Estimating the rate at which events happen has been studied under various guises and in different settings. We are interested in the specific case of consumerinitiated events or t...
We present a novel probabilistic multiple cause model for binary observations. In contrast to other approaches, the model is linear and it infers reasons behind both observed and ...
Mining feedback information from user click-through data is an important issue for modern Web retrieval systems in terms of architecture analysis, performance evaluation and algor...
Rongwei Cen, Yiqun Liu, Min Zhang, Bo Zhou, Liyun ...
Recent research in frequent pattern mining (FPM) has shifted from obtaining the complete set of frequent patterns to generating only a representative (summary) subset of frequent ...
We propose an approach for learning visual models of object categories in an unsupervised manner in which we first build a large-scale complex network which captures the interacti...