658 citations · 2.2k across the 187 of their papers we have counts for
8 papers · 1 filter
Reconstruction on Trees and Low-Degree Polynomials
Frederic Koehler, Elchanan Mossel
The study of Markov processes and broadcasting on trees has deep connections to a variety of areas including statistical physics, graphical models, phylogenetic reconstruction, Mar…
Information Spread with Error Correction
Omri Ben-Eliezer, Elchanan Mossel, Madhu Sudan
We study the process of information dispersal in a network with communication errors and local error-correction. Specifically we consider a simple model where a single bit of infor…
Tracking Truth with Liquid Democracy
Adam Berinsky, Daniel Halpern, Joseph Y. Halpern +4
The dynamics of random transitive delegations on a graph are of particular interest when viewed through the lens of an emerging voting paradigm, liquid democracy. This paradigm all…
Spectral Recovery of Binary Censored Block Models
Souvik Dhara, Julia Gaudio, Elchanan Mossel +1
Community detection is the problem of identifying community structure in graphs. Often the graph is modeled as a sample from the Stochastic Block Model, in which each vertex belong…
Approximate polymorphisms
Gilad Chase, Yuval Filmus, Dor Minzer +2
For a function , a function is called a -polymorphism if their actions commute: $f(g(\mathsf{row}_1(Z)),\ldots,g(\maths…
Spoofing Generalization: When Can't You Trust Proprietary Models?
Ankur Moitra, Elchanan Mossel, Colin Sandon
In this work, we study the computational complexity of determining whether a machine learning model that perfectly fits the training data will generalizes to unseen data. In partic…
Inference in Opinion Dynamics under Social Pressure
Ali Jadbabaie, Anuran Makur, Elchanan Mossel +1
We introduce a new opinion dynamics model where a group of agents holds two kinds of opinions: inherent and declared. Each agent's inherent opinion is fixed and unobservable by the…
Learning to Sample from Censored Markov Random Fields
Ankur Moitra, Elchanan Mossel, Colin Sandon
We study learning Censor Markov Random Fields (abbreviated CMRFs). These are Markov Random Fields where some of the nodes are censored (not observed). We present an algorithm for l…