Google Inc., Mountain View, CA, USA
David R. Karger, Eric Lehman, Tom Leighton, Rina Panigrahy, Matthew S. Levine, Daniel Lewin, Frank Thomson Leighton
We describe a family of caching protocols for distrib-uted networks that can be used to decrease or eliminate the occurrence of hot spots in the network. Our protocols are particularly designed for use with very large networks such as the Internet, ...
Nitin Agrawal, Vijayan Prabhakaran, Ted Wobber, John D. Davis, Mark S. Manasse, Rina Panigrahy
Moses Charikar, Liadan O'Callaghan, Rina Panigrahy
Proceedings of the 35th Annual ACM Symposium on Theory of Computing, 2003 – STOC
We study clustering problems in the streaming model, where the goal is to cluster a set of points by making one pass (or a few passes) over the data using a small amount of storage space. Our main result is a randomized algorithm for the k--Median ...
Gagan Aggarwal, Tomás Feder, Krishnaram Kenthapadi, Samir Khuller, Rina Panigrahy, Dilys Thomas, An Zhu
Twenty-Fifth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 2006 – PODS
Publishing data for analysis from a table containing personal records, while maintaining individual privacy, is a problem of increasing importance today. The traditional approach of de-identifying records is to remove identifying fields such as ...
Proceedings of the Seventeenth Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2006, 2006 – SODA
In this paper we study the problem of finding the approximate nearest neighbor of a query point in the high dimensional space, focusing on the Euclidean space. The earlier approaches use locality-preserving hash functions (that tend to map nearby ...
Andrei Z. Broder, Marcus Fontoura, Vanja Josifovski, S. Ravi Kumar, Rajeev Motwani, Shubha U. Nabar, Rina Panigrahy, Andrew Tomkins, Ying Xu
Proceedings of the 2006 ACM CIKM International Conference on Information and Knowledge Management, 2006 – CIKM
We consider the problem of estimating the size of a collection of documents using only a standard query interface. Our main idea is to construct an unbiased and low-variance estimator that can closely approximate the size of any set of documents ...
Atish Das Sarma, Sreenivas Gollapudi, Marc Najork, Rina Panigrahy
Third International Conference on Web Search and Web Data Mining, WSDM 2010, 2010 – WSDM
We study the fundamental problem of computing distances between nodes in large graphs such as the web graph and social networks. Our objective is to be able to answer distance queries between pairs of nodes in real time. Since the standard shortest ...
Yinglian Xie, Fang Yu, Kannan Achan, Rina Panigrahy, Geoff Hulten, Ivan Osipkov
ACM SIGCOMM 2008 conference on Data communication, 2008 – SIGCOMM
In this paper, we focus on characterizing spamming botnets by leveraging both spam payload and spam server traffic properties. Towards this goal, we developed a spam signature generation framework called AutoRE to detect botnet-based spam emails and ...