5 citations · 6 across the 5 of their papers we have counts for
6 papers · 1 filter
Explore-then-Commit for Nonstationary Linear Bandits with Latent Dynamics
Sunmook Choi, Yahya Sattar, Yassir Jedra +2
We study a nonstationary bandit problem where rewards depend on both actions and latent states, the latter governed by unknown linear dynamics. Crucially, the state dynamics also d…
Pre-trained Large Language Models Learn Hidden Markov Models In-context
Yijia Dai, Zhaolin Gao, Yahya Sattar +2
Hidden Markov Models (HMMs) are foundational tools for modeling sequential data with latent Markovian structure, yet fitting them to real-world data remains computationally challen…
Finite Sample Identification of Partially Observed Bilinear Dynamical Systems
Yahya Sattar, Yassir Jedra, Maryam Fazel +1
We consider the problem of learning a realization of a partially observed bilinear dynamical system (BLDS) from noisy input-output data. Given a single trajectory of input-output s…
Learning Linear Dynamics from Bilinear Observations
Yahya Sattar, Yassir Jedra, Sarah Dean
We consider the problem of learning a realization of a partially observed dynamical system with linear state transitions and bilinear observations. Under very mild assumptions on t…
Exploring Weight Importance and Hessian Bias in Model Pruning
Mingchen Li, Yahya Sattar, Christos Thrampoulidis +1
Model pruning is an essential procedure for building compact and computationally-efficient machine learning models. A key feature of a good pruning algorithm is that it accurately…
Quickly Finding the Best Linear Model in High Dimensions
Yahya Sattar, Samet Oymak
We study the problem of finding the best linear model that can minimize least-squares loss given a data-set. While this problem is trivial in the low dimensional regime, it becomes…