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06/07/2023
End-to-End Learning for Stochastic Optimization: A Bayesian Perspective
We develop a principled approach to end-to-end learning in stochastic op...
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05/30/2023
Policy Gradient Algorithms for Robust MDPs with Non-Rectangular Uncertainty Sets
We propose a policy gradient algorithm for robust infinite-horizon Marko...
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05/23/2023
Optimal Learning via Moderate Deviations Theory
This paper proposes a statistically optimal approach for learning a func...
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05/01/2023
ISAAC Newton: Input-based Approximate Curvature for Newton's Method
We present ISAAC (Input-baSed ApproximAte Curvature), a novel method tha...
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01/26/2023
A Robust Optimisation Perspective on Counterexample-Guided Repair of Neural Networks
Counterexample-guided repair aims at creating neural networks with mathe...
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06/12/2021
Distributionally Robust Optimization with Markovian Data
We study a stochastic program where the probability distribution of the ...
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06/08/2021
Robust Generalization despite Distribution Shift via Minimum Discriminating Information
Training models that perform well under distribution shifts is a central...
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02/06/2021
Efficient Learning of a Linear Dynamical System with Stability Guarantees
We propose a principled method for projecting an arbitrary square matrix...
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06/08/2020
Quantum Legendre-Fenchel Transform
We present a quantum algorithm to compute the discrete Legendre-Fenchel ...
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12/13/2017