[NeurIPS 2023] Efficient Solver for ERM with PLQ Loss and Linear Constraints

EnsLoss: Stochastic Calibrated Loss Ensembles for Preventing Overfitting in Classification

A statistical learning toolkit for high-dimensional Hawkes processes in Python

[NeurIPS 2023] Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence

[NeurIPS 2023] Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence

Lecture notes taken in the Quantitative Foundations of Artificial Intelligence class in Fall 2023, taught by Prof. Dr. Ludger Overbeck at Justus Liebig University Giessen.

Perceptron learning algorithm implemented in Python

Reproduction code for paper "Liu and Tong (2026). Metric entropy-free sample complexity bounds for sample average approximation in convex stochastic programming"

Adaptive Boosting of Weak Learners implemented in Python