conftrace_

Optimization

14,850 papers (55 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Continuous Optimization (4,424) Stochastic Methods (2,991) Combinatorial Optimization (2,615) Online Algorithms (2,404) Optimization (1,521) Game Theory (1,046) Convex Optimization (864) Discrete Optimization (721) Optimal Transport (474) Sparse Optimization (416) Optimal Control (271) Global Optimization (200) Non-Convex Optimization (182) Distributed Learning (164) Approximation Algorithms (162) Multi-Objective Optimization (151) Distributed Optimization (136) Bayesian Optimization (132) Theory (109) Compressed Sensing (102) Algorithms (89) Robust Optimization (86) Submodular Optimization (77) Kernel Methods (75) Evolutionary Algorithm (72) Linear Programming (54) Tensor Decomposition (48) Bilevel Optimization (42) Integer Programming (38) Matrix Completion (33) Algorithm (21) Regularization (11)

Papers per year

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102

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Papers (including subtopics)

Exploiting Covariate Similarity in Sparse Regression via the Pairwise Elastic Net AISTATS 2010 Extensions of Generalized Binary Search to Group Identification and Exponential Costs NeurIPS 2010 Fast detection of multiple change-points shared by many signals using group LARS NeurIPS 2010 Fast global convergence rates of gradient methods for high-dimensional statistical recovery NeurIPS 2010 Generalized Power Method for Sparse Principal Component Analysis JMLR 2010 Generalized roof duality and bisubmodular functions NeurIPS 2010 Group Sparse Coding with a Laplacian Scale Mixture Prior NeurIPS 2010 Guaranteed Rank Minimization via Singular Value Projection NeurIPS 2010 Guarantees for Approximate Incremental SVMs AISTATS 2010 Hierarchical Convex NMF for Clustering Massive Data ACML 2010 High Dimensional Inverse Covariance Matrix Estimation via Linear Programming JMLR 2010 High-dimensional Variable Selection with Sparse Random Projections: Measurement Sparsity and Statistical Efficiency JMLR 2010 Importance Sampling for Continuous Time Bayesian Networks JMLR 2010 Improving the Asymptotic Performance of Markov Chain Monte-Carlo by Inserting Vortices NeurIPS 2010 Incremental Sampling-based Algorithms for Optimal Motion Planning RSS 2010 Incremental Sparsification for Real-time Online Model Learning AISTATS 2010 Individualized ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles NeurIPS 2010 Iterative Scaling and Coordinate Descent Methods for Maximum Entropy Models JMLR 2010 Kernel Partial Least Squares is Universally Consistent AISTATS 2010 Kronecker Graphs: An Approach to Modeling Networks JMLR 2010 Large-Scale Matrix Factorization with Missing Data under Additional Constraints NeurIPS 2010 Learning Bayesian Network Structure using LP Relaxations AISTATS 2010 Learning Causal Structure from Overlapping Variable Sets AISTATS 2010 Learning Multiple Tasks with a Sparse Matrix-Normal Penalty NeurIPS 2010 Learning Networks of Stochastic Differential Equations NeurIPS 2010