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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

1
52
352
828
3,646
5,854
2000
'5
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'25

Papers (including subtopics)

Tracking Functional Changes in Nonstationary Signals with Evolutionary Ensemble Bayesian Model for Robust Neural Decoding NeurIPS 2022 Tracking Most Significant Arm Switches in Bandits COLT 2022 Tracking the risk of a deployed model and detecting harmful distribution shifts ICLR 2022 Tractable Abstract Argumentation via Backdoor-Treewidth AAAI 2022 Tractable Optimality in Episodic Latent MABs NeurIPS 2022 Tractable Uncertainty for Structure Learning ICML 2022 Trade-off between Payoff and Model Rewards in Shapley-Fair Collaborative Machine Learning NeurIPS 2022 Trading Off Resource Budgets For Improved Regret Bounds NeurIPS 2022 Train Flat, Then Compress: Sharpness-Aware Minimization Learns More Compressible Models EMNLP 2022 Training Data Generating Networks: Shape Reconstruction via Bi-level Optimization ICLR 2022 Training Discrete Deep Generative Models via Gapped Straight-Through Estimator ICML 2022 Training-Free Transformer Architecture Search CVPR 2022 Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate AAAI 2022 Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation CVPR 2022 Training invariances and the low-rank phenomenon: beyond linear networks ICLR 2022 Training Lipschitz Continuous Operators Using Reproducing Kernels L4DC 2022 Training on the Test Set: Mapping the System-Problem Space in AI AAAI 2022 Training Quantised Neural Networks With STE Variants: The Additive Noise Annealing Algorithm CVPR 2022 Training Robust Deep Models for Time-Series Domain: Novel Algorithms and Theoretical Analysis AAAI 2022 Training Scale-Invariant Neural Networks on the Sphere Can Happen in Three Regimes NeurIPS 2022 Training stochastic stabilized supralinear networks by dynamics-neutral growth NeurIPS 2022 Training Structured Neural Networks Through Manifold Identification and Variance Reduction ICLR 2022 Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent JMLR 2022 Training Uncertainty-Aware Classifiers with Conformalized Deep Learning NeurIPS 2022 Training Up to 50 Class ML Models on 3 $ IoT Hardware via Optimizing One-vs-One Algorithm (Student Abstract) AAAI 2022