1 citations · 1 across the 5 of their papers we have counts for
6 papers
From Pixels, Without Pre-training: Joint Generative and Self-Supervised Representation Learning in One Model
Vicente Balmaseda, Ching-Long Lin, Tianbao Yang
Strong image generation models are conditioned on class labels, aligned to frozen pretrained encoders, or built on separately trained autoencoders. While effective, generation then…
A Geometry-Aware Efficient Algorithm for Compositional Entropic Risk Minimization
Xiyuan Wei, Linli Zhou, Bokun Wang +2
This paper studies optimization for a family of problems termed , in which each data's loss is formulated as a Log-Expectation-Ex…
Stochastic Primal-Dual Double Block-Coordinate for Two-way Partial AUC Maximization
Linli Zhou, Bokun Wang, My T. Thai +1
Two-way partial AUC (TPAUC) is a critical performance metric for binary classification with imbalanced data, as it focuses on specific ranges of the true positive rate (TPR) and fa…
Discovering Global False Negatives On the Fly for Self-supervised Contrastive Learning
Vicente Balmaseda, Bokun Wang, Ching-Long Lin +1
In self-supervised contrastive learning, negative pairs are typically constructed using an anchor image and a sample drawn from the entire dataset, excluding the anchor. However, t…
On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning
Bokun Wang, Yunwen Lei, Yiming Ying +1
We study the discriminative probabilistic modeling on a continuous domain for the data prediction task of (multimodal) self-supervised representation learning. To address the chall…
A Near-Optimal Single-Loop Stochastic Algorithm for Convex Finite-Sum Coupled Compositional Optimization
Bokun Wang, Tianbao Yang
This paper studies a class of convex Finite-sum Coupled Compositional Optimization (cFCCO) problems with applications including group distributionally robust optimization (GDRO) an…