#### Filter Results:

- Full text PDF available (13)

#### Publication Year

1996

2017

- This year (2)
- Last 5 years (9)
- Last 10 years (13)

#### Publication Type

#### Co-author

#### Journals and Conferences

#### Key Phrases

Learn More

- Kapil Ahuja, Layne T. Watson, Stephen C. Billups
- Comp. Opt. and Appl.
- 2008

Probability-one homotopy algorithms have strong convergence characteristics under mild assumptions. Such algorithms for mixed complementarity problems (MCPs) have potentially wide impact because MCPs are pervasive in science and engineering. A probability-one homotopy algorithm for MCPs was developed earlier by Billups and Watson based on the default… (More)

- Uma Murthy, Kapil Ahuja, Sudarshan Murthy, Edward A. Fox
- Proceedings of the 6th ACM/IEEE-CS Joint…
- 2006

In a variety of applications such as learning, we need to integrate multimedia information into convenient packages (like presentations). The challenges involved in this process are: Selecting or working with information elements at sub-document level while retaining the original context; describing the integration or packaging of such elements; and making… (More)

- Kapil Ahuja, Eric de Sturler, Serkan Gugercin, Eun R. Chang
- SIAM J. Scientific Computing
- 2012

Science and engineering problems frequently require solving a sequence of dual linear systems. Besides having to store only few Lanczos vectors, using the BiConjugate Gradient method (BiCG) to solve dual linear systems has advantages for specific applications. For example, using BiCG to solve the dual linear systems arising in interpolatory model reduction… (More)

- Seonho Kim, Uma Murthy, Kapil Ahuja, Sandi Vasile, Edward A. Fox
- ECDL
- 2005

Most user focused data mining techniques involve purchase pattern analysis, targeted at strictly-formatted database-like transaction records. Most personalization systems employ explicitly provided user preferences rather than implicit rating data obtained automatically by collecting users’ interactions. In this paper, we show that in complex information… (More)

- Kapil Ahuja, Bryan K. Clark, Eric de Sturler, David M. Ceperley, Jeongnim Kim
- SIAM J. Scientific Computing
- 2011

Quantum Monte Carlo (QMC) methods are often used to calculate properties of many body quantum systems. The main cost of many QMC methods, for example, the variational Monte Carlo (VMC) method, is in constructing a sequence of Slater matrices and computing the ratios of determinants for successive Slater matrices. Recent work has improved the scaling of… (More)

- Kapil Ahuja, Peter Benner, Eric de Sturler, Lihong Feng
- SIAM J. Scientific Computing
- 2015

Krylov subspace recycling is a process for accelerating the convergence of sequences of linear systems. Based on this technique we have recently developed the recycling BiCG algorithm. We now generalize and extend this recycling theory to BiCGSTAB. Recycling BiCG focuses on efficiently solving sequences of dual linear systems, while the focus here is on… (More)

- Amit Amritkar, Eric de Sturler, Katarzyna Swirydowicz, Danesh K. Tafti, Kapil Ahuja
- J. Comput. Physics
- 2015

We focus on robust and efficient iterative solvers for the pressure Poisson equation in incompressible Navier-Stokes problems. Preconditioned Krylov subspace methods are popular for these problems, with BiCGStab and GMRES(m) most frequently used for nonsymmetric systems. BiCGStab is popular because it has cheap iterations, but it may fail for stiff… (More)

- Mihir Mody, Vipul Paladiya, Kapil Ahuja
- 2013 IEEE Second International Conference on…
- 2013

The Widespread usage of social media for picture sharing led resulting popularity of JPEG progressive format due to refinement of image over time on slow internet connection. Typically, these pictures are decoded by means of software and takes large decoding time as resolution in terms of Mpixels increase. In case of embedded devices, typically have… (More)

- Chandan Gautam, Aruna Tiwari, Sundaram Suresh, Kapil Ahuja
- ArXiv
- 2017

This paper presents an online learning with regularized kernel based one-class extreme learning machine (ELM) classifier and is referred as “online RK-OC-ELM”. The baseline kernel hyperplane model considers whole data in a single chunk with regularized ELM approach for offline learning in case of one-class classification (OCC). Further, the basic hyper… (More)