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Optimization

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Papers

Efficiency Through Procrastination: Approximately Optimal Algorithm Configuration with Runtime Guarantees IJCAI 2017
Constrained Bayesian Reinforcement Learning via Approximate Linear Programming IJCAI 2017
High Dimensional Bayesian Optimization using Dropout IJCAI 2017
Improving the Generalization Performance of Multi-class SVM via Angular Regularization IJCAI 2017
Online Robust Low-Rank Tensor Learning IJCAI 2017
Fast SVM Trained by Divide-and-Conquer Anchors IJCAI 2017
Sampling for Approximate Maximum Search in Factorized Tensor IJCAI 2017
Symmetric Non-negative Latent Factor Models for Undirected Large Networks IJCAI 2017
Count-Based Exploration in Feature Space for Reinforcement Learning IJCAI 2017
Logistic Markov Decision Processes IJCAI 2017
Rescale-Invariant SVM for Binary Classification IJCAI 2017
Thresholding Bandits with Augmented UCB IJCAI 2017
Large-scale Online Kernel Learning with Random Feature Reparameterization IJCAI 2017
Joint Capped Norms Minimization for Robust Matrix Recovery IJCAI 2017
Distributed Accelerated Proximal Coordinate Gradient Methods IJCAI 2017
Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization IJCAI 2017
Multiple Medoids based Multi-view Relational Fuzzy Clustering with Minimax Optimization IJCAI 2017
Dual Inference for Machine Learning IJCAI 2017
SVD-free Convex-Concave Approaches for Nuclear Norm Regularization IJCAI 2017
Incomplete Label Distribution Learning IJCAI 2017
Multiple Indefinite Kernel Learning for Feature Selection IJCAI 2017
Fast Stochastic Variance Reduced ADMM for Stochastic Composition Optimization IJCAI 2017
Adaptive Manifold Regularized Matrix Factorization for Data Clustering IJCAI 2017
Robust Regression via Heuristic Hard Thresholding IJCAI 2017
Weighted Double Q-learning IJCAI 2017