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KDD
2009
ACM
191views Data Mining» more  KDD 2009»
14 years 8 months ago
Scalable pseudo-likelihood estimation in hybrid random fields
Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
Antonino Freno, Edmondo Trentin, Marco Gori
CORR
2008
Springer
107views Education» more  CORR 2008»
13 years 7 months ago
Our Brothers' Keepers: Secure Routing with High Performance
The Trinity [1] spam classification system is based on a distributed hash table that is implemented using a structured peer-to-peer overlay. Such an overlay must be capable of proc...
Alex Brodsky, Scott Lindenberg
BMCBI
2010
70views more  BMCBI 2010»
13 years 7 months ago
The Text-mining based PubChem Bioassay neighboring analysis
Background: In recent years, the number of High Throughput Screening (HTS) assays deposited in PubChem has grown quickly. As a result, the volume of both the structured informatio...
Lianyi Han, Tugba O. Suzek, Yanli Wang, Steve H. B...
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
14 years 8 months ago
Using graph-based metrics with empirical risk minimization to speed up active learning on networked data
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
Sofus A. Macskassy
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 7 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal