Statistical Learning
Learning Matchable Prior For Entity Alignment with Unlabeled Dangling Cases
To address this challenge, we propose the framework Lambda for dangling detection and entity alignment.
Hierarchical Federated Learning with Multi-Timescale Gradient Correction
We analytically characterize the convergence behavior of MTGC under general non-convex settings, overcoming challenges associated with couplings between correction terms.
Transfer Learning for Latent Variable Network Models
We study transfer learning for estimation in latent variable network models.
Exploring and Interacting with the Set of Good Sparse Generalized Additive Models
The Rashomon set is the set of models that are approximately as good as the best model in the class. That is, it is the set of all good models.
Unified Mechanism-Specific Amplification by Subsampling and Group Privacy Amplification Jan Schuchardt
Our tight mechanism-specific bounds outperform tight mechanism-agnostic bounds and classic group privacy results.
