463 citations · 5.1k across the 190 of their papers we have counts for
17 papers · 1 filter
Finite-Time Consensus Learning for Decentralized Optimization with Nonlinear Gossiping
Junya Chen, Sijia Wang, Lawrence Carin +1
Distributed learning has become an integral tool for scaling up machine learning and addressing the growing need for data privacy. Although more robust to the network topology, dec…
Variational Inference with Holder Bounds
Junya Chen, Danni Lu, Zidi Xiu +3
The recent introduction of thermodynamic integration techniques has provided a new framework for understanding and improving variational inference (VI). In this work, we present a…
Explainable multiple abnormality classification of chest CT volumes
Rachel Lea Draelos, Lawrence Carin
Understanding model predictions is critical in healthcare, to facilitate rapid verification of model correctness and to guard against use of models that exploit confounding variabl…
Hölder Bounds for Sensitivity Analysis in Causal Reasoning
Serge Assaad, Shuxi Zeng, Henry Pfister +2
We examine interval estimation of the effect of a treatment T on an outcome Y given the existence of an unobserved confounder U. Using Hölder's inequality, we derive a set of bound…
Simpler, Faster, Stronger: Breaking The log-K Curse On Contrastive Learners With FlatNCE
Junya Chen, Zhe Gan, Xuan Li +10
InfoNCE-based contrastive representation learners, such as SimCLR, have been tremendously successful in recent years. However, these contrastive schemes are notoriously resource de…
Gradient Importance Learning for Incomplete Observations
Qitong Gao, Dong Wang, Joshua D. Amason +6
Though recent works have developed methods that can generate estimates (or imputations) of the missing entries in a dataset to facilitate downstream analysis, most depend on assump…