658 citations · 2.2k across the 187 of their papers we have counts for
12 papers · 1 filter
Two Agents, One Prompt, and Your Weight
Elchanan Mossel, Amnon Schreiber
We investigate a quantitative variant of the classic Two Doors logic puzzle, in which the answer space is no longer binary, for example when the goal is to recover a numerical fact…
Reconstructing Riemannian Metrics From Random Geometric Graphs
Han Huang, Pakawut Jiradilok, Elchanan Mossel
Random geometric graphs are random graph models defined on metric measure spaces. A random geometric graph is generated by first sampling points from a metric space and then connec…
Learning and Testing Convex Functions
Renato Ferreira Pinto, Cassandra Marcussen, Elchanan Mossel +1
We consider the problems of \emph{learning} and \emph{testing} real-valued convex functions over Gaussian space. Despite the extensive study of function convexity across mathematic…
On Algorithmic Robustness of Corrupted Markov Chains
Jason Gaitonde, Elchanan Mossel
We study the algorithmic robustness of general finite Markov chains in terms of their stationary distributions to general, adversarial corruptions of the transition matrix. We show…
Online Learning of Neural Networks
Amit Daniely, Idan Mehalel, Elchanan Mossel
We study online learning of feedforward neural networks with the sign activation function that implement functions from the unit ball in to a finite label set $\{1,…
Asymptotics for the harmonic descent chain and applications to critical beta-splitting trees
Anna Brandenberger, Byron Chin, Elchanan Mossel
Motivated by the connection to a probabilistic model of phylogenetic trees introduced by Aldous, we study the recursive sequence governed by the rule $x_n = \sum_{i=1}^{n-1} \frac{…
Stochastic block models with many communities and the Kesten--Stigum bound
Byron Chin, Elchanan Mossel, Youngtak Sohn +1
We study the inference of communities in stochastic block models with a growing number of communities. For block models with vertices and a fixed number of communities , it…
Low-dimensional Functions are Efficiently Learnable under Randomly Biased Distributions
Elisabetta Cornacchia, Dan Mikulincer, Elchanan Mossel
The problem of learning single index and multi index models has gained significant interest as a fundamental task in high-dimensional statistics. Many recent works have analysed gr…
Noise Sensitivity and Learning Lower Bounds for Hierarchical Functions
Rupert Li, Elchanan Mossel
Recent works explore deep learning's success by examining functions or data with hierarchical structure. To study the learning complexity of functions with hierarchical structure,…
Optimal Low degree hardness for Broadcasting on Trees
Han Huang, Elchanan Mossel
Broadcasting on trees is a fundamental model from statistical physics that plays an important role in information theory, noisy computation and phylogenetic reconstruction within c…
Random Subwords and Billiard Walks in Affine Weyl Groups
Colin Defant, Pakawut Jiradilok, Elchanan Mossel
Let be an irreducible affine Weyl group, and let be a finite word over the alphabet of simple reflections of . Fix a probability . For each integer $…
Detecting Abrupt Changes in Point Processes: Fundamental Limits and Applications
Anna Brandenberger, Elchanan Mossel, Anirudh Sridhar
We consider the problem of detecting abrupt changes (i.e., large jump discontinuities) in the rate function of a point process. The rate function is assumed to be fully unknown, no…