23 citations · 54 across the 9 of their papers we have counts for
9 papers
Error Correction in Learning using SVMs
Srivatsan Laxman, Sushil Mittal, Ramarathnam Venkatesan
This paper is concerned with learning binary classifiers under adversarial label-noise. We introduce the problem of error-correction in learning where the goal is to recover the or…
Streaming Algorithms for Pattern Discovery over Dynamically Changing Event Sequences
Debprakash Patnaik, Naren Ramakrishnan, Srivatsan Laxman +1
Discovering frequent episodes over event sequences is an important data mining task. In many applications, events constituting the data sequence arrive as a stream, at furious rate…
A Learning Framework for Self-Tuning Histograms
Raajay Viswanathan, Prateek Jain, Srivatsan Laxman +1
In this paper, we consider the problem of estimating self-tuning histograms using query workloads. To this end, we propose a general learning theoretic formulation. Specifically, w…
An IR-based Evaluation Framework for Web Search Query Segmentation
Rishiraj Saha Roy, Niloy Ganguly, Monojit Choudhury +1
This paper presents the first evaluation framework for Web search query segmentation based directly on IR performance. In the past, segmentation strategies were mainly validated ag…
Lexical Co-occurrence, Statistical Significance, and Word Association
Dipak Chaudhari, Om P. Damani, Srivatsan Laxman
Lexical co-occurrence is an important cue for detecting word associations. We present a theoretical framework for discovering statistically significant lexical co-occurrences from…
A unified view of Automata-based algorithms for Frequent Episode Discovery
Avinash Achar, Srivatsan Laxman, P. S. Sastry
Frequent Episode Discovery framework is a popular framework in Temporal Data Mining with many applications. Over the years many different notions of frequencies of episodes have be…