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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)

Symplectic Recurrent Neural Networks ICLR 2020 Syn2Real Transfer Learning for Image Deraining Using Gaussian Processes CVPR 2020 Synchronizing Probability Measures on Rotations via Optimal Transport CVPR 2020 Synchronous Double-channel Recurrent Network for Aspect-Opinion Pair Extraction ACL 2020 Syntactic Search by Example ACL 2020 Synthesize, Execute and Debug: Learning to Repair for Neural Program Synthesis NeurIPS 2020 Synthesizing strategies under expected and exceptional environment behaviors IJCAI 2020 Synthetic Data Generators -- Sequential and Private NeurIPS 2020 Synthetic Learning: Learn From Distributed Asynchronized Discriminator GAN Without Sharing Medical Image Data CVPR 2020 System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina NeurIPS 2020 System Identification with Time-Aware Neural Sequence Models AAAI 2020 Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization NeurIPS 2020 TACRED Revisited: A Thorough Evaluation of the TACRED Relation Extraction Task ACL 2020 Tails of Lipschitz Triangular Flows ICML 2020 Taking a hint: How to leverage loss predictors in contextual bandits? COLT 2020 Taming Discrete Integration via the Boon of Dimensionality NeurIPS 2020 Tandem Inference: An Out-of-Core Streaming Algorithm for Very Large-Scale Relational Inference AAAI 2020 Tangled up in BLEU: Reevaluating the Evaluation of Automatic Machine Translation Evaluation Metrics ACL 2020 Target–Aware Bayesian Inference: How to Beat Optimal Conventional Estimators JMLR 2020 Target-Embedding Autoencoders for Supervised Representation Learning ICLR 2020 Target Propagation in Recurrent Neural Networks JMLR 2020 Task Agnostic Robust Learning on Corrupt Outputs by Correlation-Guided Mixture Density Networks CVPR 2020 Task-Level Curriculum Learning for Non-Autoregressive Neural Machine Translation IJCAI 2020 Task-Oriented Active Perception and Planning in Environments with Partially Known Semantics ICML 2020 Task-Robust Model-Agnostic Meta-Learning NeurIPS 2020