Approximation Algorithms

Randomized Strategies for Robust Combinatorial Optimization AAAI 2019 Towards a Zero-One Law for Column Subset Selection NeurIPS 2019 Using Benson’s Algorithm for Regularization Parameter Tracking AAAI 2019 A Faster Sampling Algorithm for Spherical k-means ACML 2018 Approximating the maximum weighted decomposable graph problem with applications to probabilistic graphical models PGM 2018 Approximation algorithms for stochastic clustering NeurIPS 2018 Boosting Dynamic Programming with Neural Networks for Solving NP-hard Problems ACML 2018 Distributed k-Clustering for Data with Heavy Noise NeurIPS 2018 Hierarchical Clustering with Structural Constraints ICML 2018 Non-monotone Submodular Maximization in Exponentially Fewer Iterations NeurIPS 2018 Norm-Ranging LSH for Maximum Inner Product Search NeurIPS 2018 Online Improper Learning with an Approximation Oracle NeurIPS 2018 Optimal Algorithms for Continuous Non-monotone Submodular and DR-Submodular Maximization NeurIPS 2018 Optimization for Approximate Submodularity NeurIPS 2018 Robust Subspace Approximation in a Stream NeurIPS 2018 Approximation Algorithms for ℓ_0-Low Rank Approximation NeurIPS 2017 Beyond Worst-case: A Probabilistic Analysis of Affine Policies in Dynamic Optimization NeurIPS 2017 Efficient Approximation Algorithms for Strings Kernel Based Sequence Classification NeurIPS 2017 Gaussian Quadrature for Kernel Features NeurIPS 2017 Recursive Sampling for the Nystrom Method NeurIPS 2017 The Importance of Communities for Learning to Influence NeurIPS 2017 A Constant-Factor Bi-Criteria Approximation Guarantee for k-means++ NeurIPS 2016 Approximate maximum entropy principles via Goemans-Williamson with applications to provable variational methods NeurIPS 2016 Hierarchical Clustering via Spreading Metrics NeurIPS 2016 Maximization of Approximately Submodular Functions NeurIPS 2016