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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)

Distributed Batch Gaussian Process Optimization ICML 2017 Distributed Bayesian Learning with Stochastic Natural Gradient Expectation Propagation and the Posterior Server JMLR 2017 Distributed Learning with Regularized Least Squares JMLR 2017 Distributed Mean Estimation with Limited Communication ICML 2017 Distributed Semi-supervised Learning with Kernel Ridge Regression JMLR 2017 Distributed Sequence Memory of Multidimensional Inputs in Recurrent Networks JMLR 2017 Distributed Stochastic Variance Reduced Gradient Methods by Sampling Extra Data with Replacement JMLR 2017 Distributionally Robust Groupwise Regularization Estimator ACML 2017 Distributional Modeling on a Diet: One-shot Word Learning from Text Only IJCNLP 2017 Distribution of Gaussian Process Arc Lengths AISTATS 2017 Diverse Neural Network Learns True Target Functions AISTATS 2017 Diving into the shallows: a computational perspective on large-scale shallow learning NeurIPS 2017 Does Posh English Sound Attractive? Interspeech 2017 Domain Mismatch Modeling of Out-Domain i-Vectors for PLDA Speaker Verification Interspeech 2017 Dominance and Optimisation Based on Scale-Invariant Maximum Margin Preference Learning IJCAI 2017 Don’t Stop Me Now! Using Global Dynamic Oracles to Correct Training Biases of Transition-Based Dependency Parsers EACL 2017 Don’t understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures ACL 2017 DOPE: Distributed Optimization for Pairwise Energies CVPR 2017 Doubly Accelerated Methods for Faster CCA and Generalized Eigendecomposition ICML 2017 Doubly Accelerated Stochastic Variance Reduced Dual Averaging Method for Regularized Empirical Risk Minimization NeurIPS 2017 Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization ICML 2017 Doubly Stochastic Variational Inference for Deep Gaussian Processes NeurIPS 2017 DP-EM: Differentially Private Expectation Maximization AISTATS 2017 Dropout Inference in Bayesian Neural Networks with Alpha-divergences ICML 2017 DSAC - Differentiable RANSAC for Camera Localization CVPR 2017