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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)

Tracking the Evolution of Customer Purchase Behavior Segmentation via a Fragmentation-Coagulation Process IJCAI 2017 Tractability in Structured Probability Spaces NeurIPS 2017 Trainable Greedy Decoding for Neural Machine Translation EMNLP 2017 Training Deep Networks without Learning Rates Through Coin Betting NeurIPS 2017 Training Quantized Nets: A Deeper Understanding NeurIPS 2017 Training Word Sense Embeddings With Lexicon-based Regularization IJCNLP 2017 Train longer, generalize better: closing the generalization gap in large batch training of neural networks NeurIPS 2017 Translation Synchronization via Truncated Least Squares NeurIPS 2017 Trimmed Density Ratio Estimation NeurIPS 2017 Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs ICML 2017 Tux²: Distributed Graph Computation for Machine Learning NSDI 2017 Two New Approaches to Compressed Sensing Exhibiting Both Robust Sparse Recovery and the Grouping Effect JMLR 2017 Unbiased estimates for linear regression via volume sampling NeurIPS 2017 Uncertainty Decoding with Adaptive Sampling for Noise Robust DNN-Based Acoustic Modeling Interspeech 2017 Uncorrelation and Evenness: a New Diversity-Promoting Regularizer ICML 2017 Uncovering Causality from Multivariate Hawkes Integrated Cumulants ICML 2017 Understanding Black-box Predictions via Influence Functions ICML 2017 Understanding Synthetic Gradients and Decoupled Neural Interfaces ICML 2017 Understanding the Representation and Computation of Multilayer Perceptrons: A Case Study in Speech Recognition ICML 2017 Understanding Traffic Density From Large-Scale Web Camera Data CVPR 2017 Uniform Convergence Rates for Kernel Density Estimation ICML 2017 Uniform Deviation Bounds for k-Means Clustering ICML 2017 Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning NeurIPS 2017 Unifying Task Specification in Reinforcement Learning ICML 2017 Unit Selection with Hierarchical Cascaded Long Short Term Memory Bidirectional Recurrent Neural Nets Interspeech 2017