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Optimization

12,959 papers (55 classified directly here)

Subtopics

Continuous Optimization (3,907) Stochastic Methods (2,788) Combinatorial Optimization (2,409) Online Algorithms (2,192) Optimization (1,207) Game Theory (944) Discrete Optimization (705) Convex Optimization (591) Optimal Transport (369) Sparse Optimization (347) Optimal Control (225) Global Optimization (190) Distributed Learning (157) Multi-Objective Optimization (125) Approximation Algorithms (110) Bayesian Optimization (100) Distributed Optimization (99) Theory (98) Non-Convex Optimization (76) Kernel Methods (73) Compressed Sensing (72) Robust Optimization (70) Evolutionary Algorithm (58) Linear Programming (43) Algorithms (10) Algorithm (10) Integer Programming (9) Submodular Optimization (9) Matrix Completion (8) Bilevel Optimization (8) Tensor Decomposition (6) Regularization (5)

Papers per year

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Papers (including subtopics)

Batch Bayesian Optimization via Local Penalization AISTATS 2016
Nonparametric Budgeted Stochastic Gradient Descent AISTATS 2016
Approximate Inference Using DC Programming For Collective Graphical Models AISTATS 2016
Variational Tempering AISTATS 2016
A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models AISTATS 2016
Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with Ordered L1-Norm AISTATS 2016
(Bandit) Convex Optimization with Biased Noisy Gradient Oracles AISTATS 2016
Accelerating Online Convex Optimization via Adaptive Prediction AISTATS 2016
High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models AISTATS 2016
On the Use of Non-Stationary Strategies for Solving Two-Player Zero-Sum Markov Games AISTATS 2016
Pseudo-Marginal Slice Sampling AISTATS 2016
Pareto Front Identification from Stochastic Bandit Feedback AISTATS 2016
AdaDelay: Delay Adaptive Distributed Stochastic Optimization AISTATS 2016
Improved Learning Complexity in Combinatorial Pure Exploration Bandits AISTATS 2016
Optimization as Estimation with Gaussian Processes in Bandit Settings AISTATS 2016
Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization AISTATS 2016
Fitting Spectral Decay with the k-Support Norm AISTATS 2016
Determinantal Regularization for Ensemble Variable Selection AISTATS 2016
Scalable and Sound Low-Rank Tensor Learning AISTATS 2016
Consistently Estimating Markov Chains with Noisy Aggregate Data AISTATS 2016
Unwrapping ADMM: Efficient Distributed Computing via Transpose Reduction AISTATS 2016
Efficient Bregman Projections onto the Permutahedron and Related Polytopes AISTATS 2016
Provable Tensor Methods for Learning Mixtures of Generalized Linear Models AISTATS 2016
Scalable Exemplar Clustering and Facility Location via Augmented Block Coordinate Descent with Column Generation AISTATS 2016
On Lloyd’s Algorithm: New Theoretical Insights for Clustering in Practice AISTATS 2016