In this paper, we propose a unified algorithmic framework for solving many known variants of MDS. Our algorithm is a simple iterative scheme with guaranteed convergence, and is mo...
Arvind Agarwal, Jeff M. Phillips, Suresh Venkatasu...
Two-dimensional phase unwrapping is the problem of deducing unambiguous "phase" from values known only modulo 2. Many authors agree that the objective of phase unwrappin...
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Dyadic data matrices, such as co-occurrence matrix, rating matrix, and proximity matrix, arise frequently in various important applications. A fundamental problem in dyadic data a...
We present a memory efficient, practical, systolic, parallel architecture for the complete 0/1 knapsack dynamic programming problem, including backtracking. This problem was inte...