Algorithms and Modeling
Algorithms are central to all computing. The second word in the title stresses the fact that the input to an algorithm comes from a process modeling a real-world problem into data.
The group’s current areas of research include matrix and linear algebra algorithms, networks, games and economic models and algorithms, semi-definite programming and optimization, massive data problems, and approximation algorithms.
People
Shipra Agrawal
Deeparnab Chakrabarty
Nisheeth Vishnoi
Publications
- Raajay Viswanathan, Prateek Jain, Srivatsan Laxman, and Arvind Arasu, A Learning Framework for Self-Tuning Histograms, no. MSR-TR-2011-140, December 2011
- Prateek Jain, Pravesh Kothari, and Abhradeep Thakurta, Differentially Private Online Learning, no. MSR-TR-2011-141, September 2011
- Prateek Jain, Brian Kulis, Jason V. Davis, and Inderjit S. Dhillon, Metric and Kernel Learning using a Linear Transformation, in Journal of Machine Learning (JMLR), 2011
- Purushottam Kar and Prateek Jain, Similarity-based Learning via Data driven Embeddings, in 25th Annual Conference on Neural Information Processing Systems (NIPS), 2011
- Prateek Jain, Brian Kulis, and Inderjit S. Dhillon, Inductive Regularized Learning of Kernel Functions, in Advances in Neural Information Processing Systems (NIPS), 2010
