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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

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

Training Variational Autoencoders with Buffered Stochastic Variational Inference AISTATS 2019 Trajectory Optimization for Cable-Driven Soft Robot Locomotion RSS 2019 Trajectory Optimization on Manifolds: A Theoretically-Guaranteed Embedded Sequential Convex Programming Approach RSS 2019 Trajectory-wise Control Variates for Variance Reduction in Policy Gradient Methods CoRL 2019 Transductive Auxiliary Task Self-Training for Neural Multi-Task Models EMNLP 2019 Transductive Bounds for the Multi-Class Majority Vote Classifier AAAI 2019 Transferability and Hardness of Supervised Classification Tasks ICCV 2019 Transferable AutoML by Model Sharing Over Grouped Datasets CVPR 2019 Transfer Learning via Minimizing the Performance Gap Between Domains NeurIPS 2019 Transfer of Samples in Policy Search via Multiple Importance Sampling ICML 2019 Transformer-based Automatic Post-Editing Model with Joint Encoder and Multi-source Attention of Decoder ACL 2019 Transforming Underwriting in the Life Insurance Industry AAAI 2019 Transport Analysis of Infinitely Deep Neural Network JMLR 2019 Trend-Aware Tensor Factorization for Job Skill Demand Analysis IJCAI 2019 Triad Constraints for Learning Causal Structure of Latent Variables NeurIPS 2019 Trimming the ℓ_1 Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning ICML 2019 Trivializations for Gradient-Based Optimization on Manifolds NeurIPS 2019 Truncated Back-propagation for Bilevel Optimization AISTATS 2019 Trust Dynamics and Transfer across Human-Robot Interaction Tasks: Bayesian and Neural Computational Models IJCAI 2019 Trust Region Based Adversarial Attack on Neural Networks CVPR 2019 Trust Region Evolution Strategies AAAI 2019 Trust Region Sequential Variational Inference ACML 2019 Tunability: Importance of Hyperparameters of Machine Learning Algorithms JMLR 2019 Turbo Autoencoder: Deep learning based channel codes for point-to-point communication channels NeurIPS 2019 Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets JMLR 2019