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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)

Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers ICLR 2019 Bias Reduction via End-to-End Shift Learning: Application to Citizen Science AAAI 2019 Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions AAAI 2019 Bi-Directional Differentiable Input Reconstruction for Low-Resource Neural Machine Translation NAACL 2019 Big Generalizations with Small Data: Exploring the Role of Training Samples in Learning Adjectives of Size EMNLP 2019 Bilinear Bandits with Low-rank Structure ICML 2019 Binarsity: a penalization for one-hot encoded features in linear supervised learning JMLR 2019 Binary Space Partitioning Forest AISTATS 2019 Biologically-Plausible Learning Algorithms Can Scale to Large Datasets ICLR 2019 BioNLP-OST 2019 RDoC Tasks: Multi-grain Neural Relevance Ranking Using Topics and Attention Based Query-Document-Sentence Interactions EMNLP 2019 BIRD: Engineering an Efficient CNF-XOR SAT Solver and Its Applications to Approximate Model Counting AAAI 2019 Bit-Flip Attack: Crushing Neural Network With Progressive Bit Search ICCV 2019 Black Box Quantiles for Kernel Learning AISTATS 2019 BLAS-on-flash: An Efficient Alternative for Large Scale ML Training and Inference? NSDI 2019 Blended Matching Pursuit NeurIPS 2019 Blind Demixing via Wirtinger Flow with Random Initialization AISTATS 2019 Blind Image Deblurring With Local Maximum Gradient Prior CVPR 2019 Block Belief Propagation for Parameter Learning in Markov Random Fields AAAI 2019 Block Coordinate Regularization by Denoising NeurIPS 2019 Block Stability for MAP Inference AISTATS 2019 BN-invariant Sharpness Regularizes the Training Model to Better Generalization IJCAI 2019 Boosted Kernel Ridge Regression: Optimal Learning Rates and Early Stopping JMLR 2019 Boosting Robustness Certification of Neural Networks ICLR 2019 Bootstrapping Upper Confidence Bound NeurIPS 2019 Bottleneck Potentials in Markov Random Fields ICCV 2019