Biclustering refers to simultaneous clustering of objects and their features. Use of biclustering is gaining momentum in areas such as text mining, gene expression analysis and co...
Alok N. Choudhary, Arifa Nisar, Waseem Ahmad, Wei-...
Our proposal has the following key features: 1) The separation of a distributed program into a pure algorithm (PurAl) and a distribution/communication declaration (DUAL). This yie...
Raphael B. Yehezkael, Yair Wiseman, H. G. Mendelba...
—With the exponential growth in the amount of data that is being generated in recent years, there is a pressing need for applying machine learning algorithms to large data sets. ...
Open-text semantic parsers are designed to interpret any statement in natural language by inferring a corresponding meaning representation (MR – a formal representation of its s...
Antoine Bordes, Xavier Glorot, Jason Weston, Yoshu...
We proposed compressive data gathering (CDG) that leverages compressive sampling (CS) principle to efficiently reduce communication cost and prolong network lifetime for large scal...