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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

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52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding ICLR 2023 Zero-Cost Operation Scoring in Differentiable Architecture Search AAAI 2023 Zero-One Laws of Graph Neural Networks NeurIPS 2023 Zero-Regret Performative Prediction Under Inequality Constraints NeurIPS 2023 Zero-shot Sharpness-Aware Quantization for Pre-trained Language Models EMNLP 2023 Zeroth-Order Alternating Gradient Descent Ascent Algorithms for A Class of Nonconvex-Nonconcave Minimax Problems JMLR 2023 Zeroth-Order Methods for Nondifferentiable, Nonconvex, and Hierarchical Federated Optimization NeurIPS 2023 Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation ICLR 2023 Zeroth-order Optimization with Weak Dimension Dependency COLT 2023 Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training NSDI 2023 ZiCo: Zero-shot NAS via inverse Coefficient of Variation on Gradients ICLR 2023 zPROBE: Zero Peek Robustness Checks for Federated Learning ICCV 2023 ℓ_∞-Bounds of the MLE in the BTL Model under General Comparison Graphs UAI 2022 k-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension NeurIPS 2022 SO(2)-Equivariant Reinforcement Learning ICLR 2022 πBO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization ICLR 2022 3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation ICML 2022 A Bandit Model for Human-Machine Decision Making with Private Information and Opacity AISTATS 2022 A Bayesian Approach for Stochastic Continuum-armed Bandit with Long-term Constraints AISTATS 2022 A Bayesian Model for Online Activity Sample Sizes AISTATS 2022 ABC: Attention with Bounded-memory Control ACL 2022 abess: A Fast Best-Subset Selection Library in Python and R JMLR 2022 A Branch and Bound Framework for Stronger Adversarial Attacks of ReLU Networks ICML 2022 A Bregman Learning Framework for Sparse Neural Networks JMLR 2022 A cautionary tale on fitting decision trees to data from additive models: generalization lower bounds AISTATS 2022