21 citations · 38 across the 4 of their papers we have counts for
5 papers
A Model-Driven Lossless Compression Algorithm Resistant to Mismatch
Cordelia Hu, Jennifer Tang
Due to the fundamental connection between next-symbol prediction and compression, modern predictive models, such as large language models (LLMs), can be combined with entropy codin…
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…
Efficient Representation of Large-Alphabet Probability Distributions
Aviv Adler, Jennifer Tang, Yury Polyanskiy
A number of engineering and scientific problems require representing and manipulating probability distributions over large alphabets, which we may think of as long vectors of reals…
Capacity of Noisy Permutation Channels
Jennifer Tang, Yury Polyanskiy
We establish the capacity of a class of communication channels introduced in [1]. The -letter input from a finite alphabet is passed through a discrete memoryless channel $P_{Z|…