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Fast K-Means with Accurate Bounds

François Fleuret, James Peter Newling

We propose a novel accelerated exact

k

-means algorithm, which outperforms the current state-of-the-art low-dimensional algorithm in 18 of 22 experiments, running up to 3

\times

faster. We also propose a general improvement of existing state-of-the-art a ...

Idiap2016

Scalable Stochastic Optimization: Scenario Reduction with Guarantees

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Satisficing measure approach for vehicle routing problem with time windows under uncertainty

What Players do with the Ball: A Physically Constrained Interaction Modeling

Fast K-Means with Accurate Bounds

Distributionally Robust Multi-Item Newsvendor Problems with Multimodal Demand Distributions

Distributionally Robust Logistic Regression

Optimum Biorefinery Pathways Selection Using the Integer-Cuts Constraint Method Applied to a MILP Problem

A two-stage stochastic programming approach to employee scheduling in retail outlets with uncertain demand

Upper bounds for the reach-avoid probability via robust optimization

A Universal Primal-Dual Convex Optimization Framework

A Distributionally Robust Perspective on Uncertainty Quantification and Chance Constrained Programming

Fast K-Means with Accurate Bounds

Satisficing measure approach for vehicle routing problem with time windows under uncertainty

A Distributionally Robust Perspective on Uncertainty Quantification and Chance Constrained Programming

What Players do with the Ball: A Physically Constrained Interaction Modeling

Distributionally Robust Logistic Regression

A two-stage stochastic programming approach to employee scheduling in retail outlets with uncertain demand

A Universal Primal-Dual Convex Optimization Framework

Upper bounds for the reach-avoid probability via robust optimization

Optimum Biorefinery Pathways Selection Using the Integer-Cuts Constraint Method Applied to a MILP Problem

Distributionally Robust Multi-Item Newsvendor Problems with Multimodal Demand Distributions