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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
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Papers (including subtopics)

Practical Adversarial Multivalid Conformal Prediction NeurIPS 2022 Practically Correct, Just-in-Time Shell Script Parallelization OSDI 2022 Practical Over-the-air Perceptual AcousticWatermarking Interspeech 2022 Practical Schemes for Finding Near-Stationary Points of Convex Finite-Sums AISTATS 2022 Pre-activation Distributions Expose Backdoor Neurons NeurIPS 2022 Precise Learning Curves and Higher-Order Scalings for Dot-product Kernel Regression NeurIPS 2022 Precise Regret Bounds for Log-loss via a Truncated Bayesian Algorithm NeurIPS 2022 Preconditioning for Scalable Gaussian Process Hyperparameter Optimization ICML 2022 Predicting Attention Sparsity in Transformers ACL 2022 Predicting Difficulty and Discrimination of Natural Language Questions ACL 2022 Predicting Fine-Tuning Performance with Probing EMNLP 2022 Predicting Out-of-Distribution Error with the Projection Norm ICML 2022 Predicting the utility of search spaces for black-box optimization: a simple, budget-aware approach AISTATS 2022 Predictive Coding: Towards a Future of Deep Learning beyond Backpropagation? IJCAI 2022 Predictive Querying for Autoregressive Neural Sequence Models NeurIPS 2022 Predictive State Propensity Subclassification (PSPS): A causal inference algorithm for data-driven propensity score stratification CLeaR 2022 Predictive variational Bayesian inference as risk-seeking optimization AISTATS 2022 Preference Exploration for Efficient Bayesian Optimization with Multiple Outcomes AISTATS 2022 PrEF: Probabilistic Electricity Forecasting via Copula-Augmented State Space Model AAAI 2022 Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation AAAI 2022 Pretrained Cost Model for Distributed Constraint Optimization Problems AAAI 2022 Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors NeurIPS 2022 Primal-Dual Stochastic Mirror Descent for MDPs AISTATS 2022 Principal Components Bias in Over-parameterized Linear Models, and its Manifestation in Deep Neural Networks JMLR 2022 Prior Gradient Mask Guided Pruning-Aware Fine-Tuning AAAI 2022