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ICML
1995
IEEE
16 years 7 months ago
Ant-Q: A Reinforcement Learning Approach to the Traveling Salesman Problem
In this paper we introduce Ant-Q, a family of algorithms which present many similarities with Q-learning (Watkins, 1989), and which we apply to the solution of symmetric and asymm...
Luca Maria Gambardella, Marco Dorigo
KDD
2004
ACM
158views Data Mining» more  KDD 2004»
16 years 6 months ago
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...
STOC
2006
ACM
166views Algorithms» more  STOC 2006»
16 years 6 months ago
New upper and lower bounds for randomized and quantum local search
Local Search problem, which finds a local minimum of a black-box function on a given graph, is of both practical and theoretical importance to combinatorial optimization, complexi...
Shengyu Zhang
SIGMOD
2004
ACM
166views Database» more  SIGMOD 2004»
16 years 6 months ago
Fast Computation of Database Operations using Graphics Processors
We present new algorithms on commodity graphics processors to perform fast computation of several common database operations. Specifically, we consider operations such as conjunct...
Naga K. Govindaraju, Brandon Lloyd, Wei Wang 0010,...
PODS
2005
ACM
115views Database» more  PODS 2005»
16 years 6 months ago
A divide-and-merge methodology for clustering
We present a divide-and-merge methodology for clustering a set of objects that combines a top-down "divide" phase with a bottom-up "merge" phase. In contrast, ...
David Cheng, Santosh Vempala, Ravi Kannan, Grant W...