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» Approximation Algorithms for Scheduling on Multiple Machines
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ACL
2008
13 years 9 months ago
Pairwise Document Similarity in Large Collections with MapReduce
This paper presents a MapReduce algorithm for computing pairwise document similarity in large document collections. MapReduce is an attractive framework because it allows us to de...
Tamer Elsayed, Jimmy J. Lin, Douglas W. Oard
HEURISTICS
2006
197views more  HEURISTICS 2006»
13 years 7 months ago
Bucket elimination for multiobjective optimization problems
Multiobjective optimization deals with problems involving multiple measures of performance that should be optimized simultaneously. In this paper we extend bucket elimination (BE),...
Emma Rollon, Javier Larrosa
NIPS
2007
13 years 9 months ago
Sparse Feature Learning for Deep Belief Networks
Unsupervised learning algorithms aim to discover the structure hidden in the data, and to learn representations that are more suitable as input to a supervised machine than the ra...
Marc'Aurelio Ranzato, Y-Lan Boureau, Yann LeCun
ICML
2008
IEEE
14 years 8 months ago
On the quantitative analysis of deep belief networks
Deep Belief Networks (DBN's) are generative models that contain many layers of hidden variables. Efficient greedy algorithms for learning and approximate inference have allow...
Ruslan Salakhutdinov, Iain Murray
MOBIHOC
2008
ACM
14 years 7 months ago
On exploiting diversity and spatial reuse in relay-enabled wireless networks
Relay-enabled wireless networks (eg. WIMAX 802.16j) represent an emerging trend for the incorporation of multi-hop networking solutions for last-mile broadband access in next gene...
Karthikeyan Sundaresan, Sampath Rangarajan