Kapil Ahuja

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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)
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)
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)
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)
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)
We focus on robust and efficient iterative solvers for the pressure Poisson equation in in-compressible Navier-Stokes problems. Preconditioned Krylov subspace methods are popular for these problems, with BiCGStab and GMRES(m) most frequently used for nonsymmet-ric systems. BiCGStab is popular because it has cheap iterations, but it may fail for stiff(More)
—This paper presents an online learning with regu-larized 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)
Breast cancer is becoming increasing pervasive, and its early detection is an important step in saving life of any patient. Mammography is an important tool in breast cancer diagnosis. The most important step here is classification of mammogram patch as normal-abnormal and benign-malignant. Texture of a breast in a mammogram patch plays a big role in these(More)
We model social storage systems as a strategic network formation game. We define the utility of each player in the network under two different frameworks, one where the cost to add and maintain links is considered in the utility function and the other where budget constraints are considered. In the context of social storage and social cloud computing, these(More)