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Research Area: Machine Learning, Computational Advertising |
Profile
Rajiv has been working as a research engineer since Jul 2008 at Yahoo! labs bangalore. The main area of his focus has been on building a web scale recommendation system and has also dabbled on rare event prediction.
Prior to joining Yahoo!, Rajiv completed his Masters in Tech. from IIT Bombay. In his masters thesis, he studied and worked on learning to rank, specifically on the problem of optimizing SVMs directly for structural loss functions. Before that, he completed his Bachelors in Tech. from NIT Jalandhar.
Rajiv is a voracious reader, a foodie and loves to travel. Ever since he can remember, he has enjoyed solving and analyzing puzzles. He also enjoys an occasional AoE game, though his PC gaming days are now behind him, since he now enjoys his work more.
Recent Publications, Projects and News
- Estimating Rates of Rare Events with Multiple Hierarchies through Scalable Log-linear Models Deepak Agarwal ; Nagaraj Kota ; Rahul Agrawal ; Rajiv Khanna, SIGKDD, 2010
- Translating Relevance Scores to Probabilities for Contextual Advertising Deepak Agarwal; Evgeniy Gabrilovich; Rob Hall; Vanja Josifovski; Rajiv Khanna, The 18th ACM Conference on Information and Knowledge Management (CIKM), 2009
- Structured learning for non-smooth ranking losses Soumen Chakrabarti; Rajiv Khanna; Uma Sawant; Chiru Bhattacharyya, KDD, 2008 [view abstract]