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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8,821 to 8,880 of 9,674

When is a Convolutional Filter Easy To Learn?
Simon S. Du, Jason D. Lee, Yuandong Tian
cs.LGcs.AIcs.CVarXiv:1709.06129v22017
People on Drugs: Credibility of User Statements in Health Communities
Subhabrata Mukherjee, Gerhard Weikum, Cristian Danescu-Niculescu-Mizil
cs.AIcs.CLcs.IRarXiv:1705.02522v12017
Hybrid Spatio-Temporal Graph Convolutional Network: Improving Traffic Prediction with Navigation Data
Rui Dai, Shenkun Xu, Qian Gu +2
cs.LGstat.MLarXiv:2006.12715v12020
Profit Driven Decision Trees for Churn Prediction
Sebastiaan Höppner, Eugen Stripling, Bart Baesens +2
stat.MLcs.LGstat.AParXiv:1712.08101v12017
A XGBoost risk model via feature selection and Bayesian hyper-parameter optimization
Yan Wang, Xuelei Sherry Ni
stat.MLcs.LGarXiv:1901.08433v12019
Visual Sentiment Prediction with Deep Convolutional Neural Networks
Can Xu, Suleyman Cetintas, Kuang-Chih Lee +1
cs.CVcs.NEstat.MLarXiv:1411.5731v12014
A Multimodal Explainable Deep Learning Framework for Alzheimer's Disease Diagnosis using 3D Magnetic Resonance Imaging and Clinical Data
Yusuf Brima, Marcellin Atemkeng, Lakshmana Rao Namamula +1
cs.CVstat.MLarXiv:2609.12410v12026
Accelerated Primal-Dual Policy Optimization for Safe Reinforcement Learning
Qingkai Liang, Fanyu Que, Eytan Modiano
cs.AIcs.LGstat.MLarXiv:1802.06480v12018
On the Difference Between the Information Bottleneck and the Deep Information Bottleneck
Aleksander Wieczorek, Volker Roth
cs.LGcs.ITmath.ITarXiv:1912.13480v12019
Few-Shot Segmentation Propagation with Guided Networks
Kate Rakelly, Evan Shelhamer, Trevor Darrell +2
cs.CVcs.LGstat.MLarXiv:1806.07373v12018
Description and Discussion on DCASE 2022 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring Applying Domain Generalization Techniques
Kota Dohi, Keisuke Imoto, Noboru Harada +7
cs.SDcs.LGeess.ASarXiv:2206.05876v22022
The Roles of Supervised Machine Learning in Systems Neuroscience
Joshua I. Glaser, Ari S. Benjamin, Roozbeh Farhoodi +1
q-bio.NCcs.LGstat.MLarXiv:1805.08239v22018
dynnode2vec: Scalable Dynamic Network Embedding
Sedigheh Mahdavi, Shima Khoshraftar, Aijun An
cs.LGcs.SIstat.MLarXiv:1812.02356v22018
Domain Adaptive Transfer Learning for Fault Diagnosis
Qin Wang, Gabriel Michau, Olga Fink
stat.MLcs.LGstat.AParXiv:1905.06004v12019
Image Classification at Supercomputer Scale
Chris Ying, Sameer Kumar, Dehao Chen +2
cs.LGcs.DCstat.MLarXiv:1811.06992v22018
Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data Repository
Enyan Dai, Yiwei Sun, Suhang Wang
cs.SIcs.LGstat.MLarXiv:2002.00837v22020
Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts
Xu Liu, Juncheng Liu, Gerald Woo +7
cs.LGstat.MLarXiv:2410.10469v12024
Unmasking Trees for Tabular Data
Calvin McCarter
cs.LGstat.MLarXiv:2407.05593v52024
GAN Computers Generate Arts? A Survey on Visual Arts, Music, and Literary Text Generation using Generative Adversarial Network
Sakib Shahriar
cs.AIcs.CLcs.CVarXiv:2108.03857v22021
Universal Adversarial Attack on Attention and the Resulting Dataset DAmageNet
Sizhe Chen, Zhengbao He, Chengjin Sun +2
cs.LGstat.MLarXiv:2001.06325v32020
Federated Self-Supervised Learning of Multi-Sensor Representations for Embedded Intelligence
Aaqib Saeed, Flora D. Salim, Tanir Ozcelebi +1
cs.LGstat.MLarXiv:2007.13018v12020
The FLUXCOM ensemble of global land-atmosphere energy fluxes
Martin Jung, Sujan Koirala, Ulrich Weber +7
physics.ao-phcs.LGstat.MLarXiv:1812.04951v12018
Your Model Already Knows Don't Teach It, Learn to Ask It: Soft Prompting for Few-Shot Adaptation of Vision-Language Models
Gautam Rajendrakumar Gare, Siyi Li, Hewei Wang +5
cs.CVcs.AIcs.LGarXiv:2609.11310v12026
N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding
Ryan McConville, Raul Santos-Rodriguez, Robert J Piechocki +1
cs.LGstat.MLarXiv:1908.05968v62019
The data synergy effects of time-series deep learning models in hydrology
Kuai Fang, Daniel Kifer, Kathryn Lawson +2
cs.LGstat.MLarXiv:2101.01876v12021
Comparing Dynamics: Deep Neural Networks versus Glassy Systems
M. Baity-Jesi, L. Sagun, M. Geiger +6
stat.MLcond-mat.dis-nncs.LGarXiv:1803.06969v22018
CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity
Aditya Bhatt, Daniel Palenicek, Boris Belousov +4
cs.LGstat.MLarXiv:1902.05605v42019
Gradient Amplification: An efficient way to train deep neural networks
Sunitha Basodi, Chunyan Ji, Haiping Zhang +1
cs.LGcs.CVstat.MLarXiv:2006.10560v12020
Adversarial Sampling for Active Learning
Christoph Mayer, Radu Timofte
cs.LGcs.CVstat.MLarXiv:1808.06671v22018
Impact of Data Normalization on Deep Neural Network for Time Series Forecasting
Samit Bhanja, Abhishek Das
cs.LGstat.MLarXiv:1812.05519v22018
Adversarial Perturbations Against Real-Time Video Classification Systems
Shasha Li, Ajaya Neupane, Sujoy Paul +4
cs.LGcs.CRcs.CVarXiv:1807.00458v12018
Scatteract: Automated extraction of data from scatter plots
Mathieu Cliche, David Rosenberg, Dhruv Madeka +1
cs.CVcs.IRstat.MLarXiv:1704.06687v12017
Steering Diffusion Models to Rare Events with Sequential Monte Carlo
Aavash Subedi, Tim Reichelt, Christopher Williams +3
stat.MLcs.LGarXiv:2610.08652v12026
Combining time-series and textual data for taxi demand prediction in event areas: a deep learning approach
Filipe Rodrigues, Ioulia Markou, Francisco Pereira
stat.MLcs.CLcs.LGarXiv:1808.05535v12018
Few-Shot Bearing Fault Diagnosis Based on Model-Agnostic Meta-Learning
Shen Zhang, Fei Ye, Bingnan Wang +1
cs.LGstat.MLarXiv:2007.12851v42020
Deep Reinforcement Learning
Yuxi Li
cs.LGstat.MLarXiv:1810.06339v12018
Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity
Ran Liu, Mehdi Azabou, Max Dabagia +5
cs.LGstat.MLarXiv:2111.02338v12021
Fast Structured Decoding for Sequence Models
Zhiqing Sun, Zhuohan Li, Haoqing Wang +3
cs.LGcs.CLstat.MLarXiv:1910.11555v22019
Game Plan: What AI can do for Football, and What Football can do for AI
Karl Tuyls, Shayegan Omidshafiei, Paul Muller +33
cs.AIcs.GTcs.LGarXiv:2011.09192v12020
Self-Knowledge Distillation in Natural Language Processing
Sangchul Hahn, Heeyoul Choi
cs.CLcs.LGstat.MLarXiv:1908.01851v12019
Beyond Worst-Case Coreset Bounds for $k$-Clustering via Determinantal Sampling
Diptarka Chakraborty, Satyaki Mukherjee, Gaurav Vallabhdas Revankar +1
stat.MLcs.LGmath.PRarXiv:2609.06394v12026
Incremental Adversarial Domain Adaptation for Continually Changing Environments
Markus Wulfmeier, Alex Bewley, Ingmar Posner
stat.MLcs.CVcs.ROarXiv:1712.07436v22017
In Automation We Trust: Investigating the Role of Uncertainty in Active Learning Systems
Michael L. Iuzzolino, Tetsumichi Umada, Nisar R. Ahmed +1
cs.LGcs.HCstat.MLarXiv:2004.00762v12020
Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference
Max-Heinrich Laves, Sontje Ihler, Karl-Philipp Kortmann +1
cs.LGstat.MLarXiv:1909.13550v32019
Online Learning with Switching Costs and Other Adaptive Adversaries
Nicolo Cesa-Bianchi, Ofer Dekel, Ohad Shamir
cs.LGstat.MLarXiv:1302.4387v22013
Virtual-to-Real-World Transfer Learning for Robots on Wilderness Trails
Michael L. Iuzzolino, Michael E. Walker, Daniel Szafir
cs.LGcs.CVcs.ROarXiv:1901.05599v12019
Writer-independent Feature Learning for Offline Signature Verification using Deep Convolutional Neural Networks
Luiz G. Hafemann, Robert Sabourin, Luiz S. Oliveira
cs.CVstat.MLarXiv:1604.00974v12016
A review of possible effects of cognitive biases on the interpretation of rule-based machine learning models
Tomáš Kliegr, Štěpán Bahník, Johannes Fürnkranz
stat.MLcs.AIcs.LGarXiv:1804.02969v72018
dalex: Responsible Machine Learning with Interactive Explainability and Fairness in Python
Hubert Baniecki, Wojciech Kretowicz, Piotr Piatyszek +2
cs.LGcs.HCcs.SEarXiv:2012.14406v22020
Towards modular and programmable architecture search
Renato Negrinho, Darshan Patil, Nghia Le +3
cs.LGcs.AIstat.MLarXiv:1909.13404v12019
Fairness in representation: quantifying stereotyping as a representational harm
Mohsen Abbasi, Sorelle A. Friedler, Carlos Scheidegger +1
cs.LGstat.MLarXiv:1901.09565v12019
Amortized Data Borrowing with Exchangeability-Aware Neural Posterior Estimation
Chin-Hung Huang, JooChul Lee, Huan He
cs.LGstat.MLarXiv:2609.38902v12026
Recurrent Neural Networks for Time Series Forecasting
Gábor Petneházi
cs.LGstat.MLarXiv:1901.00069v12019
Consensus ranking under the exponential model
Marina Meila, Kapil Phadnis, Arthur Patterson +1
cs.LGcs.AIstat.MLarXiv:1206.5265v12012
Prediction of infectious disease epidemics via weighted density ensembles
Evan L. Ray, Nicholas G. Reich
stat.MLarXiv:1703.10936v12017
Performance Analysis and Comparison of Machine and Deep Learning Algorithms for IoT Data Classification
Meysam Vakili, Mohammad Ghamsari, Masoumeh Rezaei
cs.LGstat.MLarXiv:2001.09636v12020
Universal Adversarial Perturbations for Speech Recognition Systems
Paarth Neekhara, Shehzeen Hussain, Prakhar Pandey +3
cs.LGcs.SDeess.ASarXiv:1905.03828v22019
A Review of Vibration-Based Damage Detection in Civil Structures: From Traditional Methods to Machine Learning and Deep Learning Applications
Onur Avci, Osama Abdeljaber, Serkan Kiranyaz +3
eess.SPcs.LGstat.MLarXiv:2004.04373v12020
Bayesian Layers: A Module for Neural Network Uncertainty
Dustin Tran, Michael W. Dusenberry, Mark van der Wilk +1
cs.LGcs.PLstat.MLarXiv:1812.03973v32018
Character-Level Language Modeling with Deeper Self-Attention
Rami Al-Rfou, Dokook Choe, Noah Constant +2
cs.CLcs.AIcs.LGarXiv:1808.04444v22018

Machine Learning (stat)

When is a Convolutional Filter Easy To Learn?

People on Drugs: Credibility of User Statements in Health Communities

Hybrid Spatio-Temporal Graph Convolutional Network: Improving Traffic Prediction with Navigation Data

Profit Driven Decision Trees for Churn Prediction

A XGBoost risk model via feature selection and Bayesian hyper-parameter optimization

Visual Sentiment Prediction with Deep Convolutional Neural Networks

A Multimodal Explainable Deep Learning Framework for Alzheimer's Disease Diagnosis using 3D Magnetic Resonance Imaging and Clinical Data

Accelerated Primal-Dual Policy Optimization for Safe Reinforcement Learning

On the Difference Between the Information Bottleneck and the Deep Information Bottleneck

Few-Shot Segmentation Propagation with Guided Networks

Description and Discussion on DCASE 2022 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring Applying Domain Generalization Techniques

The Roles of Supervised Machine Learning in Systems Neuroscience

dynnode2vec: Scalable Dynamic Network Embedding

Domain Adaptive Transfer Learning for Fault Diagnosis

Image Classification at Supercomputer Scale

Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data Repository

Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts

Unmasking Trees for Tabular Data

GAN Computers Generate Arts? A Survey on Visual Arts, Music, and Literary Text Generation using Generative Adversarial Network

Universal Adversarial Attack on Attention and the Resulting Dataset DAmageNet

Federated Self-Supervised Learning of Multi-Sensor Representations for Embedded Intelligence

The FLUXCOM ensemble of global land-atmosphere energy fluxes

Your Model Already Knows Don't Teach It, Learn to Ask It: Soft Prompting for Few-Shot Adaptation of Vision-Language Models

N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding

The data synergy effects of time-series deep learning models in hydrology

Comparing Dynamics: Deep Neural Networks versus Glassy Systems

CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity

Gradient Amplification: An efficient way to train deep neural networks

Adversarial Sampling for Active Learning

Impact of Data Normalization on Deep Neural Network for Time Series Forecasting

Adversarial Perturbations Against Real-Time Video Classification Systems

Scatteract: Automated extraction of data from scatter plots

Steering Diffusion Models to Rare Events with Sequential Monte Carlo

Combining time-series and textual data for taxi demand prediction in event areas: a deep learning approach

Few-Shot Bearing Fault Diagnosis Based on Model-Agnostic Meta-Learning

Deep Reinforcement Learning

Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity

Fast Structured Decoding for Sequence Models

Game Plan: What AI can do for Football, and What Football can do for AI

Self-Knowledge Distillation in Natural Language Processing

Beyond Worst-Case Coreset Bounds for $k$-Clustering via Determinantal Sampling

Incremental Adversarial Domain Adaptation for Continually Changing Environments

In Automation We Trust: Investigating the Role of Uncertainty in Active Learning Systems

Well-calibrated Model Uncertainty with Temperature Scaling for Dropout Variational Inference

Online Learning with Switching Costs and Other Adaptive Adversaries

Virtual-to-Real-World Transfer Learning for Robots on Wilderness Trails

Writer-independent Feature Learning for Offline Signature Verification using Deep Convolutional Neural Networks

A review of possible effects of cognitive biases on the interpretation of rule-based machine learning models

dalex: Responsible Machine Learning with Interactive Explainability and Fairness in Python

Towards modular and programmable architecture search

Fairness in representation: quantifying stereotyping as a representational harm

Amortized Data Borrowing with Exchangeability-Aware Neural Posterior Estimation

Recurrent Neural Networks for Time Series Forecasting

Consensus ranking under the exponential model

Prediction of infectious disease epidemics via weighted density ensembles

Performance Analysis and Comparison of Machine and Deep Learning Algorithms for IoT Data Classification

Universal Adversarial Perturbations for Speech Recognition Systems

A Review of Vibration-Based Damage Detection in Civil Structures: From Traditional Methods to Machine Learning and Deep Learning Applications

Bayesian Layers: A Module for Neural Network Uncertainty

Character-Level Language Modeling with Deeper Self-Attention