2 citations · 3 across the 10 of their papers we have counts for
4 papers · 1 filter
Universal Bounds for Self-Normalized Kullback-Leibler Estimation
Buu Phan, Lester Mackey, David Alvarez-Melis
This work studies an entropy-based estimator of Kullback-Leibler (KL) divergence constructed from normalized importance weights. We prove a universal finite-sample bound showing th…
Scalable Discrete-to-Continuous Channel Simulation for Compression and Privacy
Joseph Rowan, Buu Phan, Ashish J. Khisti
Channel simulation has recently emerged as a useful component in machine learning systems where samples from a prescribed probability distribution are to be compressed. Yet, genera…
Multi-Marginal Couplings for Metropolis-Hastings
Buu Phan, Gergely Flamich, Ashish Khisti +1
Convergence diagnosis for Markov chain Monte Carlo is a matter of fundamental importance in computational statistics: it determines the resources allocated to a particular sampling…
One-Shot Broadcast Joint Source-Channel Coding with Codebook Diversity
Joseph Rowan, Buu Phan, Ashish Khisti
We study a one-shot joint source-channel coding setting where the source is encoded once and broadcast to decoders through independent channels. Success is predicated on at lea…