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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)

How to Train Your Deep Multi-Object Tracker CVPR 2020 How to Trap a Gradient Flow COLT 2020 How Useful Is Self-Supervised Pretraining for Visual Tasks? CVPR 2020 HRank: Filter Pruning Using High-Rank Feature Map CVPR 2020 HS-CAI: A Hybrid DCOP Algorithm via Combining Search with Context-Based Inference AAAI 2020 Human Gaze Assisted Artificial Intelligence: A Review IJCAI 2020 Humans Meet Models on Object Naming: A New Dataset and Analysis COLING 2020 Hybrid Stochastic-Deterministic Minibatch Proximal Gradient: Less-Than-Single-Pass Optimization with Nearly Optimal Generalization ICML 2020 Hybrid Variance-Reduced SGD Algorithms For Minimax Problems with Nonconvex-Linear Function NeurIPS 2020 Hyperbolic Interaction Model for Hierarchical Multi-Label Classification AAAI 2020 Hypermodels for Exploration ICLR 2020 Hypernymy Detection for Low-Resource Languages via Meta Learning ACL 2020 Hyperparameter Ensembles for Robustness and Uncertainty Quantification NeurIPS 2020 Hypersolvers: Toward Fast Continuous-Depth Models NeurIPS 2020 HyperSTAR: Task-Aware Hyperparameters for Deep Networks CVPR 2020 Hypothesis Sketching for Online Kernel Selection in Continuous Kernel Space IJCAI 2020 Hypothesis Testing Interpretations and Renyi Differential Privacy AISTATS 2020 I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations IJCAI 2020 I Am Going MAD: Maximum Discrepancy Competition for Comparing Classifiers Adaptively ICLR 2020 ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA NeurIPS 2020 ID3 Learns Juntas for Smoothed Product Distributions COLT 2020 IDEAL: Inexact DEcentralized Accelerated Augmented Lagrangian Method NeurIPS 2020 Identifiability and Consistency of Bayesian Network Structure Learning from Incomplete Data PGM 2020 Identifiability and Consistent Estimation of Nonparametric Translation Hidden Markov Models with General State Space JMLR 2020 Identifying Learning Rules From Neural Network Observables NeurIPS 2020