research
∙
06/05/2023
LibAUC: A Deep Learning Library for X-Risk Optimization
This paper introduces the award-winning deep learning (DL) library calle...
share
research
∙
05/19/2023
Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization
In this paper, we aim to optimize a contrastive loss with individualized...
research
∙
02/24/2022
Provable Stochastic Optimization for Global Contrastive Learning: Small Batch Does Not Harm Performance
In this paper, we study contrastive learning from an optimization perspe...
research
∙
06/09/2021
Memory-based Optimization Methods for Model-Agnostic Meta-Learning
Recently, model-agnostic meta-learning (MAML) has garnered tremendous at...
research
∙
02/09/2021
Federated Deep AUC Maximization for Heterogeneous Data with a Constant Communication Complexity
eep UC (area under the ROC curve) aximization (DAM) has attracted much a...
research
∙
12/06/2020
Robust Deep AUC Maximization: A New Surrogate Loss and Empirical Studies on Medical Image Classification
Deep AUC Maximization (DAM) is a paradigm for learning a deep neural net...
research
∙
06/12/2020
Fast Objective and Duality Gap Convergence for Non-convex Strongly-concave Min-max Problems
This paper focuses on stochastic methods for solving smooth non-convex s...
research
∙
05/05/2020
Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks
In this paper, we study distributed algorithms for large-scale AUC maxim...
research
∙
08/28/2019
Stochastic AUC Maximization with Deep Neural Networks
Stochastic AUC maximization has garnered an increasing interest due to b...
research
∙
12/10/2018
