Statistics - Machine Learning

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Machine Learning Simplifying Contextual Bandits for Operators

A user-friendly tool for understanding contextual bandit systems.

Andrew Maher, Matia Gobbo, Lancelot Lachartre

2025-05-31T22:50:52+00:00 ― 6 min read

Machine Learning Advancing Data Modeling with DrMMD Technique

A look into DrMMD and its application for better data distribution modeling.

Zonghao Chen, Aratrika Mustafi, Pierre Glaser

2025-05-31T22:00:48+00:00 ― 5 min read

Machine Learning Advancements in Time-Series Forecasting Techniques

Learn how adaptive conformal inference improves multi-step predictions in forecasting.

Johan Hallberg Szabadváry

2025-05-31T21:10:44+00:00 ― 5 min read

Machine Learning Learning Dynamics from Partial Observations in Complex Systems

Research on estimating dynamics from noisy and bilinear measurements.

Yahya Sattar, Yassir Jedra, Sarah Dean

2025-05-31T11:02:58+00:00 ― 6 min read

Machine Learning Estimating Causal Effects: Weights and Representations

A deep dive into causal effects estimation through weights and learned representations.

Oscar Clivio, Avi Feller, Chris Holmes

2025-05-31T09:40:20+00:00 ― 9 min read

Machine Learning Evaluating Generative Models: A Non-Parametric Approach

A new method for assessing generative models using non-parametric tests.

Samuele Grossi, Marco Letizia, Riccardo Torre

2025-05-31T08:17:42+00:00 ― 8 min read

Machine Learning Collaborative Learning Framework: A New Approach

A method for agents to improve estimates through teamwork and feedback.

Getachew K Befekadu

2025-05-31T06:55:04+00:00 ― 5 min read

Applications A New Approach to Economic Changes in LMICs

Innovative methods to analyze economic shifts despite data challenges.

Ronald Katende

2025-05-31T00:01:54+00:00 ― 7 min read

Optimization and Control The Extragradient Method: A Key to Complex Problem Solving

Discover the extragradient method and its role in solving optimization problems.

Quoc Tran-Dinh, Nghia Nguyen-Trung

2025-05-30T22:39:16+00:00 ― 5 min read

Machine Learning Improving Conditional Coverage in Predictive Models

New method enhances prediction reliability for diverse groups in high-stakes scenarios.

Ruijiang Gao, Mingzhang Yin, James McInerney

2025-05-30T19:54:00+00:00 ― 5 min read

Methodology Predicting Rice Yields in Peru Using Modern Techniques

This study examines data-driven methods to forecast rice production in Peru.

Rita Rocio Guzman-Lopez, Luis Huamanchumo, Kevin Fernandez

2025-05-30T17:08:44+00:00 ― 5 min read

Machine Learning Conditional Generative Models: Shaping Data with Precision

Explore how conditional generative models create tailored data for various applications.

Hanwen Huang

2025-05-30T15:46:06+00:00 ― 5 min read

Computer Vision and Pattern Recognition Improving Depth Estimation with PEFT Methods

Exploring parameter-efficient fine-tuning for depth estimation accuracy and uncertainty.

Richard D. Paul, Alessio Quercia, Vincent Fortuin

2025-05-30T14:23:28+00:00 ― 4 min read

Machine Learning Enhancing Physics-Informed Neural Networks with DCGD

A new method to improve training in physics-informed neural networks.

Youngsik Hwang, Dong-Young Lim

2025-05-30T06:07:40+00:00 ― 6 min read

Machine Learning Efficient Parameter Estimation with Embed and Emulate

A new approach for faster parameter estimation in complex systems using simulations.

Ruoxi Jiang, Peter Y. Lu, Rebecca Willett

2025-05-30T04:45:02+00:00 ― 6 min read

Machine Learning Addressing Confirmation Bias in Semi-Supervised Learning

A framework to balance pseudo-label learning in machine learning.

Yu Wang, Yuxuan Yin, Peng Li

2025-05-30T03:22:24+00:00 ― 5 min read

Machine Learning Improving Forecast Stability in Supply Chains

A method to enhance stability in forecasts while maintaining accuracy in business planning.

Daan Caljon, Jeff Vercauteren, Simon De Vos

2025-05-30T01:59:46+00:00 ― 6 min read

Machine Learning Learning from Unnormalized Distributions: Overview and Techniques

This article discusses methods for learning unnormalized distributions using noise-contrastive estimation.

J. Jon Ryu, Abhin Shah, Gregory W. Wornell

2025-05-30T00:37:08+00:00 ― 5 min read

Machine Learning New Framework to Improve Machine Learning Adaptability

A graph-based approach to enhance machine learning in dynamic environments.

Han Wang, Yixuan Li

2025-05-29T23:14:30+00:00 ― 6 min read

Machine Learning Advancements in Event Prediction Frameworks

A new model improves efficiency in predicting events over time.

Aristeidis Panos

2025-05-29T21:51:52+00:00 ― 8 min read

Quantitative Methods Understanding Shapley Values in DNA Profiling

Shapley values enhance decision-making in DNA profiling and related fields.

Lauren Elborough, Duncan Taylor, Melissa Humphries

2025-05-29T20:29:14+00:00 ― 6 min read

Machine Learning Neural Networks in High-Dimensional Data

Exploring how neural networks tackle high-dimensional challenges in classification tasks.

Andres Felipe Lerma-Pineda, Philipp Petersen, Simon Frieder

2025-05-29T19:06:36+00:00 ― 5 min read

Machine Learning Enhancing Neural Performance Through Feature Learning

Research highlights how feature learning improves neural network performance effectively.

Blake Bordelon, Alexander Atanasov, Cengiz Pehlevan

2025-05-29T17:43:58+00:00 ― 7 min read

Machine Learning Improving Classification with Enriched Functional Tree-Based Classifiers

A new method enhances classification of high-dimensional time-series data using functional analysis.

Fabrizio Maturo, Annamaria Porreca

2025-05-29T16:21:20+00:00 ― 7 min read

Machine Learning Advancements in Transfer Learning Techniques

Exploring effective strategies for hyperparameter selection in transfer learning.

Koki Okajima, Tomoyuki Obuchi

2025-05-29T14:58:42+00:00 ― 5 min read

Machine Learning Balancing Fairness and Performance in Machine Learning

A new method offers a simpler way to compute fairness-performance balance in machine learning.

Mark Kozdoba, Binyamin Perets, Shie Mannor

2025-05-29T13:36:04+00:00 ― 6 min read

Machine Learning A Bayesian Approach to Change Point Detection in Hawkes Processes

This article presents a new method for identifying changes in event data.

Zeyue Zhang, Xiaoling Lu, Feng Zhou

2025-05-29T12:13:26+00:00 ― 5 min read

Methodology New Method for Causal Effect Estimation in Health Studies

Introducing a flexible method to estimate causal effects over time using advanced techniques.

Axel Martin, Michele Santacatterina, Iván Díaz

2025-05-29T09:28:10+00:00 ― 6 min read

Machine Learning Advancing List Regression through Sample Complexity Insights

This study explores sample complexity in list regression for improved predictions.

Chirag Pabbaraju, Sahasrajit Sarmasarkar

2025-05-28T18:19:12+00:00 ― 6 min read

Machine Learning Advancing Probabilistic Forecasting Techniques

New framework improves forecasting accuracy and reliability in uncertain environments.

Charles Marx, Volodymyr Kuleshov, Stefano Ermon

2025-05-28T16:56:34+00:00 ― 7 min read

Machine Learning Advancements in Function Approximation with CFNN

Chebyshev Feature Neural Network improves precision in function approximation tasks.

Zhongshu Xu, Yuan Chen, Dongbin Xiu

2025-05-28T15:33:56+00:00 ― 5 min read

Machine Learning Federated Learning: Collaborative Privacy in Predictions

This research highlights innovative methods for privacy in collaborative machine learning.

Fengyu Gao, Ruiquan Huang, Jing Yang

2025-05-28T14:11:18+00:00 ― 6 min read

Machine Learning Navigating Choices with Multi-Armed Bandits

Learn about decision-making strategies that minimize regret in experiments.

Junwen Yang, Vincent Y. F. Tan, Tianyuan Jin

2025-05-28T11:26:02+00:00 ― 7 min read

Machine Learning Advancements in Graph Neural Networks for Geographical Data

New framework enhances predictions and uncertainty estimations in geographical data analysis.

William E. R. de Amorim, Scott A. Sisson, T. Rodrigues

2025-05-28T10:03:24+00:00 ― 6 min read

Machine Learning Evaluating Confidence Intervals for Generalization Error in Machine Learning

A comprehensive study comparing methods for estimating confidence intervals in machine learning models.

Hannah Schulz-Kümpel, Sebastian Fischer, Thomas Nagler

2025-05-28T08:40:46+00:00 ― 11 min read

Machine Learning Advancements in Self-Supervised Learning with SimCLR

SimCLR enhances model training using unlabeled data in vision tasks.

Han Zhang, Yuan Cao

2025-05-28T07:18:08+00:00 ― 7 min read

Machine Learning Connecting AI and Statistical Mechanics

Exploring how statistical concepts inform artificial intelligence and machine learning methods.

Akshay Balsubramani

2025-05-28T05:55:30+00:00 ― 7 min read

Methodology Connections That Matter: Teacher Networks and Job Satisfaction

Examining how teacher relationships impact job satisfaction and school climate.

Selena Wang, Plamena Powla, Tracy Sweet

2025-05-28T03:10:14+00:00 ― 5 min read

Machine Learning Tilted Empirical Risk: A New Approach to Generalization Error

Learn how tilted empirical risk enhances machine learning model performance.

Gholamali Aminian, Amir R. Asadi, Tian Li

2025-05-27T21:39:42+00:00 ― 6 min read

Machine Learning Identifying Shared Components in Unaligned Data

Research proposes methods to find common elements in unaligned multi-modal data.

Subash Timilsina, Sagar Shrestha, Xiao Fu

2025-05-27T20:17:04+00:00 ― 6 min read