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09/19/2023
Oracle Complexity Reduction for Model-free LQR: A Stochastic Variance-Reduced Policy Gradient Approach
We investigate the problem of learning an ϵ-approximate solution for the...
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08/08/2023
Meta-Learning Operators to Optimality from Multi-Task Non-IID Data
A powerful concept behind much of the recent progress in machine learnin...
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04/03/2023
Learning Personalized Models with Clustered System Identification
We address the problem of learning linear system models from observing m...
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03/28/2022
FedADMM: A Federated Primal-Dual Algorithm Allowing Partial Participation
Federated learning is a framework for distributed optimization that plac...
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12/08/2021
Learning Linear Models Using Distributed Iterative Hessian Sketching
This work considers the problem of learning the Markov parameters of a l...
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09/06/2021
Large-Scale System Identification Using a Randomized SVD
Learning a dynamical system from input/output data is a fundamental task...
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07/12/2021
Coloring graphs with forbidden bipartite subgraphs
A conjecture of Alon, Krivelevich, and Sudakov states that, for any grap...
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03/27/2019