Dimensionality reduction plays an important role in many data mining applications involving high-dimensional data. Many existing dimensionality reduction techniques can be formula...
Many learning algorithms rely on the curvature (in particular, strong convexity) of regularized objective functions to provide good theoretical performance guarantees. In practice...
Abstract. In the constraint satisfaction problem (CSP), the aim is to find an assignment of values to a set of variables subject to specified constraints. In the minimum cost hom...
We propose in this paper a general framework for integrating inductive and case-based reasoning techniques for diagnosis tasks. We present a set of practical integrated approaches...
FPGAs, because of their re-programmability, are becoming very popular for creating and exchanging VLSI intellectual properties (IPs) in the reuse-based design paradigm. Existing w...
Adarsh K. Jain, Lin Yuan, Pushkin R. Pari, Gang Qu