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

1

2

6

6

5

16

67

72

80

102

133

171

219

398

425

440

487

649

812

1,162

1,353

1,487

1,474

1,600

1,870

1,441

372

2000

'5

'10

'15

'20

'25

Papers (including subtopics)

Scalable Inference on Kingman’s Coalescent using Pair Similarity AISTATS 2012 Scalable nonconvex inexact proximal splitting NeurIPS 2012 Scaled Gradients on Grassmann Manifolds for Matrix Completion NeurIPS 2012 Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization NeurIPS 2012 Selecting Diverse Features via Spectral Regularization NeurIPS 2012 Smoothing Multivariate Performance Measures JMLR 2012 Smooth-projected Neighborhood Pursuit for High-dimensional Nonparanormal Graph Estimation NeurIPS 2012 Sparse and Unique Nonnegative Matrix Factorization Through Data Preprocessing JMLR 2012 Sparse Approximate Manifolds for Differential Geometric MCMC NeurIPS 2012 Sparse Prediction with the k-Support Norm NeurIPS 2012 Spectral Learning of General Weighted Automata via Constrained Matrix Completion NeurIPS 2012 Stochastic Bandit Based on Empirical Moments AISTATS 2012 Stochastic Gradient Descent with Only One Projection NeurIPS 2012 Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions NeurIPS 2012 Structured Learning of Gaussian Graphical Models NeurIPS 2012 Structured Sparse Canonical Correlation Analysis AISTATS 2012 Structured Sparsity via Alternating Direction Methods JMLR 2012 Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses NeurIPS 2012 Submodular-Bregman and the Lovász-Bregman Divergences with Applications NeurIPS 2012 Symbolic Dynamic Programming for Continuous State and Observation POMDPs NeurIPS 2012 Tensor Decomposition for Fast Parsing with Latent-Variable PCFGs NeurIPS 2012 The Bethe Partition Function of Log-supermodular Graphical Models NeurIPS 2012 The Lovász ϑ function, SVMs and finding large dense subgraphs NeurIPS 2012 The representer theorem for Hilbert spaces: a necessary and sufficient condition NeurIPS 2012 There’s a Hole in My Data Space: Piecewise Predictors for Heterogeneous Learning Problems AISTATS 2012