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Optimization

14,850 papers (55 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Continuous Optimization (4,424) Stochastic Methods (2,991) Combinatorial Optimization (2,615) Online Algorithms (2,404) Optimization (1,521) Game Theory (1,046) Convex Optimization (864) Discrete Optimization (721) Optimal Transport (474) Sparse Optimization (416) Optimal Control (271) Global Optimization (200) Non-Convex Optimization (182) Distributed Learning (164) Approximation Algorithms (162) Multi-Objective Optimization (151) Distributed Optimization (136) Bayesian Optimization (132) Theory (109) Compressed Sensing (102) Algorithms (89) Robust Optimization (86) Submodular Optimization (77) Kernel Methods (75) Evolutionary Algorithm (72) Linear Programming (54) Tensor Decomposition (48) Bilevel Optimization (42) Integer Programming (38) Matrix Completion (33) Algorithm (21) Regularization (11)

Papers per year

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16
133
440
1,353
1,441
2000
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Papers (including subtopics)

Katalyst: Boosting Convex Katayusha for Non-Convex Problems with a Large Condition Number ICML 2019 K-Core Maximization: An Edge Addition Approach IJCAI 2019 KerGM: Kernelized Graph Matching NeurIPS 2019 Kernel Instrumental Variable Regression NeurIPS 2019 Kernel Learning for Data-Driven Spectral Analysis of Koopman Operators ACML 2019 Kernel quadrature with DPPs NeurIPS 2019 Kernel Truncated Randomized Ridge Regression: Optimal Rates and Low Noise Acceleration NeurIPS 2019 k-Means Clustering of Lines for Big Data NeurIPS 2019 KNG: The K-Norm Gradient Mechanism NeurIPS 2019 Knowledge Refinement via Rule Selection AAAI 2019 Large Scale Learning of Agent Rationality in Two-Player Zero-Sum Games AAAI 2019 Large-Scale, Metric Structure From Motion for Unordered Light Fields CVPR 2019 Large-scale optimal transport map estimation using projection pursuit NeurIPS 2019 Large-Scale Sparse Kernel Canonical Correlation Analysis ICML 2019 Lazifying Conditional Gradient Algorithms JMLR 2019 Leadership in Congestion Games: Multiple User Classes and Non-Singleton Actions IJCAI 2019 Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling ICML 2019 Learning Adaptive Random Features AAAI 2019 Learning and Data Selection in Big Datasets ICML 2019 Learning Dynamic Generator Model by Alternating Back-Propagation through Time AAAI 2019 Learning dynamic polynomial proofs NeurIPS 2019 Learning Embeddings into Entropic Wasserstein Spaces ICLR 2019 Learning Erdos-Renyi Random Graphs via Edge Detecting Queries NeurIPS 2019 Learning (from) Deep Hierarchical Structure among Features AAAI 2019 Learning from Delayed Outcomes via Proxies with Applications to Recommender Systems ICML 2019