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
1
2
6
6
5
16
67
72
80
102
133
171
219
398
425
440
487
649
812
1,162
1,353
1,487
1,474
1,600
1,870
1,441
372
2000
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Papers (including subtopics)
Runtime Analysis of Somatic Contiguous Hypermutation Operators in MOEA/D Framework
AAAI 2020
SAdam: A Variant of Adam for Strongly Convex Functions
ICLR 2020
Safe Linear Stochastic Bandits
AAAI 2020
Safe non-smooth black-box optimization with application to policy search
L4DC 2020
Safe Optimal Control Using Stochastic Barrier Functions and Deep Forward-Backward SDEs
CoRL 2020
Safe screening rules for L0-regression from Perspective Relaxations
ICML 2020
Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors
ICML 2020
Sample complexity bounds for localized sketching
AISTATS 2020
Sample Complexity of Kalman Filtering for Unknown Systems
L4DC 2020
Sample-Efficient Optimization in the Latent Space of Deep Generative Models via Weighted Retraining
NeurIPS 2020
Sampling from a k-DPP without looking at all items
NeurIPS 2020
Sampling Random Chordal Graphs by MCMC (Student Abstract)
AAAI 2020
Sampling Without Compromising Accuracy in Adaptive Data Analysis
ALT 2020
Scalable and Probabilistically Complete Planning for Robotic Spatial Extrusion
RSS 2020
Scalable Approximate MCMC Algorithms for the Horseshoe Prior
JMLR 2020
Scalable Bayesian Network Structure Learning via Maximum Acyclic Subgraph
PGM 2020
Scalable Calibration of Affinity Matrices from Incomplete Observations
ACML 2020
Scalable Nearest Neighbor Search for Optimal Transport
ICML 2020
Scalable Nonparametric Factorization for High-Order Interaction Events
AISTATS 2020
Scaling Hidden Markov Language Models
EMNLP 2020
Scaling Up AND/OR Abstraction Sampling
IJCAI 2020
Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing
ICML 2020
Schatten Norms in Matrix Streams: Hello Sparsity, Goodbye Dimension
ICML 2020
Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations
COLT 2020
Second Order Optimality in Decentralized Non-Convex Optimization via Perturbed Gradient Tracking
NeurIPS 2020