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Optimization

14,983 papers

Papers per year

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Papers

Nyström Approximation for Large-Scale Determinantal Processes AISTATS 2013
Convex Collective Matrix Factorization AISTATS 2013
Why Steiner-tree type algorithms work for community detection AISTATS 2013
DivMCuts: Faster Training of Structural SVMs with Diverse M-Best Cutting-Planes AISTATS 2013
A Parallel, Block Greedy Method for Sparse Inverse Covariance Estimation for Ultra-high Dimensions AISTATS 2013
Structure Learning of Mixed Graphical Models AISTATS 2013
Learning Markov Networks With Arithmetic Circuits AISTATS 2013
A Last-Step Regression Algorithm for Non-Stationary Online Learning AISTATS 2013
High-dimensional Inference via Lipschitz Sparsity-Yielding Regularizers AISTATS 2013
Random Projections for Support Vector Machines AISTATS 2013
Bethe Bounds and Approximating the Global Optimum AISTATS 2013
Dual Decomposition for Joint Discrete-Continuous Optimization AISTATS 2013
Learning Social Infectivity in Sparse Low-rank Networks Using Multi-dimensional Hawkes Processes AISTATS 2013
Scoring anomalies: a M-estimation formulation AISTATS 2013
Open Problem: Fast Stochastic Exp-Concave Optimization COLT 2013
On the Complexity of Bandit and Derivative-Free Stochastic Convex Optimization COLT 2013
Estimation of Extreme Values and Associated Level Sets of a Regression Function via Selective Sampling COLT 2013
Recovering the Optimal Solution by Dual Random Projection COLT 2013
Online Learning for Time Series Prediction COLT 2013
Beating Bandits in Gradually Evolving Worlds COLT 2013
Passive Learning with Target Risk COLT 2013
Algorithms and Hardness for Robust Subspace Recovery COLT 2013
Subspace Embeddings and \ell_p-Regression Using Exponential Random Variables COLT 2013
Divide and Conquer Kernel Ridge Regression COLT 2013
A Tale of Two Metrics: Simultaneous Bounds on Competitiveness and Regret COLT 2013