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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)

Binary Rating Estimation with Graph Side Information NeurIPS 2018 Black Box FDR ICML 2018 Black-Box Reductions for Parameter-free Online Learning in Banach Spaces COLT 2018 Black-Box Variational Inference for Stochastic Differential Equations ICML 2018 BLEU is Not Suitable for the Evaluation of Text Simplification EMNLP 2018 Blind Deconvolutional Phase Retrieval via Convex Programming NeurIPS 2018 BML: A High-performance, Low-cost Gradient Synchronization Algorithm for DML Training NeurIPS 2018 BOCK : Bayesian Optimization with Cylindrical Kernels ICML 2018 BOHB: Robust and Efficient Hyperparameter Optimization at Scale ICML 2018 Boolean Decision Rules via Column Generation NeurIPS 2018 Boosting Adversarial Attacks With Momentum CVPR 2018 Boosting Black Box Variational Inference NeurIPS 2018 Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions ICLR 2018 Boosting Dynamic Programming with Neural Networks for Solving NP-hard Problems ACML 2018 Boosting the Actor with Dual Critic ICLR 2018 Boosting Variational Inference: an Optimization Perspective AISTATS 2018 Bootstrapping EM via Power EM and Convergence in the Naive Bayes Model AISTATS 2018 Bounding and Counting Linear Regions of Deep Neural Networks ICML 2018 Bounds on the Approximation Power of Feedforward Neural Networks ICML 2018 BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning CVPR 2018 Brain-inspired Balanced Tuning for Spiking Neural Networks IJCAI 2018 BrainT at IEST 2018: Fine-tuning Multiclass Perceptron For Implicit Emotion Classification EMNLP 2018 Breaking the 1/√n Barrier: Faster Rates for Permutation-based Models in Polynomial Time COLT 2018 Breaking the Activation Function Bottleneck through Adaptive Parameterization NeurIPS 2018 Breaking the Beam Search Curse: A Study of (Re-)Scoring Methods and Stopping Criteria for Neural Machine Translation EMNLP 2018