#### Filter Results:

#### Publication Year

1991

2016

#### Publication Type

#### Co-author

#### Key Phrase

#### Publication Venue

Learn More

As trees are used in a wide variety of application areas, the comparison of trees arises in many guises. Here we consider two generalizations of classical tree pattern matching, which consists of determining if one tree is isomorphic to a subgraph of another. For the embedding problems of subgraph isomorphism and topological embedding, we present algorithms… (More)

- Rajeev Gupta, Prakash C. Deedwania, Krishnakumar Sharma, Arvind Gupta, Soneil Guptha, Vijay Achari +10 others
- PloS one
- 2012

BACKGROUND
To determine correlation of multiple parameters of socioeconomic status with cardiovascular risk factors in India.
METHODS
The study was performed at eleven cities using cluster sampling. Subjects (n = 6198, men 3426, women 2772) were evaluated for socioeconomic, demographic, biophysical and biochemical factors. They were classified into low,… (More)

We study the problem of designing fault tolerant routings in both complete and complete bipartite optical networks. We show that this problem has strong connections to various fundamental problems in design theory. Using a design theory approach, we find optimal f-fault tolerant arc-forwarding indexes for all complete networks and all complete balanced… (More)

- Arvind Gupta
- LFCS
- 1992

For digraphs G and H, a homomorphism of G to H is a mapping f : V (G)→V (H) such that uv ∈ A(G) implies f (u)f (v) ∈ A(H). If moreover each vertex u ∈ V (G) is associated with costs c i (u), i ∈ V (H), then the cost of a homomorphism f is u∈V (G) c f (u) (u). For each fixed digraph H, the minimum cost homomorphism problem for H, denoted MinHOM(H), is the… (More)

BACKGROUND
Recent biological discoveries have shown that clustering large datasets is essential for better understanding biology in many areas. Spectral clustering in particular has proven to be a powerful tool amenable for many applications. However, it cannot be directly applied to large datasets due to time and memory limitations. To address this issue,… (More)

Mitchell and Ternovska [49, 50] propose a constraint programming framework for search problems that is based on classical logic extended with inductive definitions. They formulate a search problem as the problem of model expansion (MX). In this framework, the problem is encoded in a logic, an instance of the problem is represented by a finite structure, and… (More)