Statistics - Machine Learning

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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

Methodology Advancing Predictions with Posterior Conformal Prediction

A method that improves prediction accuracy across diverse groups.

Yao Zhang, Emmanuel J. Candès

2025-05-27T18:54:26+00:00 ― 7 min read

Applications Selecting Simulation-Based Inference Methods in Computational Biology

A guide to choosing SBI methods for biological data analysis.

Xiaoyu Wang, Ryan P. Kelly, Adrianne L. Jenner

2025-05-27T16:09:10+00:00 ― 7 min read

Machine Learning Advancements in Survival Analysis: SurvCORN Method

SurvCORN enhances survival predictions with neural networks for better patient outcomes.

Muhammad Ridzuan, Numan Saeed, Fadillah Adamsyah Maani

2025-05-27T14:46:32+00:00 ― 6 min read

Machine Learning Addressing Class Imbalance in Machine Learning Models

Learn strategies to improve model performance on imbalanced datasets.

Mohamed Abdelhamid, Abhyuday Desai

2025-05-27T13:23:54+00:00 ― 7 min read

Machine Learning Progress in Average Reward TD Learning Convergence

New insights into average reward TD learning help ensure reliable decision-making.

Ethan Blaser, Shangtong Zhang

2025-05-27T10:38:38+00:00 ― 6 min read

Machine Learning Annealing Flow: A New Approach to Sampling

Annealing Flow offers improved sampling techniques for complex distributions in various fields.

Dongze Wu, Yao Xie

2025-05-27T06:30:44+00:00 ― 7 min read

Machine Learning Understanding Machine Learning Model Predictions

A unified framework for improving machine learning model explainability.

Beepul Bharti, Paul Yi, Jeremias Sulam

2025-05-27T05:08:06+00:00 ― 6 min read

Machine Learning Advancing Data Generation through Flow Matching Techniques

A new approach to generating data using flow matching and Bayesian methods.

Ganchao Wei, Li Ma

2025-05-27T03:45:28+00:00 ― 5 min read

Machine Learning Addressing Uncertainty in Treatment Dosing

A new method improves predictions for individualized treatment effectiveness.

Jarne Verhaeghe, Jef Jonkers, Sofie Van Hoecke

2025-05-27T02:22:50+00:00 ― 7 min read

Machine Learning New Method Tackles Inverse Problems in Science

Ensemble Kalman Diffusion Guidance offers a fresh approach to solving complex inverse problems.

Hongkai Zheng, Wenda Chu, Austin Wang

2025-05-27T01:00:12+00:00 ― 5 min read

Machine Learning Enhancing Decision-Making Through Task Knowledge Transfer

A new method improves performance by sharing insights between similar tasks.

NR Rahul, Vaibhav Katewa

2025-05-26T23:37:34+00:00 ― 5 min read

Applications Predicting Electricity Use for a Greener Future

A new method to estimate household electricity consumption using predictive clustering trees.

J. Soenen, A. Yurtman, T. Becker

2025-05-26T19:29:40+00:00 ― 7 min read