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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)

RotDCF: Decomposition of Convolutional Filters for Rotation-Equivariant Deep Networks ICLR 2019 Rotting bandits are no harder than stochastic ones AISTATS 2019 RS3CIS: Robust Single-Step Spectral Clustering with Intrinsic Subspace AAAI 2019 RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets AAAI 2019 RSN: Randomized Subspace Newton NeurIPS 2019 RUDDER: Return Decomposition for Delayed Rewards NeurIPS 2019 Running Time Analysis of MOEA/D with Crossover on Discrete Optimization Problem AAAI 2019 Safe and Sample-Efficient Reinforcement Learning Algorithms for Factored Environments IJCAI 2019 Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning IJCAI 2019 Safe Convex Learning under Uncertain Constraints AISTATS 2019 Safe Exploration for Interactive Machine Learning NeurIPS 2019 Safe Grid Search with Optimal Complexity ICML 2019 Safeguarded Dynamic Label Regression for Noisy Supervision AAAI 2019 SAGA with Arbitrary Sampling ICML 2019 Saliency Learning: Teaching the Model Where to Pay Attention NAACL 2019 Sample Adaptive MCMC NeurIPS 2019 Sample Complexity of Learning Mixture of Sparse Linear Regressions NeurIPS 2019 Sample complexity of partition identification using multi-armed bandits COLT 2019 Sample Complexity of Sinkhorn Divergences AISTATS 2019 Sample Compression for Real-Valued Learners ALT 2019 Sampled Softmax with Random Fourier Features NeurIPS 2019 Sample Efficient Graph-Based Optimization with Noisy Observations AISTATS 2019 Sample-Optimal Parametric Q-Learning Using Linearly Additive Features ICML 2019 Sampling-Free Epistemic Uncertainty Estimation Using Approximated Variance Propagation ICCV 2019 Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation UAI 2019