19 citations · 22 across the 6 of their papers we have counts for
6 papers
Almost-lossless compression of a low-rank random tensor
Minh Thanh Vu
In this work, we establish an asymptotic limit of almost-lossless compression of a random, finite alphabet tensor which admits a low-rank canonical polyadic decomposition.
Hypothesis Testing of Mixture Distributions using Compressed Data
Minh Thanh Vu
In this paper we revisit the binary hypothesis testing problem with one-sided compression. Specifically we assume that the distribution in the null hypothesis is a mixture distribu…
Belief Propagation for Approximate Inference
Dong Liu, Minh Thành Vu, Zuxing Li +1
Belief propagation (BP) algorithm is a widely used message-passing method for inference in graphical models. BP on loop-free graphs converges in linear time. But for graphs with lo…
Neural Network based Explicit Mixture Models and Expectation-maximization based Learning
Dong Liu, Minh Thành Vu, Saikat Chatterjee +1
We propose two neural network based mixture models in this article. The proposed mixture models are explicit in nature. The explicit models have analytical forms with the advantage…
Entropy-regularized Optimal Transport Generative Models
Dong Liu, Minh Thành Vu, Saikat Chatterjee +1
We investigate the use of entropy-regularized optimal transport (EOT) cost in developing generative models to learn implicit distributions. Two generative models are proposed. One…
General Rank Multiuser Downlink Beamforming With Shaping Constraints Using Real-valued OSTBC
Ka Lung Law, Xin Wen, Minh Thanh Vu +1
In this paper we consider optimal multiuser downlink beamforming in the presence of a massive number of arbitrary quadratic shaping constraints. We combine beamforming with full-ra…