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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)

Flow Annealed Importance Sampling Bootstrap ICLR 2023 Flow Matching for Scalable Simulation-Based Inference NeurIPS 2023 FlowPG: Action-constrained Policy Gradient with Normalizing Flows NeurIPS 2023 Focal Training and Tagger Decouple for Grammatical Error Correction ACL 2023 Focused Prefix Tuning for Controllable Text Generation ACL 2023 Focus Your Attention (with Adaptive IIR Filters) EMNLP 2023 Folded Hamiltonian Monte Carlo for Bayesian Generative Adversarial Networks ACML 2023 Following the Data, Not the Function: Rethinking Function Orchestration in Serverless Computing NSDI 2023 Follow the leader(board) with confidence: Estimating p-values from a single test set with item and response variance ACL 2023 Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems ALT 2023 Follow the Wisdom of the Crowd: Effective Text Generation via Minimum Bayes Risk Decoding ACL 2023 Follow-ups Also Matter: Improving Contextual Bandits via Post-serving Contexts NeurIPS 2023 Forecasting with Sparse but Informative Variables: A Case Study in Predicting Blood Glucose AAAI 2023 ForestPrune: Compact Depth-Pruned Tree Ensembles AISTATS 2023 Forget Unlearning: Towards True Data-Deletion in Machine Learning ICML 2023 Forgotten Knowledge: Examining the Citational Amnesia in NLP ACL 2023 ForkMerge: Mitigating Negative Transfer in Auxiliary-Task Learning NeurIPS 2023 Formalising the Robustness of Counterfactual Explanations for Neural Networks AAAI 2023 Formalizing locality for normative synaptic plasticity models NeurIPS 2023 Formally Verified Solution Methods for Markov Decision Processes AAAI 2023 Formulating Discrete Probability Flow Through Optimal Transport NeurIPS 2023 Forward-Backward Gaussian Variational Inference via JKO in the Bures-Wasserstein Space ICML 2023 Forward Super-Resolution: How Can GANs Learn Hierarchical Generative Models for Real-World Distributions ICLR 2023 Fourier Neural Operator with Learned Deformations for PDEs on General Geometries JMLR 2023 FP-Diffusion: Improving Score-based Diffusion Models by Enforcing the Underlying Score Fokker-Planck Equation ICML 2023