Channel-aware scheduling and link adaptation (LA) methods are widely considered to be crucial for realizing high data rates in wireless networks. Multi-carrier systems that spread...
Sampling is a popular way of scaling up machine learning algorithms to large datasets. The question often is how many samples are needed. Adaptive stopping algorithms monitor the ...
Finding the core members of a virtual community is an important problem in community analysis. Here we presented an simulated annealing algorithm to solve this problem by optimizi...
We present two modifications to the popular k-means clustering algorithm to address the extreme requirements for latency, scalability, and sparsity encountered in user-facing web...
We study online nonclairvoyant speed scaling to minimize total flow time plus energy. We first consider the traditional model where the power function is P(s) = sα . We give a ...
Ho-Leung Chan, Jeff Edmonds, Tak Wah Lam, Lap-Kei ...