3 papers
cs.CV2026
Object Affordance Recognition and Grounding via Multi-scale Cross-modal Representation Learning
Xinhang Wan, Dongqiang Gou, Xinwang Liu +2
A core problem of Embodied AI is to learn object manipulation from observation, as humans do. To achieve this, it is important to localize 3D object affordance areas through observ…
stat.ME2025
Non-Asymptotic Analysis of Online Local Private Learning with SGD
Enze Shi, Jinhan Xie, Bei Jiang +2
Differentially Private Stochastic Gradient Descent (DP-SGD) has been widely used for solving optimization problems with privacy guarantees in machine learning and statistics. Despi…
stat.ME2025
Online differentially private inference in stochastic gradient descent
Jinhan Xie, Enze Shi, Bei Jiang +2
We propose a general privacy-preserving optimization-based framework for real-time environments without requiring trusted data curators. In particular, we introduce a noisy stochas…