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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)

Interpolating between sampling and variational inference with infinite stochastic mixtures UAI 2022 Interpolating Predictors in High-Dimensional Factor Regression JMLR 2022 Interpolation and Regularization for Causal Learning NeurIPS 2022 Interpretable Clustering via Multi-Polytope Machines AAAI 2022 Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations AAAI 2022 Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings ICML 2022 Interpretable Off-Policy Learning via Hyperbox Search ICML 2022 Interpretable Self-Aware Neural Networks for Robust Trajectory Prediction CoRL 2022 Interpreting Operation Selection in Differentiable Architecture Search: A Perspective from Influence-Directed Explanations NeurIPS 2022 Interpreting the Robustness of Neural NLP Models to Textual Perturbations ACL 2022 Interpreting Time-Varying Dynamic Bayesian Networks for Earth Climate Modelling PGM 2022 Interspace Pruning: Using Adaptive Filter Representations To Improve Training of Sparse CNNs CVPR 2022 Interventional Contrastive Learning with Meta Semantic Regularizer ICML 2022 Interventions, Where and How? Experimental Design for Causal Models at Scale NeurIPS 2022 Intra-speaker phonetic variation in read speech: comparison with inter-speaker variability in a controlled population Interspeech 2022 Intriguing Properties of Input-Dependent Randomized Smoothing ICML 2022 Intrinsic dimensionality estimation using Normalizing Flows NeurIPS 2022 Intrinsic Dimension Estimation Using Wasserstein Distance JMLR 2022 Intrinsic Gradient Compression for Scalable and Efficient Federated Learning ACL 2022 Introspective Learning : A Two-Stage approach for Inference in Neural Networks NeurIPS 2022 IntSGD: Adaptive Floatless Compression of Stochastic Gradients ICLR 2022 Invariance-Aware Randomized Smoothing Certificates NeurIPS 2022 Invariance Learning in Deep Neural Networks with Differentiable Laplace Approximations NeurIPS 2022 Invariant Ancestry Search ICML 2022 Invariant Language Modeling EMNLP 2022