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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)

Temporal Dynamic Quantization for Diffusion Models NeurIPS 2023 Temporal Robustness against Data poisoning NeurIPS 2023 Tensor-based Kernel Machines with Structured Inducing Points for Large and High-Dimensional Data AISTATS 2023 Tensor-Based Sketching Method for the Low-Rank Approximation of Data Streams. ICLR 2023 Tensor decomposition for minimization of E2E SLU model toward on-device processing Interspeech 2023 Tensor Decompositions Meet Control Theory: Learning General Mixtures of Linear Dynamical Systems ICML 2023 Test Coverage for Network Configurations NSDI 2023 Tester-Learners for Halfspaces: Universal Algorithms NeurIPS 2023 Testing of Horn Samplers AISTATS 2023 Testing of Index-Invariant Properties in the Huge Object Model COLT 2023 Testing Tail Weight of a Distribution Via Hazard Rate ALT 2023 Testing the Channels of Convolutional Neural Networks AAAI 2023 Test Time Adaptation With Regularized Loss for Weakly Supervised Salient Object Detection CVPR 2023 Test Time Augmentation Meets Post-hoc Calibration: Uncertainty Quantification under Real-World Conditions AAAI 2023 Test-Time Distribution Normalization for Contrastively Learned Visual-language Models NeurIPS 2023 TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization ICLR 2023 TextVerifier: Robustness Verification for Textual Classifiers with Certifiable Guarantees ACL 2023 The k-Cap Process on Geometric Random Graphs COLT 2023 The Adversarial Consistency of Surrogate Risks for Binary Classification NeurIPS 2023 The Aggregation–Heterogeneity Trade-off in Federated Learning COLT 2023 The Analysis of Deep Neural Networks by Information Theory: From Explainability to Generalization AAAI 2023 The Art of BART: Minimax Optimality over Nonhomogeneous Smoothness in High Dimension JMLR 2023 The Asymmetric Maximum Margin Bias of Quasi-Homogeneous Neural Networks ICLR 2023 The Bayesian Learning Rule JMLR 2023 The Bayesian Stability Zoo NeurIPS 2023