6105 Gates Hillman Center, Carnegie Mellon University
PITTSBURGH, PA 15213
I’m looking for a Machine Learning research internship for Summer 2018!
I am a third year PhD student in the Computer Science Department of Carnegie Mellon University (CMU). I am fortunate to be advised by Zico Kolter. My interests lie in the algorithmic and foundational aspects of Machine Learning and Artificial Intelligence. Currently I am working on theoretically understanding Generative Adversarial Networks and Deep Learning. In the past I have worked in Learning Theory, Multi-Agent Systems and Reinforcement Learning.
I completed my undergraduate studies in the Department of Computer Science and Engineering at the Indian Institute of Technology, Chennai, India. Here I was advised by Balaraman Ravindran with whom I worked in Reinforcement Learning.
Here is a link to my CV.
Full Conference Papers
Gradient descent GAN optimization is locally stable, Neural Information Processing Systems (NIPS) 2017 (Accepted for Oral presentation)
Vaishnavh Nagarajan and J. Zico Kolter
[arxiv] [1hr talk - slides] [NIPS Oral - Slides] [Poster] [3 min video]
Learning-Theoretic Foundations of Algorithm Configuration for Combinatorial Partitioning Problems, Conference On Learning Theory (COLT), 2017
with Maria-Florina Balcan, Ellen Vitercik and Colin White
[arxiv] [Slides] [Talk]
Every team deserves a second chance: Identifying when things go wrong, Autonomous Agents and Multiagent Systems (AAMAS) 2015
(Double 1st author) Vaishnavh Nagarajan, Leandro S. Marcolino and Milind Tambe
- A Reinforcement Learning Approach to Online Learning of Decision Trees, European Workshop on Reinforcement Learning (EWRL 2015 - ICML)
(Triple 1st author) Abhinav Garlapati, Aditi Raghunathan, Vaishnavh Nagarajan and Balaraman Ravindran.
Short Papers and Demonstrations
- Knows-What-It-Knows Inverse Reinforcement Learning, Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM) 2015
Vaishnavh Nagarajan and Balaraman Ravindran
Last Updated: Oct 6th, 2017