papers

Publications (10)

eess.SY2024

Stochastic Opinion Dynamics under Social Pressure in Arbitrary Networks

Jennifer Tang, Aviv Adler, Amir Ajorlou +1

Social pressure is a key factor affecting the evolution of opinions on networks in many types of settings, pushing people to conform to their neighbors' opinions. To study this, th…

cs.IT2023

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|…

cs.IT2023

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…

cs.IT2026

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…

cs.CV2018

Generative Visual Rationales

Jarrel Seah, Jennifer Tang, Andy Kitchen +1

Interpretability and small labelled datasets are key issues in the practical application of deep learning, particularly in areas such as medicine. In this paper, we present a semi-…

eess.SP2022

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…