4 citations · 4 across the 5 of their papers we have counts for
6 papers
Fine-grained Analysis of Stability and Generalization for Stochastic Bilevel Optimization
Xuelin Zhang, Hong Chen, Bin Gu +2
Stochastic bilevel optimization (SBO) has been integrated into many machine learning paradigms recently, including hyperparameter optimization, meta learning, and reinforcement lea…
Negative Label Guided OOD Detection with Pretrained Vision-Language Models
Xue Jiang, Feng Liu, Zhen Fang +4
Out-of-distribution (OOD) detection aims at identifying samples from unknown classes, playing a crucial role in trustworthy models against errors on unexpected inputs. Extensive re…
CageViT: Convolutional Activation Guided Efficient Vision Transformer
Hao Zheng, Jinbao Wang, Xiantong Zhen +3
Recently, Transformers have emerged as the go-to architecture for both vision and language modeling tasks, but their computational efficiency is limited by the length of the input…
On the Stability and Generalization of Triplet Learning
Jun Chen, Hong Chen, Xue Jiang +4
Triplet learning, i.e. learning from triplet data, has attracted much attention in computer vision tasks with an extremely large number of categories, e.g., face recognition and pe…
Error-based Knockoffs Inference for Controlled Feature Selection
Xuebin Zhao, Hong Chen, Yingjie Wang +4
Recently, the scheme of model-X knockoffs was proposed as a promising solution to address controlled feature selection under high-dimensional finite-sample settings. However, the p…
A Bayesian Federated Learning Framework with Online Laplace Approximation
Liangxi Liu, Xi Jiang, Feng Zheng +4
Federated learning (FL) allows multiple clients to collaboratively learn a globally shared model through cycles of model aggregation and local model training, without the need to s…