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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)

Asymptotics of Ridge(less) Regression under General Source Condition AISTATS 2021 Asymptotics of Ridge Regression in Convolutional Models ICML 2021 Asymptotics of the Bootstrap via Stability with Applications to Inference with Model Selection NeurIPS 2021 Asynchronous $ε$-Greedy Bayesian Optimisation UAI 2021 Asynchronous Active Learning with Distributed Label Querying IJCAI 2021 Asynchronous Decentralized Online Learning NeurIPS 2021 Asynchronous Decentralized Optimization With Implicit Stochastic Variance Reduction ICML 2021 Asynchronous Decentralized SGD with Quantized and Local Updates NeurIPS 2021 Asynchronous Distributed Learning : Adapting to Gradient Delays without Prior Knowledge ICML 2021 Asynchronous Online Testing of Multiple Hypotheses JMLR 2021 Asynchronous Optimization Methods for Efficient Training of Deep Neural Networks with Guarantees AAAI 2021 Asynchronous Stochastic Gradient Descent for Extreme-Scale Recommender Systems AAAI 2021 Asynchronous Stochastic Optimization Robust to Arbitrary Delays NeurIPS 2021 Asynchronous Teacher Guided Bit-wise Hard Mining for Online Hashing AAAI 2021 Async-RED: A Provably Convergent Asynchronous Block Parallel Stochastic Method using Deep Denoising Priors ICLR 2021 A Tale of Two Efficient and Informative Negative Sampling Distributions ICML 2021 A Technical Note on Non-Stationary Parametric Bandits: Existing Mistakes and Preliminary Solutions ALT 2021 A Theoretical Analysis of Catastrophic Forgetting through the NTK Overlap Matrix AISTATS 2021 A Theoretical Analysis of Fine-tuning with Linear Teachers NeurIPS 2021 A Theoretical Analysis of the Repetition Problem in Text Generation AAAI 2021 A Theory of Heuristic Learnability COLT 2021 A theory of high dimensional regression with arbitrary correlations between input features and target functions: sample complexity, multiple descent curves and a hierarchy of phase transitions ICML 2021 A Theory of Independent Mechanisms for Extrapolation in Generative Models AAAI 2021 A Theory of Label Propagation for Subpopulation Shift ICML 2021 A Theory of the Distortion-Perception Tradeoff in Wasserstein Space NeurIPS 2021