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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)

Deep Activation Mixture Model for Speech Recognition Interspeech 2017 Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability ICML 2017 Deep Forest: Towards An Alternative to Deep Neural Networks IJCAI 2017 Deep Generative Models for Relational Data with Side Information ICML 2017 Deep IV: A Flexible Approach for Counterfactual Prediction ICML 2017 Deep Kernels for Optimizing Locomotion Controllers CoRL 2017 Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC ICML 2017 Deeply Aggregated Alternating Minimization for Image Restoration CVPR 2017 Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction ICML 2017 Deep Mean-Shift Priors for Image Restoration NeurIPS 2017 Deep Network Flow for Multi-Object Tracking CVPR 2017 Deep Neural Machine Translation with Linear Associative Unit ACL 2017 Deep Neural Solver for Math Word Problems EMNLP 2017 Deep Roots: Improving CNN Efficiency With Hierarchical Filter Groups CVPR 2017 Delta Networks for Optimized Recurrent Network Computation ICML 2017 Denoising Recurrent Neural Network for Deep Bidirectional LSTM Based Voice Conversion Interspeech 2017 Dense Distributions from Sparse Samples: Improved Gibbs Sampling Parameter Estimators for LDA JMLR 2017 Density Estimation in Infinite Dimensional Exponential Families JMLR 2017 Depth Separation for Neural Networks COLT 2017 Depth-Width Tradeoffs in Approximating Natural Functions with Neural Networks ICML 2017 Deriving Consensus for Multi-Parallel Corpora: an English Bible Study IJCNLP 2017 Detecting Dependencies in Sparse, Multivariate Databases Using Probabilistic Programming and Non-parametric Bayes AISTATS 2017 Determining Semantic Textual Similarity using Natural Deduction Proofs EMNLP 2017 Device Placement Optimization with Reinforcement Learning ICML 2017 Diachrony-aware Induction of Binary Latent Representations from Typological Features IJCNLP 2017