From the 1 of 35 linked papers with an AI index.
35 papers
Stochastic Autoregressive Learning
Ilan Doron-Arad, Idan Mehalel, Elchanan Mossel
Motivated by LLMs, which generate outputs by iteratively sampling from next-token distributions, we introduce a PAC-learning model for binary stochastic autoregressive learning. Th…
Recovering Assignments with One-Sided Noise
Cassandra Marcussen, Elchanan Mossel, Colin Sandon
We study the query complexity of recovering a planted assignment from a random constraint-satisfaction instance with one-sided noise. We consider the following 1-CNF recovery probl…
Learning and Testing Convex Functions
Renato Ferreira Pinto, Cassandra Marcussen, Elchanan Mossel +1
The paper investigates how to learn and test real-valued convex functions under the Gaussian distribution, providing algorithms with explicit sample‑complexity bounds assuming the…
Denoising Distances in Metric Measure Spaces
Han Huang, Pakawut Jiradilok, Elchanan Mossel
Recent work studied the problem of finding clusters and denoising pairwise distances from noisy distances of points sampled on a manifold. We study the same problems in more genera…
Depth Lower Bounds for ReLU Networks with Binary Inputs
Neil Krishnan, Elchanan Mossel
We study the role of depth in ReLU networks with discrete (Boolean) inputs and real-valued outputs, complementing two established lines of work. For Boolean inputs, striking depth…
Multiplayer Games of War
Axel Adjei, Neil Krishnan, Elchanan Mossel
A recent paper by Bhatia, Chin, Mani, and Mossel (2026) defined stochastic processes modeling the game of War for {\em two players} with cards. That paper showed that these mod…