Function Aligned Regression: A Method Explicitly Learns Functional Derivatives from Data.
CoRR, 2024
Non-Smooth Weakly-Convex Finite-sum Coupled Compositional Optimization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
LibAUC: A Deep Learning Library for X-Risk Optimization.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity.
Proceedings of the International Conference on Machine Learning, 2023
Provable Multi-instance Deep AUC Maximization with Stochastic Pooling.
Proceedings of the International Conference on Machine Learning, 2023
Benchmarking Deep AUROC Optimization: Loss Functions and Algorithmic Choices.
CoRR, 2022
When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee.
Proceedings of the International Conference on Machine Learning, 2022
A Unified DRO View of Multi-class Loss Functions with top-N Consistency.
CoRR, 2021
Deep Unsupervised Binary Coding Networks for Multivariate Time Series Retrieval.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
A Robust Zero-Sum Game Framework for Pool-based Active Learning.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019
A Machine Learning Approach for Air Quality Prediction: Model Regularization and Optimization.
Big Data Cogn. Comput., 2018
deBWT: parallel construction of Burrows-Wheeler Transform for large collection of genomes with de Bruijn-branch encoding.
Bioinform., 2016