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
'5
'10
'15
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Papers (including subtopics)
On Multi-Armed Bandit with Impatient Arms
ICML 2024
On Optimal Tradeoffs between EFX and Nash Welfare
AAAI 2024
On Partial Optimal Transport: Revising the Infeasibility of Sinkhorn and Efficient Gradient Methods
AAAI 2024
On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation
ICLR 2024
On Socially Fair Low-Rank Approximation and Column Subset Selection
NeurIPS 2024
On Sparse Canonical Correlation Analysis
NeurIPS 2024
On the Capacitated Facility Location Problem with Scarce Resources
UAI 2024
On the Complexity of Finite-Sum Smooth Optimization under the Polyak–Łojasiewicz Condition
ICML 2024
On The Complexity of First-Order Methods in Stochastic Bilevel Optimization
ICML 2024
On the Computational and Statistical Complexity of Over-parameterized Matrix Sensing
JMLR 2024
On the Computational Complexity of Metropolis-Adjusted Langevin Algorithms for Bayesian Posterior Sampling
JMLR 2024
On the Computational Complexity of Private High-dimensional Model Selection
NeurIPS 2024
On the Connection between Lp- and Risk Consistency and its Implications on Regularized Kernel Methods
JMLR 2024
On the convergence of adaptive first order methods: Proximal gradient and alternating minimization algorithms
L4DC 2024
On the Convergence of Projected Alternating Maximization for Equitable and Optimal Transport
JMLR 2024
On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity
ICML 2024
On the Error-Propagation of Inexact Hotelling’s Deflation for Principal Component Analysis
ICML 2024
On the estimation of persistence intensity functions and linear representations of persistence diagrams
AISTATS 2024
On the Hardness of Online Nonconvex Optimization with Single Oracle Feedback
ICLR 2024
On the Hyperparameters in Stochastic Gradient Descent with Momentum
JMLR 2024
On the Implicit Bias of Adam
ICML 2024
On the Last-Iterate Convergence of Shuffling Gradient Methods
ICML 2024
On the Maximal Local Disparity of Fairness-Aware Classifiers
ICML 2024
On the Minimax Regret for Contextual Linear Bandits and Multi-Armed Bandits with Expert Advice
NeurIPS 2024
On the Necessity of Collaboration for Online Model Selection with Decentralized Data
NeurIPS 2024