The Multi-Level Decomposition Diagrams (MLDDs) of this paper are a canonical representation of Boolean functions expliciting disjoint-support decompositions. MLDDs allow the reduc...
MOEA/D is a multi-objective metaheuristic which has shown a remarkable performance when solving hard optimization problems. In this paper, we propose a thread-based parallel versio...
In this paper, we provide a methodology to perform both bus partitioning and bus frequency assignment to each of the bus segment simultaneously while optimizing both power consump...
Suresh Srinivasan, Lin Li, Narayanan Vijaykrishnan
Partially Observable Markov Decision Processes (POMDPs) are a well-established and rigorous framework for sequential decision-making under uncertainty. POMDPs are well-known to be...
The sequence kernel has been shown to be a promising kernel function for learning from sequential data such as speech and DNA. However, it is not scalable to massive datasets due ...
Makoto Yamada, Masashi Sugiyama, Gordon Wichern, T...