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» The Tradeoffs of Large Scale Learning
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PAMI
2010
205views more  PAMI 2010»
13 years 6 months ago
Learning a Hierarchical Deformable Template for Rapid Deformable Object Parsing
In this paper, we address the tasks of detecting, segmenting, parsing, and matching deformable objects. We use a novel probabilistic object model that we call a hierarchical defor...
Long Zhu, Yuanhao Chen, Alan L. Yuille
WWW
2011
ACM
13 years 2 months ago
Parallel boosted regression trees for web search ranking
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...
GECCO
2008
Springer
141views Optimization» more  GECCO 2008»
13 years 9 months ago
Managing team-based problem solving with symbiotic bid-based genetic programming
Bid-based Genetic Programming (GP) provides an elegant mechanism for facilitating cooperative problem decomposition without an a priori specification of the number of team member...
Peter Lichodzijewski, Malcolm I. Heywood
KDD
2009
ACM
164views Data Mining» more  KDD 2009»
14 years 8 months ago
Social influence analysis in large-scale networks
In large social networks, nodes (users, entities) are influenced by others for various reasons. For example, the colleagues have strong influence on one's work, while the fri...
Jie Tang, Jimeng Sun, Chi Wang, Zi Yang
CONEXT
2010
ACM
13 years 6 months ago
Optimal content placement for a large-scale VoD system
IPTV service providers offering Video-on-Demandcurrently use servers at each metropolitan office to store all the videos in their library. With the rapid increase in library sizes...
David Applegate, Aaron Archer, Vijay Gopalakrishna...