Research
Developing efficient algorithms that power faster, smarter, and more reliable computing across diverse applications.
The Academic Research Summit 2018 is a forum to foster meaningful discussion among the Indian Computer Science research community and enable collaborations to advance the state of the art and raise the bar on research…
The Academic Research Summit, co-organized by Microsoft Research and the Association for Computing Machinery, is a forum to foster meaningful discussion among the Indian computer science research community and raise the bar on research efforts.…
The Academic Research Summit, co-organized by Microsoft Research and the Association for Computing Machinery, is a forum to foster meaningful discussion among the Indian computer science research community and raise the bar on research efforts.…
The Academic Research Summit, co-organized by Microsoft Research and the Association for Computing Machinery, is a forum to foster meaningful discussion among the Indian computer science research community and raise the bar on research efforts.…
The Academic Research Summit, co-organized by Microsoft Research and the Association for Computing Machinery, is a forum to foster meaningful discussion among the Indian computer science research community and raise the bar on research efforts.…
In Theoretical CS many of the fastest algorithms are obtained by considering the Linear Programming (LP) relaxation of the problem. In this talk, I will survey several results on the effectiveness of employing the more…
The Academic Research Summit, co-organized by Microsoft Research and the Association for Computing Machinery, is a forum to foster meaningful discussion among the Indian computer science research community and raise the bar on research efforts.…
A fundamental goal in data analysis is learning which actions (i.e. interventions) are optimal for producing a desired outcome within specific individuals or over an entire population. While advances in reinforcement learning, Bayesian optimization, and…
Quadratic assignment is a very general problem in theoretical computer science. It includes graph matching, the traveling salesman problem, and the Gromov-Hausdorff distance between finite metric spaces as particular cases. Quadratic assignment is in general…
Stochastic gradient-based methods are the state-of-the-art in large-scale machine learning optimization due to their extremely efficient per-iteration computational cost. Second-order methods, that use the second derivative of the optimization objective, are known to enable faster…
