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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4,141 to 4,200 of 6,790

Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models
Juan Miguel Lopez Alcaraz, Nils Strodthoff
cs.LGstat.MLarXiv:2208.09399v32022
PixelSNAIL: An Improved Autoregressive Generative Model
Xi Chen, Nikhil Mishra, Mostafa Rohaninejad +1
cs.LGstat.MLarXiv:1712.09763v12017
Consistency Regularization for Generative Adversarial Networks
Han Zhang, Zizhao Zhang, Augustus Odena +1
cs.LGcs.CVstat.MLarXiv:1910.12027v22019
Adversarial Attacks on Deep-Learning Based Radio Signal Classification
Meysam Sadeghi, Erik G. Larsson
cs.ITcs.CRcs.LGarXiv:1808.07713v12018
TRAK: Attributing Model Behavior at Scale
Sung Min Park, Kristian Georgiev, Andrew Ilyas +2
stat.MLcs.LGarXiv:2303.14186v22023
A Survey of Reinforcement Learning Informed by Natural Language
Jelena Luketina, Nantas Nardelli, Gregory Farquhar +5
cs.LGcs.AIcs.CLarXiv:1906.03926v12019
Membership Leakage in Label-Only Exposures
Zheng Li, Yang Zhang
cs.LGcs.CRstat.MLarXiv:2007.15528v32020
Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound
Lin F. Yang, Mengdi Wang
cs.LGstat.MLarXiv:1905.10389v22019
Adaptively Sparse Transformers
Gonçalo M. Correia, Vlad Niculae, André F. T. Martins
cs.CLstat.MLarXiv:1909.00015v22019
Data Driven Governing Equations Approximation Using Deep Neural Networks
Tong Qin, Kailiang Wu, Dongbin Xiu
math.NAcs.LGcs.NEarXiv:1811.05537v12018
PassGAN: A Deep Learning Approach for Password Guessing
Briland Hitaj, Paolo Gasti, Giuseppe Ateniese +1
cs.CRcs.LGstat.MLarXiv:1709.00440v32017
Universal Adversarial Perturbations Against Semantic Image Segmentation
Jan Hendrik Metzen, Mummadi Chaithanya Kumar, Thomas Brox +1
stat.MLcs.AIcs.CVarXiv:1704.05712v32017
Is Homophily a Necessity for Graph Neural Networks?
Yao Ma, Xiaorui Liu, Neil Shah +1
cs.LGstat.MLarXiv:2106.06134v42021
Prediction-Powered Inference
Anastasios N. Angelopoulos, Stephen Bates, Clara Fannjiang +2
stat.MLcs.AIcs.LGarXiv:2301.09633v42023
Deep Network Approximation for Smooth Functions
Jianfeng Lu, Zuowei Shen, Haizhao Yang +1
cs.LGmath.NAstat.MLarXiv:2001.03040v82020
Communication Compression for Decentralized Training
Hanlin Tang, Shaoduo Gan, Ce Zhang +2
cs.LGcs.DCeess.SYarXiv:1803.06443v52018
Robust Subspace Learning: Robust PCA, Robust Subspace Tracking, and Robust Subspace Recovery
Namrata Vaswani, Thierry Bouwmans, Sajid Javed +1
cs.ITcs.CVstat.MEarXiv:1711.09492v42017
LSQ+: Improving low-bit quantization through learnable offsets and better initialization
Yash Bhalgat, Jinwon Lee, Markus Nagel +2
cs.CVcs.LGstat.MLarXiv:2004.09576v12020
Federated Learning for Keyword Spotting
David Leroy, Alice Coucke, Thibaut Lavril +2
eess.AScs.CLcs.LGarXiv:1810.05512v42018
Comparing BERT against traditional machine learning text classification
Santiago González-Carvajal, Eduardo C. Garrido-Merchán
cs.CLcs.LGstat.MLarXiv:2005.13012v22020
Coresets via Bilevel Optimization for Continual Learning and Streaming
Zalán Borsos, Mojmír Mutný, Andreas Krause
cs.LGstat.MLarXiv:2006.03875v22020
Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel Derivation
Greg Yang
cs.NEcond-mat.dis-nncs.LGarXiv:1902.04760v32019
Inference Suboptimality in Variational Autoencoders
Chris Cremer, Xuechen Li, David Duvenaud
cs.LGstat.MLarXiv:1801.03558v32018
Skew-Fit: State-Covering Self-Supervised Reinforcement Learning
Vitchyr H. Pong, Murtaza Dalal, Steven Lin +3
cs.LGcs.AIcs.ROarXiv:1903.03698v42019
A vector-contraction inequality for Rademacher complexities
Andreas Maurer
cs.LGstat.MLarXiv:1605.00251v12016
Hierarchical modeling of molecular energies using a deep neural network
Nicholas Lubbers, Justin S. Smith, Kipton Barros
stat.MLphysics.chem-pharXiv:1710.00017v12017
Multimodal Sentiment Analysis with Word-Level Fusion and Reinforcement Learning
Minghai Chen, Sen Wang, Paul Pu Liang +3
cs.LGcs.AIcs.CLarXiv:1802.00924v12018
Deep Rewiring: Training very sparse deep networks
Guillaume Bellec, David Kappel, Wolfgang Maass +1
cs.NEcs.AIcs.DCarXiv:1711.05136v52017
Representer Point Selection for Explaining Deep Neural Networks
Chih-Kuan Yeh, Joon Sik Kim, Ian E. H. Yen +1
cs.LGstat.MLarXiv:1811.09720v12018
SteganoGAN: High Capacity Image Steganography with GANs
Kevin Alex Zhang, Alfredo Cuesta-Infante, Lei Xu +1
cs.CVcs.LGcs.MMarXiv:1901.03892v22019
How (not) to Train your Generative Model: Scheduled Sampling, Likelihood, Adversary?
Ferenc Huszár
stat.MLcs.AIcs.ITarXiv:1511.05101v12015
Grounded Language Learning in a Simulated 3D World
Karl Moritz Hermann, Felix Hill, Simon Green +11
cs.CLcs.LGstat.MLarXiv:1706.06551v22017
Evaluating and Aggregating Feature-based Model Explanations
Umang Bhatt, Adrian Weller, José M. F. Moura
cs.LGcs.AIcs.CYarXiv:2005.00631v12020
Input complexity and out-of-distribution detection with likelihood-based generative models
Joan Serrà, David Álvarez, Vicenç Gómez +3
cs.LGstat.MLarXiv:1909.11480v32019
Salvaging Federated Learning by Local Adaptation
Tao Yu, Eugene Bagdasaryan, Vitaly Shmatikov
cs.LGcs.AIcs.DCarXiv:2002.04758v32020
Optimal Clustering Framework for Hyperspectral Band Selection
Qi Wang, Fahong Zhang, Xuelong Li
eess.IVcs.LGstat.MLarXiv:1904.13036v12019
CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training
Murat Kocaoglu, Christopher Snyder, Alexandros G. Dimakis +1
cs.LGcs.AIcs.ITarXiv:1709.02023v22017
Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring
Sungjin Ahn, Anoop Korattikara, Max Welling
cs.LGstat.COstat.MLarXiv:1206.6380v12012
Stochastic Controlled Averaging for Federated Learning with Communication Compression
Xinmeng Huang, Ping Li, Xiaoyun Li
math.OCcs.DCcs.LGarXiv:2308.08165v22023
Unsupervised and Semi-supervised Anomaly Detection with LSTM Neural Networks
Tolga Ergen, Ali Hassan Mirza, Suleyman Serdar Kozat
eess.SPcs.LGstat.MLarXiv:1710.09207v12017
Toward Robustness against Label Noise in Training Deep Discriminative Neural Networks
Arash Vahdat
cs.LGstat.MLarXiv:1706.00038v22017
Deep Learning for Time Series Forecasting: The Electric Load Case
Alberto Gasparin, Slobodan Lukovic, Cesare Alippi
cs.LGstat.MLarXiv:1907.09207v12019
Maximizing acquisition functions for Bayesian optimization
James T. Wilson, Frank Hutter, Marc Peter Deisenroth
stat.MLcs.LGarXiv:1805.10196v22018
Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs
Alon Brutzkus, Amir Globerson
cs.LGmath.OCstat.MLarXiv:1702.07966v12017
TAP-Vid: A Benchmark for Tracking Any Point in a Video
Carl Doersch, Ankush Gupta, Larisa Markeeva +6
cs.CVstat.MLarXiv:2211.03726v22022
On the Inductive Bias of Neural Tangent Kernels
Alberto Bietti, Julien Mairal
stat.MLcs.LGarXiv:1905.12173v22019
GMNN: Graph Markov Neural Networks
Meng Qu, Yoshua Bengio, Jian Tang
cs.LGcs.SIstat.MLarXiv:1905.06214v32019
A consistent adjacency spectral embedding for stochastic blockmodel graphs
Daniel L. Sussman, Minh Tang, Donniell E. Fishkind +1
stat.MLarXiv:1108.2228v32011
A Closer Look at Deep Learning Heuristics: Learning rate restarts, Warmup and Distillation
Akhilesh Gotmare, Nitish Shirish Keskar, Caiming Xiong +1
cs.LGstat.MLarXiv:1810.13243v12018
Voice Conversion from Non-parallel Corpora Using Variational Auto-encoder
Chin-Cheng Hsu, Hsin-Te Hwang, Yi-Chiao Wu +2
stat.MLcs.LGcs.SDarXiv:1610.04019v12016
Unsupervised Generative Modeling Using Matrix Product States
Zhao-Yu Han, Jun Wang, Heng Fan +2
cond-mat.stat-mechcs.LGquant-pharXiv:1709.01662v32017
Sever: A Robust Meta-Algorithm for Stochastic Optimization
Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane +3
cs.LGcs.AIcs.DSarXiv:1803.02815v22018
Towards Understanding the Spectral Bias of Deep Learning
Yuan Cao, Zhiying Fang, Yue Wu +2
cs.LGstat.MLarXiv:1912.01198v32019
Deep learning from crowds
Filipe Rodrigues, Francisco Pereira
stat.MLcs.CVcs.HCarXiv:1709.01779v22017
CRED: A Deep Residual Network of Convolutional and Recurrent Units for Earthquake Signal Detection
S. Mostafa Mousavi, Weiqiang Zhu, Yixiao Sheng +1
cs.LGstat.MLarXiv:1810.01965v12018
Differentiable Learning of Quantum Circuit Born Machine
Jin-Guo Liu, Lei Wang
quant-phcs.LGstat.MLarXiv:1804.04168v12018
Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network
Risi Kondor, Zhen Lin, Shubhendu Trivedi
stat.MLcs.LGarXiv:1806.09231v22018
The Primacy Bias in Deep Reinforcement Learning
Evgenii Nikishin, Max Schwarzer, Pierluca D'Oro +2
cs.LGcs.AIstat.MLarXiv:2205.07802v12022
A Bayesian Approach to Network Modularity
Jake M. Hofman, Chris H. Wiggins
physics.data-ancond-mat.stat-mechstat.MLarXiv:0709.3512v32007
Weak SINDy For Partial Differential Equations
Daniel A. Messenger, David M. Bortz
math.NAcs.LGstat.MLarXiv:2007.02848v32020

Machine Learning (stat)

Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models

PixelSNAIL: An Improved Autoregressive Generative Model

Consistency Regularization for Generative Adversarial Networks

Adversarial Attacks on Deep-Learning Based Radio Signal Classification

TRAK: Attributing Model Behavior at Scale

A Survey of Reinforcement Learning Informed by Natural Language

Membership Leakage in Label-Only Exposures

Reinforcement Learning in Feature Space: Matrix Bandit, Kernels, and Regret Bound

Adaptively Sparse Transformers

Data Driven Governing Equations Approximation Using Deep Neural Networks

PassGAN: A Deep Learning Approach for Password Guessing

Universal Adversarial Perturbations Against Semantic Image Segmentation

Is Homophily a Necessity for Graph Neural Networks?

Prediction-Powered Inference

Deep Network Approximation for Smooth Functions

Communication Compression for Decentralized Training

Robust Subspace Learning: Robust PCA, Robust Subspace Tracking, and Robust Subspace Recovery

LSQ+: Improving low-bit quantization through learnable offsets and better initialization

Federated Learning for Keyword Spotting

Comparing BERT against traditional machine learning text classification

Coresets via Bilevel Optimization for Continual Learning and Streaming

Scaling Limits of Wide Neural Networks with Weight Sharing: Gaussian Process Behavior, Gradient Independence, and Neural Tangent Kernel Derivation

Inference Suboptimality in Variational Autoencoders

Skew-Fit: State-Covering Self-Supervised Reinforcement Learning

A vector-contraction inequality for Rademacher complexities

Hierarchical modeling of molecular energies using a deep neural network

Multimodal Sentiment Analysis with Word-Level Fusion and Reinforcement Learning

Deep Rewiring: Training very sparse deep networks

Representer Point Selection for Explaining Deep Neural Networks

SteganoGAN: High Capacity Image Steganography with GANs

How (not) to Train your Generative Model: Scheduled Sampling, Likelihood, Adversary?

Grounded Language Learning in a Simulated 3D World

Evaluating and Aggregating Feature-based Model Explanations

Input complexity and out-of-distribution detection with likelihood-based generative models

Salvaging Federated Learning by Local Adaptation

Optimal Clustering Framework for Hyperspectral Band Selection

CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training

Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring

Stochastic Controlled Averaging for Federated Learning with Communication Compression

Unsupervised and Semi-supervised Anomaly Detection with LSTM Neural Networks

Toward Robustness against Label Noise in Training Deep Discriminative Neural Networks

Deep Learning for Time Series Forecasting: The Electric Load Case

Maximizing acquisition functions for Bayesian optimization

Globally Optimal Gradient Descent for a ConvNet with Gaussian Inputs

TAP-Vid: A Benchmark for Tracking Any Point in a Video

On the Inductive Bias of Neural Tangent Kernels

GMNN: Graph Markov Neural Networks

A consistent adjacency spectral embedding for stochastic blockmodel graphs

A Closer Look at Deep Learning Heuristics: Learning rate restarts, Warmup and Distillation

Voice Conversion from Non-parallel Corpora Using Variational Auto-encoder

Unsupervised Generative Modeling Using Matrix Product States

Sever: A Robust Meta-Algorithm for Stochastic Optimization

Towards Understanding the Spectral Bias of Deep Learning

Deep learning from crowds

CRED: A Deep Residual Network of Convolutional and Recurrent Units for Earthquake Signal Detection

Differentiable Learning of Quantum Circuit Born Machine

Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network

The Primacy Bias in Deep Reinforcement Learning

A Bayesian Approach to Network Modularity

Weak SINDy For Partial Differential Equations