All You Need
Eran Malach, Gilad Yehudai, Shai Shalev-Shwartz +1
cs.LGstat.MLarXiv:2002.00585v12020
Embedding Logical Queries on Knowledge Graphs
William L. Hamilton, Payal Bajaj, Marinka Zitnik +2
cs.SIcs.LGstat.MLarXiv:1806.01445v42018
The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning
Siyuan Ma, Raef Bassily, Mikhail Belkin
cs.LGstat.MLarXiv:1712.06559v32017
Learning mixtures of spherical Gaussians: moment methods and spectral decompositions
Daniel Hsu, Sham M. Kakade
cs.LGstat.MLarXiv:1206.5766v42012
Latent Space Oddity: on the Curvature of Deep Generative Models
Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg
stat.MLarXiv:1710.11379v32017
Paris-Lille-3D: a large and high-quality ground truth urban point cloud dataset for automatic segmentation and classification
Xavier Roynard, Jean-Emmanuel Deschaud, François Goulette
cs.LGcs.CVstat.MLarXiv:1712.00032v22017
Fast low-rank estimation by projected gradient descent: General statistical and algorithmic guarantees
Yudong Chen, Martin J. Wainwright
math.STcs.LGstat.MLarXiv:1509.03025v12015
Simple random search provides a competitive approach to reinforcement learning
Horia Mania, Aurelia Guy, Benjamin Recht
cs.LGcs.AImath.OCarXiv:1803.07055v12018
Deep Structural Causal Models for Tractable Counterfactual Inference
Nick Pawlowski, Daniel C. Castro, Ben Glocker
stat.MLcs.LGarXiv:2006.06485v22020
Dynamic Backdoor Attacks Against Machine Learning Models
Ahmed Salem, Rui Wen, Michael Backes +2
cs.CRcs.LGstat.MLarXiv:2003.03675v22020
Large-Scale Representation Learning on Graphs via Bootstrapping
Shantanu Thakoor, Corentin Tallec, Mohammad Gheshlaghi Azar +5
cs.LGcs.SIstat.MLarXiv:2102.06514v32021
Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation
Diederik P. Kingma, Ruiqi Gao
cs.LGcs.AIstat.MLarXiv:2303.00848v72023
Clustering Stability: An Overview
Ulrike von Luxburg
stat.MLarXiv:1007.1075v12010
Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift
Zachary Nado, Shreyas Padhy, D. Sculley +3
cs.LGstat.MLarXiv:2006.10963v32020
Distribution-Free, Risk-Controlling Prediction Sets
Stephen Bates, Anastasios Angelopoulos, Lihua Lei +2
cs.LGcs.AIcs.CVarXiv:2101.02703v32021
Learning Latent Block Structure in Weighted Networks
Christopher Aicher, Abigail Z. Jacobs, Aaron Clauset
stat.MLcs.SIphysics.data-anarXiv:1404.0431v22014
GANS for Sequences of Discrete Elements with the Gumbel-softmax Distribution
Matt J. Kusner, José Miguel Hernández-Lobato
stat.MLcs.LGarXiv:1611.04051v12016
Truncated Back-propagation for Bilevel Optimization
Amirreza Shaban, Ching-An Cheng, Nathan Hatch +1
cs.LGstat.MLarXiv:1810.10667v22018
Flexible statistical inference for mechanistic models of neural dynamics
Jan-Matthis Lueckmann, Pedro J. Goncalves, Giacomo Bassetto +3
stat.MLarXiv:1711.01861v12017
Adaptive Cross-Modal Few-Shot Learning
Chen Xing, Negar Rostamzadeh, Boris N. Oreshkin +1
cs.LGstat.MLarXiv:1902.07104v32019
Generalization and Exploration via Randomized Value Functions
Ian Osband, Benjamin Van Roy, Zheng Wen
stat.MLcs.AIcs.LGarXiv:1402.0635v32014
Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO
Logan Engstrom, Andrew Ilyas, Shibani Santurkar +4
cs.LGcs.ROstat.MLarXiv:2005.12729v12020
Multi-Level Variational Autoencoder: Learning Disentangled Representations from Grouped Observations
Diane Bouchacourt, Ryota Tomioka, Sebastian Nowozin
cs.LGstat.MLarXiv:1705.08841v12017
Deep Exploration via Randomized Value Functions
Ian Osband, Benjamin Van Roy, Daniel Russo +1
stat.MLcs.AIcs.LGarXiv:1703.07608v52017
Machine Learning and Deep Learning -- A review for Ecologists
Maximilian Pichler, Florian Hartig
q-bio.QMstat.MLarXiv:2204.05023v32022
Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design
Andrew Campbell, Jason Yim, Regina Barzilay +2
stat.MLcs.LGq-bio.QMarXiv:2402.04997v22024
Convergence Time Optimization for Federated Learning over Wireless Networks
Mingzhe Chen, H. Vincent Poor, Walid Saad +1
cs.LGcs.ITcs.NIarXiv:2001.07845v22020
Unsupervised speech representation learning using WaveNet autoencoders
Jan Chorowski, Ron J. Weiss, Samy Bengio +1
cs.LGeess.ASstat.MLarXiv:1901.08810v22019
Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification
Shiqi Wang, Huan Zhang, Kaidi Xu +4
cs.LGcs.AIcs.CRarXiv:2103.06624v22021
Online Learning under Delayed Feedback
Pooria Joulani, András György, Csaba Szepesvári
cs.LGcs.AIstat.MLarXiv:1306.0686v22013
Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddings
Thomas Manzini, Yao Chong Lim, Yulia Tsvetkov +1
cs.CLcs.LGstat.MLarXiv:1904.04047v32019
Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks
Yuanzhi Li, Colin Wei, Tengyu Ma
cs.LGstat.MLarXiv:1907.04595v22019
Path-SGD: Path-Normalized Optimization in Deep Neural Networks
Behnam Neyshabur, Ruslan Salakhutdinov, Nathan Srebro
cs.LGcs.CVcs.NEarXiv:1506.02617v12015
Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization
John Miller, Rohan Taori, Aditi Raghunathan +6
cs.LGstat.MLarXiv:2107.04649v22021
Surpassing Human-Level Face Verification Performance on LFW with GaussianFace
Chaochao Lu, Xiaoou Tang
cs.CVcs.LGstat.MLarXiv:1404.3840v32014
The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification
Been Kim, Cynthia Rudin, Julie Shah
stat.MLcs.LGarXiv:1503.01161v12015
Machine Learning that Matters
Kiri Wagstaff
cs.LGcs.AIstat.MLarXiv:1206.4656v12012
Generating Steganographic Images via Adversarial Training
Jamie Hayes, George Danezis
stat.MLcs.CRcs.MMarXiv:1703.00371v32017
Provable Bounds for Learning Some Deep Representations
Sanjeev Arora, Aditya Bhaskara, Rong Ge +1
cs.LGcs.AIstat.MLarXiv:1310.6343v12013
A deep matrix factorization method for learning attribute representations
George Trigeorgis, Konstantinos Bousmalis, Stefanos Zafeiriou +1
cs.CVcs.LGstat.MLarXiv:1509.03248v12015
Early stopping and non-parametric regression: An optimal data-dependent stopping rule
Garvesh Raskutti, Martin J. Wainwright, Bin Yu
stat.MLarXiv:1306.3574v12013
Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy
Stanislav Nikolov, Sam Blackwell, Alexei Zverovitch +26
cs.CVcs.LGcs.NEarXiv:1809.04430v32018
Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks
Reinhard Heckel, Paul Hand
cs.CVcs.LGstat.MLarXiv:1810.03982v22018
SHINE: Signed Heterogeneous Information Network Embedding for Sentiment Link Prediction
Hongwei Wang, Fuzheng Zhang, Min Hou +3
stat.MLcs.IRcs.LGarXiv:1712.00732v12017
Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks
Pratik Chaudhari, Stefano Soatto
cs.LGcond-mat.stat-mechmath.OCarXiv:1710.11029v22017
Stochastic modified equations and adaptive stochastic gradient algorithms
Qianxiao Li, Cheng Tai, Weinan E
cs.LGstat.MLarXiv:1511.06251v32015
Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks
Yuhang Li, Xin Dong, Wei Wang
cs.LGstat.MLarXiv:1909.13144v22019
Learning De-biased Representations with Biased Representations
Hyojin Bahng, Sanghyuk Chun, Sangdoo Yun +2
cs.CVcs.LGstat.MLarXiv:1910.02806v32019
Bandits with heavy tail
Sébastien Bubeck, Nicolò Cesa-Bianchi, Gábor Lugosi
stat.MLcs.LGarXiv:1209.1727v12012
Improving data-driven global weather prediction using deep convolutional neural networks on a cubed sphere
Jonathan A. Weyn, Dale R. Durran, Rich Caruana
physics.ao-phcs.LGstat.MLarXiv:2003.11927v12020
Federated Learning with Compression: Unified Analysis and Sharp Guarantees
Farzin Haddadpour, Mohammad Mahdi Kamani, Aryan Mokhtari +1
cs.LGcs.DCstat.MLarXiv:2007.01154v22020
Uncertainty Guided Multi-Scale Residual Learning-using a Cycle Spinning CNN for Single Image De-Raining
Rajeev Yasarla, Vishal M. Patel
cs.CVcs.LGeess.IVarXiv:1906.11129v12019
WoodScape: A multi-task, multi-camera fisheye dataset for autonomous driving
Senthil Yogamani, Ciaran Hughes, Jonathan Horgan +14
cs.CVcs.AIcs.LGarXiv:1905.01489v32019
GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations
Martin Engelcke, Adam R. Kosiorek, Oiwi Parker Jones +1
cs.LGcs.CVcs.NEarXiv:1907.13052v42019
User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient
Arnak S. Dalalyan, Avetik G. Karagulyan
math.STcs.LGmath.PRarXiv:1710.00095v42017
Character-based Neural Machine Translation
Marta R. Costa-Jussà, José A. R. Fonollosa
cs.CLcs.LGcs.NEarXiv:1603.00810v32016

Machine Learning (stat)

Compressed Sensing for Energy-Efficient Wireless Telemonitoring of Noninvasive Fetal ECG via Block Sparse Bayesian Learning

SPoC: Search-based Pseudocode to Code

The Vendi Score: A Diversity Evaluation Metric for Machine Learning

Transformer Dissection: A Unified Understanding of Transformer's Attention via the Lens of Kernel

Proving the Lottery Ticket Hypothesis: Pruning is All You Need

Embedding Logical Queries on Knowledge Graphs

The Power of Interpolation: Understanding the Effectiveness of SGD in Modern Over-parametrized Learning

Learning mixtures of spherical Gaussians: moment methods and spectral decompositions

Latent Space Oddity: on the Curvature of Deep Generative Models

Paris-Lille-3D: a large and high-quality ground truth urban point cloud dataset for automatic segmentation and classification

Fast low-rank estimation by projected gradient descent: General statistical and algorithmic guarantees

Simple random search provides a competitive approach to reinforcement learning

Deep Structural Causal Models for Tractable Counterfactual Inference

Dynamic Backdoor Attacks Against Machine Learning Models

Large-Scale Representation Learning on Graphs via Bootstrapping

Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation

Clustering Stability: An Overview

Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift

Distribution-Free, Risk-Controlling Prediction Sets

Learning Latent Block Structure in Weighted Networks

GANS for Sequences of Discrete Elements with the Gumbel-softmax Distribution

Truncated Back-propagation for Bilevel Optimization

Flexible statistical inference for mechanistic models of neural dynamics

Adaptive Cross-Modal Few-Shot Learning

Generalization and Exploration via Randomized Value Functions

Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO

Multi-Level Variational Autoencoder: Learning Disentangled Representations from Grouped Observations

Deep Exploration via Randomized Value Functions

Machine Learning and Deep Learning -- A review for Ecologists

Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design

Convergence Time Optimization for Federated Learning over Wireless Networks

Unsupervised speech representation learning using WaveNet autoencoders

Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification

Online Learning under Delayed Feedback

Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddings

Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks

Path-SGD: Path-Normalized Optimization in Deep Neural Networks

Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization

Surpassing Human-Level Face Verification Performance on LFW with GaussianFace

The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification

Machine Learning that Matters

Generating Steganographic Images via Adversarial Training

Provable Bounds for Learning Some Deep Representations

A deep matrix factorization method for learning attribute representations

Early stopping and non-parametric regression: An optimal data-dependent stopping rule

Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy

Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networks

SHINE: Signed Heterogeneous Information Network Embedding for Sentiment Link Prediction

Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks

Stochastic modified equations and adaptive stochastic gradient algorithms

Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks

Learning De-biased Representations with Biased Representations

Bandits with heavy tail

Improving data-driven global weather prediction using deep convolutional neural networks on a cubed sphere

Federated Learning with Compression: Unified Analysis and Sharp Guarantees

Uncertainty Guided Multi-Scale Residual Learning-using a Cycle Spinning CNN for Single Image De-Raining

WoodScape: A multi-task, multi-camera fisheye dataset for autonomous driving

GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations

User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient

Character-based Neural Machine Translation