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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)

Challenges and Opportunities in High Dimensional Variational Inference NeurIPS 2021 Challenges and Opportunities of Building Fast GBDT Systems IJCAI 2021 Change Matters: Medication Change Prediction with Recurrent Residual Networks IJCAI 2021 Change Point Detection via Multivariate Singular Spectrum Analysis NeurIPS 2021 Change the World - How Hard Can that Be? On the Computational Complexity of Fixing Planning Models IJCAI 2021 Channel Permutations for N:M Sparsity NeurIPS 2021 Chaos of Learning Beyond Zero-sum and Coordination via Game Decompositions ICLR 2021 Characterizing Deep Gaussian Processes via Nonlinear Recurrence Systems AAAI 2021 Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning NeurIPS 2021 Characterizing possible failure modes in physics-informed neural networks NeurIPS 2021 Characterizing Structural Regularities of Labeled Data in Overparameterized Models ICML 2021 Characterizing the Gap Between Actor-Critic and Policy Gradient ICML 2021 Characterizing the implicit bias via a primal-dual analysis ALT 2021 Characterizing the Loss Landscape in Non-Negative Matrix Factorization AAAI 2021 Charting and Navigating the Space of Solutions for Recurrent Neural Networks NeurIPS 2021 Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote NeurIPS 2021 Chebyshev Polynomial Codes: Task Entanglement-based Coding for Distributed Matrix Multiplication ICML 2021 Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation ICCV 2021 CheXbreak: Misclassification Identification for Deep Learning Models Interpreting Chest X-rays MLHC 2021 Choose a Transformer: Fourier or Galerkin NeurIPS 2021 Choosing the Right Algorithm With Hints From Complexity Theory IJCAI 2021 CIDEr-R: Robust Consensus-based Image Description Evaluation EMNLP 2021 Cinematic-L1 Video Stabilization With a Log-Homography Model WACV 2021 Circles are like Ellipses, or Ellipses are like Circles? Measuring the Degree of Asymmetry of Static and Contextual Word Embeddings and the Implications to Representation Learning AAAI 2021 Class Anchor Clustering: A Loss for Distance-Based Open Set Recognition WACV 2021