conftrace_

approximation algorithm

630 papers

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Also known as

APPROX

Co-occurring keywords

combinatorial optimization (1039) submodular maximization (143) submodular optimization (261) k-means clustering (235) greedy algorithm (242) mechanism design (340) fair division (158) submodular function (121) hierarchical clustering (232) graph algorithm (178)

Papers

Robust Submodular Maximization: A Non-Uniform Partitioning Approach ICML 2017
Hierarchical Clustering via Spreading Metrics JMLR 2017
Order Statistics for Probabilistic Graphical Models IJCAI 2017
Inapproximability of VC Dimension and Littlestone’s Dimension COLT 2017
Computing an Approximately Optimal Agreeable Set of Items IJCAI 2017
Efficient Approximation Algorithms for Strings Kernel Based Sequence Classification NIPS 2017
Consistent k-Clustering ICML 2017
Pessimistic Leader-Follower Equilibria with Multiple Followers IJCAI 2017
Clustering High Dimensional Dynamic Data Streams ICML 2017
Sparse Approximate Conic Hulls NIPS 2017
Near-Optimal Design of Experiments via Regret Minimization ICML 2017
Robust Advertisement Allocation IJCAI 2017
Differentially Private Submodular Maximization: Data Summarization in Disguise ICML 2017
Influence Maximization with $\varepsilon$-Almost Submodular Threshold Functions NIPS 2017
Robust Optimization for Non-Convex Objectives NIPS 2017
Subset Selection under Noise NIPS 2017
Minimizing a Submodular Function from Samples NIPS 2017
Approximation Bounds for Hierarchical Clustering: Average Linkage, Bisecting K-means, and Local Search NIPS 2017
Maximization of Approximately Submodular Functions NIPS 2016
Distributed Submodular Maximization JMLR 2016
Solving Marginal MAP Problems with NP Oracles and Parity Constraints NIPS 2016
An Efficient Streaming Algorithm for the Submodular Cover Problem NIPS 2016
A Constant-Factor Bi-Criteria Approximation Guarantee for k-means++ NIPS 2016
Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures AISTATS 2016
Speeding up k-means by approximating Euclidean distances via block vectors ICML 2016