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CORR
2010
Springer
153views Education» more  CORR 2010»
14 years 11 months ago
GraphLab: A New Framework for Parallel Machine Learning
Designing and implementing efficient, provably correct parallel machine learning (ML) algorithms is challenging. Existing high-level parallel abstractions like MapReduce are insuf...
Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny B...
JMLR
2010
136views more  JMLR 2010»
14 years 5 months ago
Reducing Label Complexity by Learning From Bags
We consider a supervised learning setting in which the main cost of learning is the number of training labels and one can obtain a single label for a bag of examples, indicating o...
Sivan Sabato, Nathan Srebro, Naftali Tishby
KDD
2012
ACM
292views Data Mining» more  KDD 2012»
13 years 1 months ago
Online allocation of display ads with smooth delivery
Display ads on the Internet are often sold in bundles of thousands or millions of impressions over a particular time period, typically weeks or months. Ad serving systems that ass...
Anand Bhalgat, Jon Feldman, Vahab S. Mirrokni
BMCBI
2007
207views more  BMCBI 2007»
14 years 11 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...
ICDM
2006
IEEE
153views Data Mining» more  ICDM 2006»
15 years 5 months ago
k-STARs: Sequences of Spatio-Temporal Association Rules
A Spatio-Temporal Association Rule (STAR) describes how objects move between regions over time. Since they describe only a single movement between two regions, it is very difficu...
Florian Verhein