Series
Transdisciplinary Research Institute for Advancing Data Science Lectures
Permanent Link
Series Type
Description
Associated Organization(s)
Associated Organization(s)
Publication Search Results
Lecture 5: Inference and Uncertainty Quantification for Noise Matrix Completion
Lecture 2: Random initialization and implicit regularization in nonconvex statistical estimation
Lecture 5: Mathematics for Deep Neural Networks: Energy landscape and open problems
Lecture 2: Mathematics for Deep Neural Networks: Theory for shallow networks
Lecture 4: Spectral Methods Meets Asymmetry: Two Recent Stories
Lecture 1: The power of nonconvex optimization in solving random quadratic systems of equations
Lecture 4: Mathematics for Deep Neural Networks: Statistical theory for deep ReLU networks
Lecture 3: Projected Power Method: An Efficient Algorithm for Joint Discrete Assignment
Lecture 3: Mathematics for Deep Neural Networks: Advantages of Additional Layers