980 citations · 2k across the 73 of their papers we have counts for
8 papers · 1 filter
Post-hoc Uncertainty Learning using a Dirichlet Meta-Model
Maohao Shen, Yuheng Bu, Prasanna Sattigeri +3
It is known that neural networks have the problem of being over-confident when directly using the output label distribution to generate uncertainty measures. Existing methods mainl…
On counterfactual inference with unobserved confounding
Abhin Shah, Raaz Dwivedi, Devavrat Shah +1
Given an observational study with independent but heterogeneous units, our goal is to learn the counterfactual distribution for each unit using only one -dimensional sample…
Information-theoretic Characterizations of Generalization Error for the Gibbs Algorithm
Gholamali Aminian, Yuheng Bu, Laura Toni +2
Various approaches have been developed to upper bound the generalization error of a supervised learning algorithm. However, existing bounds are often loose and even vacuous when ev…
Can Shadows Reveal Biometric Information?
Safa C. Medin, Amir Weiss, Frédo Durand +2
We study the problem of extracting biometric information of individuals by looking at shadows of objects cast on diffuse surfaces. We show that the biometric information leakage fr…
Data-Driven Blind Synchronization and Interference Rejection for Digital Communication Signals
Alejandro Lancho, Amir Weiss, Gary C. F. Lee +4
We study the potential of data-driven deep learning methods for separation of two communication signals from an observation of their mixture. In particular, we assume knowledge on…
Exploiting Temporal Structures of Cyclostationary Signals for Data-Driven Single-Channel Source Separation
Gary C. F. Lee, Amir Weiss, Alejandro Lancho +4
We study the problem of single-channel source separation (SCSS), and focus on cyclostationary signals, which are particularly suitable in a variety of application domains. Unlike c…