Praneeth Netrapalli
Research Interests
The main focus of my work is to develop a deeper understanding of machine learning, ranging across optimization, generalization, robustness etc. Given the difficulty and diversity of these questions, I use both theoretical [Paper1 Paper2] and experimental [Paper3] tools to make progress on these questions.
I also work on designing efficient algorithms for various optimization problems that arise in machine learning [Paper4].
Google Scholar DBLP arXiv
News and announcements
Professional service
On the program committee/area chair: NeurIPS 2019-20, COLT 2019-21, ICLR 2021, ICML 2019, 2021, AISTATS 2019.
Selected publications
* indicates alphabetical ordering of author names. Please see here for all publications.
How to Escape Saddle Points Efficiently
C. Jin, R. Ge, P. Netrapalli, S. M. Kakade and M. I. Jordan
ICML 2017
Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja's Algorithm [*]
P. Jain, C. Jin, S. M. Kakade, P. Netrapalli and A. Sidford
COLT 2016
Phase Retrieval using Alternating Minimization
P. Netrapalli, P. Jain and S. Sanghavi
IEEE Transactions on Signal Processing 2015, Vol. 63, Issue 18, Pages 4814–4826
Low-rank Matrix Completion using Alternating Minimization [*]
P. Jain, P. Netrapalli and S. Sanghavi
STOC 2013
Mentoring
I have been extremely fortunate to work with an amazing set of students.
Interns/Visitors (in reverse chronological order)
Research fellows (in reverse chronological order)
Harshay Shah
Abhishek Panigrahi
Suhas Jayaram (now PhD student at CMU)
Raghav Somani (now PhD student at University of Washington)
Chirag Gupta (now PhD student at CMU)
Rahul Anand Sharma (now PhD student at CMU)
Vivek Gupta (now PhD student at University of Utah)
Yeshwanth Cherapanamjeri (now PhD student at UC Berkeley)
Contact details
Address: Microsoft Research, # 9, Vigyan 1st floor, Lavelle Road, Bengaluru, Karnataka 560001, India.
E-mail: praneeth [at] microsoft [dot] com
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