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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)

Efficient Non-conjugate Gaussian Process Factor Models for Spike Count Data using Polynomial Approximations ICML 2020 Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees NeurIPS 2020 Efficient nonparametric statistical inference on population feature importance using Shapley values ICML 2020 Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient Descent NeurIPS 2020 Efficient Optimistic Exploration in Linear-Quadratic Regulators via Lagrangian Relaxation ICML 2020 Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning AISTATS 2020 Efficient Policy Learning from Surrogate-Loss Classification Reductions ICML 2020 Efficient Predictive Uncertainty Estimators for Deep Probabilistic Models AAAI 2020 Efficient Projection-free Algorithms for Saddle Point Problems NeurIPS 2020 Efficient Proximal Mapping of the 1-path-norm of Shallow Networks ICML 2020 Efficient Querying from Weighted Binary Codes AAAI 2020 Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley Transform ICLR 2020 Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More ICML 2020 Efficient Rollout Strategies for Bayesian Optimization UAI 2020 Efficient Spatial-Temporal Rebalancing of Shareable Bikes (Student Abstract) AAAI 2020 Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning EMNLP 2020 Efficient Variational Inference for Sparse Deep Learning with Theoretical Guarantee NeurIPS 2020 Efficient Verification of ReLU-Based Neural Networks via Dependency Analysis AAAI 2020 EiGLasso: Scalable Estimation of Cartesian Product of Sparse Inverse Covariance Matrices UAI 2020 Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits ICML 2020 Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks NeurIPS 2020 Eliminating the Invariance on the Loss Landscape of Linear Autoencoders ICML 2020 Elimination of All Bad Local Minima in Deep Learning AISTATS 2020 Embedding Dimension of Polyhedral Losses COLT 2020 Emergence of functional and structural properties of the head direction system by optimization of recurrent neural networks ICLR 2020