This work presents a kernel method for clustering the nodes of a weighted, undirected, graph. The algorithm is based on a two-step procedure. First, the sigmoid commute-time kernel...
We study a general algorithm to improve accuracy in cluster analysis that employs the James-Stein shrinkage effect in k-means clustering. We shrink the centroids of clusters towar...
Gradient Boosted Regression Trees (GBRT) are the current state-of-the-art learning paradigm for machine learned websearch ranking — a domain notorious for very large data sets. ...
Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal...
Finding similar structures from 3-D structure databases of proteins is becoming more and more important issue in the post-genomic molecular biology. To compare 3-D structures of tw...
Density biased sampling (DBS) has been proposed to address the limitations of Uniform sampling, by producing the desired probability distribution in the sample. The ease of produc...