Statistics

A new method improves the estimation of treatment effects across diverse populations.

A new method improves estimates of treatment effects despite participant noncompliance.

Methods to determine sources of pollutants through sensor data analysis.

Research shows new methods can improve building energy efficiency and comfort.

Improving reproducibility in machine learning requires embracing variability in results.

A new method for assessing cardiovascular disease risk based on individual factors.

Aiming to clarify Bayesian methods for astronomers with practical advice.

A new method reveals insights into human gestures and their relationship with speech.

This study presents a new method for bi-clustering using block-diagonal covariance.

New models improve analysis of complex, high-dimensional data while considering skewness.

Sparse GEMINI combines feature selection and clustering for improved data analysis.

A new approach to efficiently detect changes in various data streams.

Improve model predictions by smartly selecting input samples for Monte Carlo simulations.

Discover a simple method for efficient data value selection.

Introducing mGHS for effective network analysis across diverse datasets.

Research reveals a new approach to analyze health outcomes over time.

Examining methods to enhance the reliability of diffusion models in image generation.

Exploring how user feedback enhances contextual bandit algorithms.

New methods improve efficiency in training deep learning models.

This study shows AMP can work well from random starts in matrix estimation.

OPORP streamlines data vector management, improving efficiency and accuracy in retrieval tasks.

Discover how pre-existing data boosts online learning performance.

This article discusses improving audio recommendations for lasting user engagement.

Sparse GEMINI combines feature selection and clustering for improved data analysis.

A new method improves the estimation of treatment effects across diverse populations.

A new method improves estimates of treatment effects despite participant noncompliance.

This study highlights a Bayesian approach to improve quantile regression estimates with measurement errors.

This article discusses a new approach to meta-analysis in clinical research.

Exploring how convolutional kernel size affects bias in facial recognition systems.

Sparse GEMINI combines feature selection and clustering for improved data analysis.

This article examines a model for consumer decision-making in today's market.

Methods to determine sources of pollutants through sensor data analysis.

Discover a simple method for efficient data value selection.

New sampling methods improve efficiency and accuracy in Bayesian Neural Networks.

Examining the reliability and validation of influence functions in deep learning models.

A new algorithm enhances accuracy in forecasting disease outbreaks through detailed data generation.

A discussion on merging statistical approaches for better data analysis.

A fresh approach uncovers individual variations in program treatment effects.

Methods to accurately calculate averages and variances despite missing data points.

A method for predicting specific outcomes using relevant past data.

This study focuses on identifying hidden bipartite structures within random networks.

DCSBM reveals community structures in complex networks through varying connection strengths.

A look into concentration inequalities and their role in random variable analysis.

A clear look at probabilities and their role in dealing with uncertainty.

A fresh look at probability that embraces uncertainty and flexibility.

Improving methods for estimating ordered values across various fields is crucial for decision-making.

A study on improving entropy estimation methods for better data analysis.

This study shows AMP can work well from random starts in matrix estimation.