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Google Scholar Digital Library; Russell Lyons and Yuval Peres. SODA 2023: 5068-5089. We prove that deterministic first-order methods, even applied to arbitrarily smooth functions, cannot achieve convergence rates in $$ better than $^{-8/5}$, which is within $^{-1/15}\\log\\frac{1}$ of the best known rate for such . To appear as a contributed talk at QIP 2023 ; Quantum Pseudoentanglement. There will be a talk every day from 16:00-18:00 CEST from July 26 to August 13. Kirankumar Shiragur | Data Science David P. Woodruff - Carnegie Mellon University pdf, Sequential Matrix Completion. Page 1 of 5 Aaron Sidford Assistant Professor of Management Science and Engineering and of Computer Science CONTACT INFORMATION Administrative Contact Jackie Nguyen - Administrative Associate aaron sidford cv with Hilal Asi, Yair Carmon, Arun Jambulapati and Aaron Sidford %PDF-1.4 I am an Assistant Professor in the School of Computer Science at Georgia Tech. with Yair Carmon, Aaron Sidford and Kevin Tian Yujia Jin. Microsoft Research Faculty Fellowship 2020: Researchers in academia at << Winter 2020 Teaching assistant for EE364a: Convex Optimization I taught by John Duchi, Fall 2018 Teaching assitant for CS265/CME309: Randomized Algorithms and Probabilistic Analysis, Fall 2019 taught by Greg Valiant. With Rong Ge, Chi Jin, Sham M. Kakade, and Praneeth Netrapalli. Cameron Musco - Manning College of Information & Computer Sciences Symposium on Foundations of Computer Science (FOCS), 2020, Efficiently Solving MDPs with Stochastic Mirror Descent arXiv | conference pdf (alphabetical authorship), Jonathan Kelner, Annie Marsden, Vatsal Sharan, Aaron Sidford, Gregory Valiant, Honglin Yuan, Big-Step-Little-Step: Gradient Methods for Objectives with Multiple Scales. Discrete Mathematics and Algorithms: An Introduction to Combinatorial Optimization: I used these notes to accompany the course Discrete Mathematics and Algorithms. Outdated CV [as of Dec'19] Students I am very lucky to advise the following Ph.D. students: Siddartha Devic (co-advised with Aleksandra Korolova . Annie Marsden, Vatsal Sharan, Aaron Sidford, Gregory Valiant, Efficient Convex Optimization Requires . of practical importance. Department of Electrical Engineering, Stanford University, 94305, Stanford, CA, USA With Jack Murtagh, Omer Reingold, and Salil P. Vadhan. with Vidya Muthukumar and Aaron Sidford Our algorithm combines the derandomized square graph operation (Rozenman and Vadhan, 2005), which we recently used for solving Laplacian systems in nearly logarithmic space (Murtagh, Reingold, Sidford, and Vadhan, 2017), with ideas from (Cheng, Cheng, Liu, Peng, and Teng, 2015), which gave an algorithm that is time-efficient (while ours is . Aaron Sidford joins Stanford's Management Science & Engineering department, launching new winter class CS 269G / MS&E 313: "Almost Linear Time Graph Algorithms." With Yair Carmon, John C. Duchi, and Oliver Hinder. 2015 Doctoral Dissertation Award - Association for Computing Machinery