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09/01/2023
Data-Driven Projection for Reducing Dimensionality of Linear Programs: Generalization Bound and Learning Methods
This paper studies a simple data-driven approach to high-dimensional lin...
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06/09/2023
Faster Discrete Convex Function Minimization with Predictions: The M-Convex Case
Recent years have seen a growing interest in accelerating optimization a...
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02/02/2023
Rethinking Warm-Starts with Predictions: Learning Predictions Close to Sets of Optimal Solutions for Faster L-/L^â™®-Convex Function Minimization
An emerging line of work has shown that machine-learned predictions are ...
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09/17/2022
Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation
Learning sketching matrices for fast and accurate low-rank approximation...
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06/13/2022
Lazy and Fast Greedy MAP Inference for Determinantal Point Process
The maximum a posteriori (MAP) inference for determinantal point process...
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05/20/2022
Sample Complexity of Learning Heuristic Functions for Greedy-Best-First and A* Search
Greedy best-first search (GBFS) and A* search (A*) are popular algorithm...
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05/20/2022
Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictions
Augmenting algorithms with learned predictions is a promising approach f...
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04/06/2022
Nearly Tight Spectral Sparsification of Directed Hypergraphs by a Simple Iterative Sampling Algorithm
Spectral hypergraph sparsification, which is an attempt to extend well-k...
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12/12/2021
Algorithmic Bayesian persuasion with combinatorial actions
Bayesian persuasion is a model for understanding strategic information r...
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10/05/2021
Differentiable Equilibrium Computation with Decision Diagrams for Stackelberg Models of Combinatorial Congestion Games
We address Stackelberg models of combinatorial congestion games (CCGs); ...
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05/06/2020
Differentiable Greedy Submodular Maximization: Guarantees, Gradient Estimators, and Applications
We consider making outputs of the greedy algorithm for monotone submodul...
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05/06/2020
Differentiable Greedy Submodular Maximization with Guarantees and Gradient Estimators
We consider making outputs of the greedy algorithm for monotone submodul...
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02/17/2020
Learning Individually Fair Classifier with Causal-Effect Constraint
Machine learning is increasingly being used in various applications that...
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10/03/2019
Best-first Search Algorithm for Non-convex Sparse Minimization
Non-convex sparse minimization (NSM), or â„“_0-constrained minimization of...
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08/17/2019
Guarantees of Stochastic Greedy Algorithms for Non-monotone Submodular Maximization with Cardinality Constraint
Submodular maximization with a cardinality constraint can model various ...
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08/17/2019
Approximation Guarantees of Stochastic Greedy Algorithms for Non-monotone Submodular Maximization with a Size Constraint
The stochastic greedy algorithm (SG) is a randomized version of the gree...
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04/24/2019
Beyond Adaptive Submodularity: Approximation Guarantees of Greedy Policy with Adaptive Submodularity Ratio
We propose a new concept named adaptive submodularity ratio to study the...
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05/29/2018
