Path-following gradient-based decomposition algorithms for separable convex optimization

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Path-following gradient-based decomposition algorithms for separable convex optimization

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Universal and adaptive methods for robust stochastic optimization

Results on Sparse Integer Programming and Geometric Independent Sets

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Probabilistic methods for neural combinatorial optimization

Stochastic adaptive resampling for the estimation of discrete choice models

Training Efficient Controllers via Analytic Policy Gradient

Safe Zeroth-Order Convex Optimization Using Quadratic Local Approximations

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Contextual Stochastic Bilevel Optimization

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