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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)

Joint Learning of Brain Lesion and Anatomy Segmentation from Heterogeneous Datasets MIDL 2019 Jointly Learning Semantic Parser and Natural Language Generator via Dual Information Maximization ACL 2019 Jointly Measuring Diversity and Quality in Text Generation Models NAACL 2019 Jointly Optimizing Diversity and Relevance in Neural Response Generation NAACL 2019 Joint Manifold Diffusion for Combining Predictions on Decoupled Observations CVPR 2019 Joint Nonparametric Precision Matrix Estimation with Confounding UAI 2019 Joint Optimization for Cooperative Image Captioning ICCV 2019 Joint Semi-Supervised Feature Selection and Classification through Bayesian Approach AAAI 2019 JPEG Artifacts Reduction via Deep Convolutional Sparse Coding ICCV 2019 Judge the Judges: A Large-Scale Evaluation Study of Neural Language Models for Online Review Generation EMNLP 2019 Jumping Manifolds: Geometry Aware Dense Non-Rigid Structure From Motion CVPR 2019 Jumpout : Improved Dropout for Deep Neural Networks with ReLUs ICML 2019 Kalman Filter, Sensor Fusion, and Constrained Regression: Equivalences and Insights NeurIPS 2019 Katalyst: Boosting Convex Katayusha for Non-Convex Problems with a Large Condition Number ICML 2019 K-Best Transformation Synchronization ICCV 2019 KCNN: Kernel-wise Quantization to Remarkably Decrease Multiplications in Convolutional Neural Network IJCAI 2019 Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods NeurIPS 2019 Kernel-Based Reinforcement Learning in Robust Markov Decision Processes ICML 2019 Kernel Change-point Detection with Auxiliary Deep Generative Models ICLR 2019 Kernel Exponential Family Estimation via Doubly Dual Embedding AISTATS 2019 Kernelized Bayesian Softmax for Text Generation NeurIPS 2019 Kernel quadrature with DPPs NeurIPS 2019 Kernel RNN Learning (KeRNL) ICLR 2019 Kernels for Sequentially Ordered Data JMLR 2019 Kernel Stein Tests for Multiple Model Comparison NeurIPS 2019