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Yuhan Liu is a postdoc at Rice University working with Prof. Maryam Aliakbarpour, Vladimir Braverman, and Nai-Hui Chia. He obtained his PhD in Electrical and Computer Engineering from Cornell University in 2024, advised by Prof. Jayadev Acharya. He...
Certain non-trivial flattenings of tensors to matrices have been useful for proving lower bounds on the rank of explicit tensors such as the matrix multiplication tensor. I will show how this tool can also be used to obtain algorithmic results for the...
Ria Stevens is a PhD student at Rice University, advised by Maryam Aliakbarpour and Anastasios (Tasos) Kyrillidis. Her research interests include differential privacy, augmented algorithms and optimization.
Tomas Gonzalez is a third-year PhD student in the Machine Learning Department at Carnegie Mellon University, co-advised by Aaditya Ramdas and Giulia Fanti. He earned his MSc from the Institute for Mathematical and Computational Engineering at the Catholic...
For a square matrix A, the resolvent of A at a point z ∈ C that is not an eigenvalue of A is defined as (A − zI)^{-1}. The nearest (in 2-norm) rank one matrix to (A − zI)^{-1} is σ1(z)u1(z)v1(z)*, where σ1(z) is the largest singular value and u1(z) and v1...
In this talk, I will discuss some new developments on sum-of-exponential (SOE) approximations, which is motivated by applications in many-body physics. We will examine what could be proved for the complexity of these approximations, emphasizing how it...
What do Jacobi’s eigenvalue algorithm and an iterative algorithm for finding the QR decomposition have in common? Under a randomized pivoting strategy, a unified analysis can show that these algorithms converge with the same linear rate of convergence. We...
Double saddle-point systems are drawing increasing attention in the past few years, due to the importance of multiphysics applications and recent advances in the solution of indefinite linear systems. In this talk I will describe some of the numerical...