In this paper, we propose GAD (General Activity Detection) for fast clustering on large scale data. Within this framework we design a set of algorithms for different scenarios: (...
Jiawei Han, Liangliang Cao, Sangkyum Kim, Xin Jin,...
We propose to solve the combinatorial problem of finding the highest scoring Bayesian network structure from data. This structure learning problem can be viewed as an inference pr...
Tommi Jaakkola, David Sontag, Amir Globerson, Mari...
Background: Agglomerative hierarchical clustering (AHC) is a common unsupervised data analysis technique used in several biological applications. Standard AHC methods require that...
We propose a new approach to library-based technology mapping, based on the method of logical effort. Our algorithm is close to optimal for fanout-free circuits, and is extended t...
Simulation optimization (SO) is the process of finding the optimum design of a system whose performance measure(s) are estimated via simulation. We propose some ideas to improve o...