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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5,101 to 5,160 of 6,785

Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing
Hao Fu, Chunyuan Li, Xiaodong Liu +3
cs.LGcs.AIcs.CLarXiv:1903.10145v32019
Deep Structured Energy Based Models for Anomaly Detection
Shuangfei Zhai, Yu Cheng, Weining Lu +1
cs.LGstat.MLarXiv:1605.07717v22016
Auxiliary Deep Generative Models
Lars Maaløe, Casper Kaae Sønderby, Søren Kaae Sønderby +1
stat.MLcs.AIcs.LGarXiv:1602.05473v42016
A Practical Algorithm for Topic Modeling with Provable Guarantees
Sanjeev Arora, Rong Ge, Yoni Halpern +5
cs.LGcs.DSstat.MLarXiv:1212.4777v12012
Distributional Smoothing with Virtual Adversarial Training
Takeru Miyato, Shin-ichi Maeda, Masanori Koyama +2
stat.MLcs.LGarXiv:1507.00677v92015
Domain Adaptive Neural Networks for Object Recognition
Muhammad Ghifary, W. Bastiaan Kleijn, Mengjie Zhang
cs.CVcs.AIcs.LGarXiv:1409.6041v12014
Stacked Generative Adversarial Networks
Xun Huang, Yixuan Li, Omid Poursaeed +2
cs.CVcs.LGcs.NEarXiv:1612.04357v42016
Data Augmentation by Pairing Samples for Images Classification
Hiroshi Inoue
cs.LGcs.CVstat.MLarXiv:1801.02929v22018
Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks
Ji Young Lee, Franck Dernoncourt
cs.CLcs.AIcs.LGarXiv:1603.03827v12016
The Benefit of Group Sparsity
Junzhou Huang, Tong Zhang
stat.MLmath.STarXiv:0901.2962v22009
PRNet: Self-Supervised Learning for Partial-to-Partial Registration
Yue Wang, Justin M. Solomon
cs.LGstat.MLarXiv:1910.12240v22019
GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Media
Yi-Ju Lu, Cheng-Te Li
cs.CLcs.LGstat.MLarXiv:2004.11648v12020
Normalization Techniques in Training DNNs: Methodology, Analysis and Application
Lei Huang, Jie Qin, Yi Zhou +3
cs.LGcs.CVstat.MLarXiv:2009.12836v12020
LoRA+: Efficient Low Rank Adaptation of Large Models
Soufiane Hayou, Nikhil Ghosh, Bin Yu
cs.LGcs.AIcs.CLarXiv:2402.12354v22024
Multi-scale Dynamic Graph Convolutional Network for Hyperspectral Image Classification
Sheng Wan, Chen Gong, Ping Zhong +3
eess.IVcs.LGstat.MLarXiv:1905.06133v12019
A Deep Learning Approach to Structured Signal Recovery
Ali Mousavi, Ankit B. Patel, Richard G. Baraniuk
cs.LGstat.MLarXiv:1508.04065v12015
Further Optimal Regret Bounds for Thompson Sampling
Shipra Agrawal, Navin Goyal
cs.LGcs.DSstat.MLarXiv:1209.3353v12012
A Comprehensive Review of Deep Learning Applications in Hydrology and Water Resources
Muhammed Sit, Bekir Z. Demiray, Zhongrun Xiang +3
physics.geo-phcs.LGstat.MLarXiv:2007.12269v12020
Robust Compressed Sensing MRI with Deep Generative Priors
Ajil Jalal, Marius Arvinte, Giannis Daras +3
cs.LGcs.CVcs.ITarXiv:2108.01368v22021
Do CIFAR-10 Classifiers Generalize to CIFAR-10?
Benjamin Recht, Rebecca Roelofs, Ludwig Schmidt +1
cs.LGstat.MLarXiv:1806.00451v12018
Low-bit Quantization of Neural Networks for Efficient Inference
Yoni Choukroun, Eli Kravchik, Fan Yang +1
cs.LGcs.CVstat.MLarXiv:1902.06822v22019
Fastfood: Approximate Kernel Expansions in Loglinear Time
Quoc Viet Le, Tamas Sarlos, Alexander Johannes Smola
cs.LGstat.MLarXiv:1408.3060v12014
Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space
Arvind Neelakantan, Jeevan Shankar, Alexandre Passos +1
cs.CLstat.MLarXiv:1504.06654v12015
Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization
Shai Shalev-Shwartz, Tong Zhang
stat.MLcs.LGmath.NAarXiv:1309.2375v22013
Should we really use post-hoc tests based on mean-ranks?
Alessio Benavoli, Giorgio Corani, Francesca Mangili
cs.LGmath.STphysics.data-anarXiv:1505.02288v12015
Differentiable MPC for End-to-end Planning and Control
Brandon Amos, Ivan Dario Jimenez Rodriguez, Jacob Sacks +2
cs.LGcs.AImath.OCarXiv:1810.13400v32018
Bolasso: model consistent Lasso estimation through the bootstrap
Francis Bach
cs.LGmath.STstat.MLarXiv:0804.1302v12008
Pose-Normalized Image Generation for Person Re-identification
Xuelin Qian, Yanwei Fu, Tao Xiang +5
cs.CVcs.AIcs.MMarXiv:1712.02225v62017
Transfer Learning for Brain-Computer Interfaces: A Euclidean Space Data Alignment Approach
He He, Dongrui Wu
cs.LGcs.HCq-bio.NCarXiv:1808.05464v22018
Neural Photo Editing with Introspective Adversarial Networks
Andrew Brock, Theodore Lim, J. M. Ritchie +1
cs.LGcs.CVcs.NEarXiv:1609.07093v32016
Doubly Stochastic Variational Inference for Deep Gaussian Processes
Hugh Salimbeni, Marc Deisenroth
stat.MLarXiv:1705.08933v22017
A Convex Formulation for Learning Task Relationships in Multi-Task Learning
Yu Zhang, Dit-Yan Yeung
cs.LGcs.AIstat.MLarXiv:1203.3536v12012
Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup
Jang-Hyun Kim, Wonho Choo, Hyun Oh Song
cs.LGcs.AIcs.CVarXiv:2009.06962v22020
Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging
Nils Reimers, Iryna Gurevych
cs.CLstat.MLarXiv:1707.09861v12017
Dimensionality-Driven Learning with Noisy Labels
Xingjun Ma, Yisen Wang, Michael E. Houle +5
cs.CVcs.LGstat.MLarXiv:1806.02612v22018
Tactics of Adversarial Attack on Deep Reinforcement Learning Agents
Yen-Chen Lin, Zhang-Wei Hong, Yuan-Hong Liao +3
cs.LGcs.CRstat.MLarXiv:1703.06748v42017
Dynamic Graph Convolutional Networks
Franco Manessi, Alessandro Rozza, Mario Manzo
cs.LGstat.MLarXiv:1704.06199v12017
Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting
Rajat Sen, Hsiang-Fu Yu, Inderjit Dhillon
stat.MLcs.LGarXiv:1905.03806v22019
On Human Predictions with Explanations and Predictions of Machine Learning Models: A Case Study on Deception Detection
Vivian Lai, Chenhao Tan
cs.AIcs.CLcs.CYarXiv:1811.07901v42018
Algorithmic Recourse: from Counterfactual Explanations to Interventions
Amir-Hossein Karimi, Bernhard Schölkopf, Isabel Valera
cs.LGcs.AIstat.MLarXiv:2002.06278v42020
Verified Uncertainty Calibration
Ananya Kumar, Percy Liang, Tengyu Ma
cs.LGstat.MLarXiv:1909.10155v22019
Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition
Naoya Takeishi, Yoshinobu Kawahara, Takehisa Yairi
cs.LGmath.DSstat.MLarXiv:1710.04340v22017
Time-to-Event Prediction with Neural Networks and Cox Regression
Håvard Kvamme, Ørnulf Borgan, Ida Scheel
stat.MLcs.LGarXiv:1907.00825v22019
Deep Anomaly Detection with Deviation Networks
Guansong Pang, Chunhua Shen, Anton van den Hengel
cs.LGstat.MLarXiv:1911.08623v12019
Hyperspherical Variational Auto-Encoders
Tim R. Davidson, Luca Falorsi, Nicola De Cao +2
stat.MLcs.LGarXiv:1804.00891v32018
A Semi-supervised Graph Attentive Network for Financial Fraud Detection
Daixin Wang, Jianbin Lin, Peng Cui +7
cs.SIcs.CRcs.LGarXiv:2003.01171v12020
An Investigation into Neural Net Optimization via Hessian Eigenvalue Density
Behrooz Ghorbani, Shankar Krishnan, Ying Xiao
cs.LGstat.MLarXiv:1901.10159v12019
Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning
Zeyuan Allen-Zhu, Yuanzhi Li
cs.LGcs.NEmath.OCarXiv:2012.09816v32020
Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning
Cong Zhang, Wen Song, Zhiguang Cao +3
cs.LGcs.AIstat.MLarXiv:2010.12367v12020
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques
Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen +17
cs.AIcs.CVcs.HCarXiv:1909.03012v22019
Gauge Equivariant Convolutional Networks and the Icosahedral CNN
Taco S. Cohen, Maurice Weiler, Berkay Kicanaoglu +1
cs.LGcs.CVcs.NEarXiv:1902.04615v32019
What Are Bayesian Neural Network Posteriors Really Like?
Pavel Izmailov, Sharad Vikram, Matthew D. Hoffman +1
cs.LGstat.MLarXiv:2104.14421v12021
Secure and Robust Machine Learning for Healthcare: A Survey
Adnan Qayyum, Junaid Qadir, Muhammad Bilal +1
cs.LGeess.IVstat.MLarXiv:2001.08103v12020
Inductive Biases for Deep Learning of Higher-Level Cognition
Anirudh Goyal, Yoshua Bengio
cs.LGcs.AIstat.MLarXiv:2011.15091v42020
Visualizing and Measuring the Geometry of BERT
Andy Coenen, Emily Reif, Ann Yuan +4
cs.LGcs.CLstat.MLarXiv:1906.02715v22019
Forward and Reverse Gradient-Based Hyperparameter Optimization
Luca Franceschi, Michele Donini, Paolo Frasconi +1
stat.MLarXiv:1703.01785v32017
Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction
Pi Qi, Xiaoqiang Zhu, Guorui Zhou +5
cs.IRstat.MLarXiv:2006.05639v22020
Generative Adversarial Networks (GANs Survey): Challenges, Solutions, and Future Directions
Divya Saxena, Jiannong Cao
cs.LGeess.IVstat.MLarXiv:2005.00065v42020
Machine Learning Advances for Time Series Forecasting
Ricardo P. Masini, Marcelo C. Medeiros, Eduardo F. Mendes
econ.EMcs.LGstat.AParXiv:2012.12802v32020
Stabilizing Training of Generative Adversarial Networks through Regularization
Kevin Roth, Aurelien Lucchi, Sebastian Nowozin +1
cs.LGstat.MLarXiv:1705.09367v22017

Machine Learning (stat)

Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing

Deep Structured Energy Based Models for Anomaly Detection

Auxiliary Deep Generative Models

A Practical Algorithm for Topic Modeling with Provable Guarantees

Distributional Smoothing with Virtual Adversarial Training

Domain Adaptive Neural Networks for Object Recognition

Stacked Generative Adversarial Networks

Data Augmentation by Pairing Samples for Images Classification

Sequential Short-Text Classification with Recurrent and Convolutional Neural Networks

The Benefit of Group Sparsity

PRNet: Self-Supervised Learning for Partial-to-Partial Registration

GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Media

Normalization Techniques in Training DNNs: Methodology, Analysis and Application

LoRA+: Efficient Low Rank Adaptation of Large Models

Multi-scale Dynamic Graph Convolutional Network for Hyperspectral Image Classification

A Deep Learning Approach to Structured Signal Recovery

Further Optimal Regret Bounds for Thompson Sampling

A Comprehensive Review of Deep Learning Applications in Hydrology and Water Resources

Robust Compressed Sensing MRI with Deep Generative Priors

Do CIFAR-10 Classifiers Generalize to CIFAR-10?

Low-bit Quantization of Neural Networks for Efficient Inference

Fastfood: Approximate Kernel Expansions in Loglinear Time

Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space

Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization

Should we really use post-hoc tests based on mean-ranks?

Differentiable MPC for End-to-end Planning and Control

Bolasso: model consistent Lasso estimation through the bootstrap

Pose-Normalized Image Generation for Person Re-identification

Transfer Learning for Brain-Computer Interfaces: A Euclidean Space Data Alignment Approach

Neural Photo Editing with Introspective Adversarial Networks

Doubly Stochastic Variational Inference for Deep Gaussian Processes

A Convex Formulation for Learning Task Relationships in Multi-Task Learning

Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup

Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging

Dimensionality-Driven Learning with Noisy Labels

Tactics of Adversarial Attack on Deep Reinforcement Learning Agents

Dynamic Graph Convolutional Networks

Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting

On Human Predictions with Explanations and Predictions of Machine Learning Models: A Case Study on Deception Detection

Algorithmic Recourse: from Counterfactual Explanations to Interventions

Verified Uncertainty Calibration

Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition

Time-to-Event Prediction with Neural Networks and Cox Regression

Deep Anomaly Detection with Deviation Networks

Hyperspherical Variational Auto-Encoders

A Semi-supervised Graph Attentive Network for Financial Fraud Detection

An Investigation into Neural Net Optimization via Hessian Eigenvalue Density

Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning

Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning

One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques

Gauge Equivariant Convolutional Networks and the Icosahedral CNN

What Are Bayesian Neural Network Posteriors Really Like?

Secure and Robust Machine Learning for Healthcare: A Survey

Inductive Biases for Deep Learning of Higher-Level Cognition

Visualizing and Measuring the Geometry of BERT

Forward and Reverse Gradient-Based Hyperparameter Optimization

Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction

Generative Adversarial Networks (GANs Survey): Challenges, Solutions, and Future Directions

Machine Learning Advances for Time Series Forecasting

Stabilizing Training of Generative Adversarial Networks through Regularization