11 papers
Differentially Private Conformal Prediction
Jiamei Wu, Ce Zhang, Zhipeng Cai +4
Conformal prediction (CP) has attracted broad attention as a simple and flexible framework for uncertainty quantification through prediction sets. In this work, we study how to dep…
Understanding Fairness and Prediction Error through Subspace Decomposition and Influence Analysis
Enze Shi, Pankaj Bhagwat, Zhixian Yang +2
Machine learning models have achieved widespread success but often inherit and amplify historical biases, resulting in unfair outcomes. Traditional fairness methods typically impos…
Predicting Market Trends with Enhanced Technical Indicator Integration and Classification Models
Abdelatif Hafid, Abderazzak Mouiha, Linglong Kong +4
Thanks to the high potential for profit, trading has become increasingly attractive to investors as the cryptocurrency and stock markets rapidly expand. However, because financial…
CBMA: Improving conformal prediction through Bayesian model averaging
Pankaj Bhagwat, Linglong Kong, Bei Jiang
Conformal prediction has emerged as a popular technique for facilitating valid predictive inference across a spectrum of machine learning models, under minimal assumption of exchan…
Conformal Inference For Missing Data under Multiple Robust Learning
Wenlu Tang, Hongni Wang, Xingcai Zhou +2
We develop a novel approach to tackle the common but challenging problem of conformal inference for missing data in machine learning, focusing on Missing at Random (MAR) data. We p…
Toward Optimal Statistical Inference in Noisy Linear Quadratic Reinforcement Learning over a Finite Horizon
Bo Pan, Jianya Lu, Yafei Wang +3
Recent developments in Reinforcement learning have significantly enhanced sequential decision-making in uncertain environments. Despite their strong performance guarantees, most ex…