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IJAIT
2007
119views more  IJAIT 2007»
15 years 18 days ago
Minimizing the makespan for Unrelated Parallel Machines
In this paper, we study the unrelated parallel machine problem for minimizing the makespan, which is NP-hard. We used Simulated Annealing (SA) and Tabu Search (TS) with Neighborho...
Yunsong Guo, Andrew Lim, Brian Rodrigues, Liang Ya...
118
Voted
IPPS
2010
IEEE
14 years 10 months ago
Large neighborhood local search optimization on graphics processing units
Local search (LS) algorithms are among the most powerful techniques for solving computationally hard problems in combinatorial optimization. These algorithms could be viewed as &q...
Thé Van Luong, Nouredine Melab, El-Ghazali ...
114
Voted
SC
2005
ACM
15 years 6 months ago
A Scalable Distributed Parallel Breadth-First Search Algorithm on BlueGene/L
Many emerging large-scale data science applications require searching large graphs distributed across multiple memories and processors. This paper presents a distributed breadth...
Andy Yoo, Edmond Chow, Keith W. Henderson, Will Mc...
SIGMOD
2012
ACM
203views Database» more  SIGMOD 2012»
13 years 3 months ago
Optimizing index for taxonomy keyword search
Query substitution is an important problem in information retrieval. Much work focuses on how to find substitutes for any given query. In this paper, we study how to efficiently ...
Bolin Ding, Haixun Wang, Ruoming Jin, Jiawei Han, ...
WWW
2011
ACM
14 years 7 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...