We propose a new framework for supervised machine learning. Our goal is to learn from smaller amounts of supervised training data, by collecting a richer kind of training data: an...
Many real world datasets are represented in the form of graphs. The classical graph properties found in the data, like cliques or independent sets, can reveal new interesting info...
The development of high-throughput genome sequencing and protein structure determination techniques have provided researchers with a wealth of biological data. Integrated analysis...
William M. Shui, Raymond K. Wong, Stephen C. Graha...
Determining the occurrence of an event is fundamental to developing systems that can observe and react to them. Often, this determination is based on collecting video and/or audio...
Dmitry N. Zotkin, Ramani Duraiswami, Larry S. Davi...
Discrete-event simulation models typically have stochastic components that mimic the probabilistic nature of the system under consideration. Successful input modeling requires a c...