Many classification tasks benefit from integrating manifold learning and semi-supervised learning. By formulating the learning task in a semi-supervised manner, we propose a novel...
We present an improved data model that reflects the whole VLSI design process including bottom-up and topdown design phases. The kernel of the model is a static version concept th...
We present an efficient framework for dynamic reconfiguration of application-specific custom instructions. A key component of this framework is an iterative algorithm for temporal...
Modulo scheduling is an e cient technique for exploiting instruction level parallelism in a variety of loops, resulting in high performance code but increased register requirement...
Alexandre E. Eichenberger, Edward S. Davidson, San...
This paper presents a simple and novel structure representation supporting the assembly and disassembly planning of electromechanical products. The proposed Relationship Matrix de...