Abstract. Distributing process-oriented programs across a cluster of machines requires careful attention to the effects of network latency. The MPI standard, widely used for cluste...
We consider the semi-supervised learning problem, where a decision rule is to be learned from labeled and unlabeled data. In this framework, we motivate minimum entropy regulariza...
The process of learning models from raw data typically requires a substantial amount of user input during the model initialization phase. We present an assistive visualization sys...
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
Modern embedded systems often require high degrees of instruction-level parallelism (ILP) within strict constraints on power consumption and chip cost. Unfortunately, a high-perfo...