works on

From the 1 of 7 linked papers with an AI index.

most citedThe Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication

1 citations · 1 across the 3 of their papers we have counts for

collaborators

7 papers

cs.LG20261 cited

The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication

Kumar Kshitij Patel, Margalit Glasgow, Ali Zindari +5

The paper analyzes the theoretical limits of Local SGD for distributed learning with heterogeneous data, showing existing heterogeneity assumptions are insufficient for proving its…

cs.LG2026

Learning through Internalization

Nikolaos Tsilivis, Nirmit Joshi, Marko Medvedev +2

We study internalization processes, by which neural-network-based systems absorb an explicit computational procedure into their own weights, and how they facilitate learning. We in…

cs.LG2026

Learning to Think from Multiple Thinkers

Nirmit Joshi, Roey Magen, Nathan Srebro +2

We study learning with Chain-of-Thought (CoT) supervision from multiple thinkers, all of whom provide correct but possibly systematically different solutions, e.g., step-by-step so…

cs.LG2026

Learning to Answer from Correct Demonstrations

Nirmit Joshi, Gene Li, Siddharth Bhandari +3

We study the problem of learning to generate an answer (or completion) to a question (or prompt), where there could be multiple correct answers, any one of which is acceptable at t…

cs.LG2025

Learning single-index models via harmonic decomposition

Nirmit Joshi, Hugo Koubbi, Theodor Misiakiewicz +1

We study the problem of learning single-index models, where the label depends on the input only through an unknown one-dimensio…

stat.ML2025

A Theory of Learning with Autoregressive Chain of Thought

Nirmit Joshi, Gal Vardi, Adam Block +4

For a given base class of sequence-to-next-token generators, we consider learning prompt-to-answer mappings obtained by iterating a fixed, time-invariant generator for multiple ste…