This paper presents a recommendation algorithm that performs a query dependent random walk on a k-partite graph constructed from the various features relevant to the recommendatio...
Haibin Cheng, Pang-Ning Tan, Jon Sticklen, William...
In this paper, we introduce an assumption which makes it possible to extend the learning ability of discriminative model to unsupervised setting. We propose an informationtheoreti...
Median-shift is a mode seeking algorithm that relies on
computing the median of local neighborhoods, instead of
the mean. We further combine median-shift with Locality
Sensitive...
We present a probabilistic model for a document corpus that combines many of the desirable features of previous models. The model is called “GaP” for Gamma-Poisson, the distri...
Abstract. Feature Extraction, also known as Multidimensional Scaling, is a basic primitive associated with indexing, clustering, nearest neighbor searching and visualization. We co...