It is well known that optimal server placement is NP-hard. We present an approximate model for the case when both clients and servers are dense, and propose a simple server alloca...
Conditional Random Fields (CRFs) are a widely-used approach for supervised sequence labelling, notably due to their ability to handle large description spaces and to integrate str...
We present a random-walk-based approach to learning paraphrases from bilingual parallel corpora. The corpora are represented as a graph in which a node corresponds to a phrase, an...
This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...
In this paper we look at combining and compressing a set of workflows, such that computation can be minimized. In this context, we look at two novel theoretical problems with appl...
Dhrubajyoti Saha, Abhishek Samanta, Smruti R. Sara...