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
1
14
29
44
31
52
189
195
212
235
352
382
457
787
816
828
1,066
1,391
1,913
3,012
3,646
4,303
4,450
5,357
6,155
5,854
1,521
2000
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'15
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Papers (including subtopics)
On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability (Extended Abstract)
IJCAI 2020
On Parameter Adaptation in Softmax-Based Cross-Entropy Loss for Improved Convergence Speed and Accuracy in DNN-Based Speaker Recognition
Interspeech 2020
On Performance Estimation in Automatic Algorithm Configuration
AAAI 2020
On Pruning for Score-Based Bayesian Network Structure Learning
AISTATS 2020
On Random Subsampling of Gaussian Process Regression: A Graphon-Based Analysis
AISTATS 2020
On ranking via sorting by estimated expected utility
NeurIPS 2020
On Regret with Multiple Best Arms
NeurIPS 2020
On Reward-Free Reinforcement Learning with Linear Function Approximation
NeurIPS 2020
On Robustness in Qualitative Constraint Networks
IJCAI 2020
On Robustness of Neural Ordinary Differential Equations
ICLR 2020
On Second Order Behaviour in Augmented Neural ODEs
NeurIPS 2020
On Second-Order Group Influence Functions for Black-Box Predictions
ICML 2020
On Semi-parametric Inference for BART
ICML 2020
On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach
ICLR 2020
On Stationary-Point Hitting Time and Ergodicity of Stochastic Gradient Langevin Dynamics
JMLR 2020
On Suboptimality of Least Squares with Application to Estimation of Convex Bodies
COLT 2020
On Testing of Samplers
NeurIPS 2020
On the Ability and Limitations of Transformers to Recognize Formal Languages
EMNLP 2020
On the Acceleration of Deep Learning Model Parallelism With Staleness
CVPR 2020
On the Almost Sure Convergence of Stochastic Gradient Descent in Non-Convex Problems
NeurIPS 2020
On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models
AAAI 2020
On the Branching Bias of Syntax Extracted from Pre-trained Language Models
EMNLP 2020
On the Complexity Analysis of the Primal Solutions for the Accelerated Randomized Dual Coordinate Ascent
JMLR 2020
On the Complexity of Proper Distribution-Free Learning of Linear Classifiers
ALT 2020
On the Computational Power of Transformers and Its Implications in Sequence Modeling
CoNLL 2020