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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)

Universality of Computational Lower Bounds for Submatrix Detection COLT 2019 Universally Slimmable Networks and Improved Training Techniques ICCV 2019 Universal Stagewise Learning for Non-Convex Problems with Convergence on Averaged Solutions ICLR 2019 Universal Statistics of Fisher Information in Deep Neural Networks: Mean Field Approach AISTATS 2019 UniXGrad: A Universal, Adaptive Algorithm with Optimal Guarantees for Constrained Optimization NeurIPS 2019 Unreproducible Research is Reproducible ICML 2019 Unsupervised Alignment of Embeddings with Wasserstein Procrustes AISTATS 2019 Unsupervised Dialog Structure Learning NAACL 2019 Unsupervised Domain Adaptation Based on Source-Guided Discrepancy AAAI 2019 Unsupervised Evaluation Metrics and Learning Criteria for Non-Parallel Textual Transfer EMNLP 2019 Unsupervised Feature Selection by Pareto Optimization AAAI 2019 Unsupervised Image Matching and Object Discovery as Optimization CVPR 2019 Unsupervised Learning of Scene Flow Estimation Fusing with Local Rigidity IJCAI 2019 Unsupervised Primitive Discovery for Improved 3D Generative Modeling CVPR 2019 Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach CVPR 2019 Untangling in Invariant Speech Recognition NeurIPS 2019 Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input NeurIPS 2019 User-Specified Local Differential Privacy in Unconstrained Adaptive Online Learning NeurIPS 2019 Using Benson’s Algorithm for Regularization Parameter Tracking AAAI 2019 Using Contextual Information to Improve Blood Glucose Prediction MLHC 2019 Using Domain Knowledge to Overcome Latent Variables in Causal Inference from Time Series MLHC 2019 Using Large Corpus N-gram Statistics to Improve Recurrent Neural Language Models NAACL 2019 Using Simulation to Improve Sample-Efficiency of Bayesian Optimization for Bipedal Robots JMLR 2019 Using Statistics to Automate Stochastic Optimization NeurIPS 2019 VAE-Based Regularization for Deep Speaker Embedding Interspeech 2019