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Theory

4,950 papers

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Papers

Beyond Sub-Gaussian Noises: Sharp Concentration Analysis for Stochastic Gradient Descent JMLR 2022
Overparameterization of Deep ResNet: Zero Loss and Mean-field Analysis JMLR 2022
DoubleML - An Object-Oriented Implementation of Double Machine Learning in Python JMLR 2022
Inherent Tradeoffs in Learning Fair Representations JMLR 2022
Are All Layers Created Equal? JMLR 2022
Efficient Change-Point Detection for Tackling Piecewise-Stationary Bandits JMLR 2022
Posterior Asymptotics for Boosted Hierarchical Dirichlet Process Mixtures JMLR 2022
CD-split and HPD-split: Efficient Conformal Regions in High Dimensions JMLR 2022
Generalized Ambiguity Decomposition for Ranking Ensemble Learning JMLR 2022
When Hardness of Approximation Meets Hardness of Learning JMLR 2022
Total Stability of SVMs and Localized SVMs JMLR 2022
An Error Analysis of Generative Adversarial Networks for Learning Distributions JMLR 2022
Darts: User-Friendly Modern Machine Learning for Time Series JMLR 2022
Foolish Crowds Support Benign Overfitting JMLR 2022
Recovery and Generalization in Over-Realized Dictionary Learning JMLR 2022
A Perturbation-Based Kernel Approximation Framework JMLR 2022
Deep Limits and a Cut-Off Phenomenon for Neural Networks JMLR 2022
Gaussian process regression: Optimality, robustness, and relationship with kernel ridge regression JMLR 2022
Universal Approximation Theorems for Differentiable Geometric Deep Learning JMLR 2022
Underspecification Presents Challenges for Credibility in Modern Machine Learning JMLR 2022
The Interplay Between Implicit Bias and Benign Overfitting in Two-Layer Linear Networks JMLR 2022
A Random Matrix Perspective on Random Tensors JMLR 2022
Deep Network Approximation: Achieving Arbitrary Accuracy with Fixed Number of Neurons JMLR 2022
On the Convergence Rates of Policy Gradient Methods JMLR 2022
Theoretical Foundations of t-SNE for Visualizing High-Dimensional Clustered Data JMLR 2022