Publications associées à Augmented Lagrangian Methods for Provable and Scalable Machine Learning

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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

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Graph Chatbot

Chattez avec Graph Search

Demand-based discrete optimization

Multiple Query Optimization on the D-Wave 2X Adiabatic Quantum Computer

Stochastic Three-Composite Convex Minimization

Time-Optimal Path-Following Operation in the Presence of Uncertainty

Clustering of heterogeneous networks with directional flows based on “Snake” similarities

Mumford-Shah and Potts Regularization for Manifold-Valued Data

MATHICSE Technical Report : A fast gradient method for nonnegative sparse regression with self dictionary

Scampi: a robust approximate message-passing framework for compressive imaging

Subspace Acceleration For Large-Scale Parameter-Dependent Hermitian Eigenproblems

Fast K-Means with Accurate Bounds

Mumford-Shah and Potts Regularization for Manifold-Valued Data

Time-Optimal Path-Following Operation in the Presence of Uncertainty

Clustering of heterogeneous networks with directional flows based on “Snake” similarities

Scampi: a robust approximate message-passing framework for compressive imaging

Subspace Acceleration For Large-Scale Parameter-Dependent Hermitian Eigenproblems

Multiple Query Optimization on the D-Wave 2X Adiabatic Quantum Computer

Demand-based discrete optimization

Stochastic Three-Composite Convex Minimization

Fast K-Means with Accurate Bounds

MATHICSE Technical Report : A fast gradient method for nonnegative sparse regression with self dictionary