High-dimensional data usually incur learning deficiencies and computational difficulties. We present a novel semi-supervised dimensionality reduction technique that embeds high-dim...
This paper proposes DINloop (Data-In-Network loop) based multicast with GMPLS (generalized multiprotocol label switching) to overcome the scalability problems existing in current i...
Disk power management is becoming increasingly important in high-end server and cluster type of environments that execute dataintensive applications. While hardware-only approache...
We consider the in-network computation of approximate “big picture” summaries in bandwidth-constrained sensor networks. First we review early work on computing the Haar wavele...
Dimensionality reduction plays an important role in many machine learning and pattern recognition tasks. In this paper, we present a novel dimensionality reduction algorithm calle...