Prediction Function

Prediction functions aim to model the relationship between input variables and an outcome, enabling accurate predictions and informed decision-making. Current research emphasizes developing prediction functions that handle complex, non-linear relationships, often employing advanced techniques like conditional generative adversarial networks (GANs) and functional bilevel optimization, as well as adapting to scenarios with imbalanced data or extreme values. These advancements are improving the accuracy and reliability of predictions across diverse fields, from scientific discovery (e.g., identifying disease biomarkers) to engineering applications (e.g., optimizing resource allocation), while also focusing on providing robust uncertainty quantification through methods like conformal prediction.

Papers

April 21, 2024

Generalized Regression with Conditional GANs
Deddy Jobson, Eddy Hudson
Novel Regression Conditional Generative Adversarial Network Linear Regression Long Tailed Data Regression Problem Conditional GAN Prediction Function

March 29, 2024

Functional Bilevel Optimization for Machine Learning
Ieva Petrulionyte, Julien Mairal, Michael Arbel
Neural Network Machine Learning Bilevel Optimization Prediction Function

October 7, 2023

The Conditional Prediction Function: A Novel Technique to Control False Discovery Rate for Complex Models
Yushu Shi, Michael Martens
Complex Model Novel Technique False Discovery Rate Prediction Function Knockoff Statistic Irrelevant Variable

September 30, 2023

Nonparametric active learning for cost-sensitive classification
Boris Ndjia Njike, Xavier Siebert
Active Learning Cost Sensitive Nonparametric Modeling Passive Learning Prediction Function

March 6, 2023

On Regression in Extreme Regions
Nathan Huet, Stephan Clémençon, Anne Sabourin
Novel Regression Empirical Risk Minimization Predictive Performance Challenging Environment Prediction Function

November 29, 2022

An Extreme-Adaptive Time Series Prediction Model Based on Probability-Enhanced LSTM Neural Networks
Yanhong Li, Jack Xu, David C. Anastasiu
Probabilistic Neural Network Adaptive Forecasting Selective Neural Network Prediction Function

June 24, 2022

Analyzing Explainer Robustness via Probabilistic Lipschitzness of Prediction Functions
Zulqarnain Khan, Davin Hill, Aria Masoomi, Joshua Bone, Jennifer Dy
Native Robustness Inherent Interpretability Robust Explanation Local Prediction Prediction Function

May 28, 2022

A Confidence Machine for Sparse High-Order Interaction Model
Diptesh Das, Eugene Ndiaye, Ichiro Takeuchi
Conformal Prediction Predictive Model Machine Self Confidence Sparse High Order Interaction Prediction Function Complex Predictive Model

May 2, 2022

Smoothed Online Convex Optimization Based on Discounted-Normal-Predictor
Lijun Zhang, Wei Jiang, Jinfeng Yi, Tianbao Yang
Optimal Regret Online Convex Optimization Adaptive Regret Online Gradient Descent Prediction Function