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Optimization & Theory

43,292 papers (3 classified directly here)

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

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

1
52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Fast and Concurrent RDF Queries with RDMA-Based Distributed Graph Exploration OSDI 2016 Fast and Scalable Structural SVM with Slack Rescaling AISTATS 2016 Fast Collaborative Filtering from Implicit Feedback with Provable Guarantees ACML 2016 Fast Collocation-Based Bayesian HMM Word Alignment COLING 2016 Fast ConvNets Using Group-Wise Brain Damage CVPR 2016 Fast Distributed Submodular Cover: Public-Private Data Summarization NeurIPS 2016 Fast DPP Sampling for Nystrom with Application to Kernel Methods ICML 2016 Faster Convex Optimization: Simulated Annealing with an Efficient Universal Barrier ICML 2016 Faster Projection-free Convex Optimization over the Spectrahedron NeurIPS 2016 Fast Inference for Interactive Models of Text COLING 2016 Fast learning rates with heavy-tailed losses NeurIPS 2016 Fast methods for estimating the Numerical rank of large matrices ICML 2016 Fast Parameter Inference in Nonlinear Dynamical Systems using Iterative Gradient Matching ICML 2016 Fast Rate Analysis of Some Stochastic Optimization Algorithms ICML 2016 Fast recovery from a union of subspaces NeurIPS 2016 Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with Ordered L1-Norm AISTATS 2016 Fast Stochastic Algorithms for SVD and PCA: Convergence Properties and Convexity ICML 2016 Fast ε-free Inference of Simulation Models with Bayesian Conditional Density Estimation NeurIPS 2016 Feature-distributed sparse regression: a screen-and-clean approach NeurIPS 2016 Feature-Level Domain Adaptation JMLR 2016 Finding significant combinations of features in the presence of categorical covariates NeurIPS 2016 Finite-Dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models NeurIPS 2016 Finite-Sample Analysis of Fixed-k Nearest Neighbor Density Functional Estimators NeurIPS 2016 Finite Sample Prediction and Recovery Bounds for Ordinal Embedding NeurIPS 2016 FireCaffe: Near-Linear Acceleration of Deep Neural Network Training on Compute Clusters CVPR 2016