155 search results - page 7 / 31 » On learning linear ranking functions for beam search |
AIPS
2008
13 years 10 months ago
2008
Planning problems are often formulated as heuristic search. The choice of the heuristic function plays a significant role in the performance of planning systems, but a good heuris...
CIKM
2010
Springer
13 years 6 months ago
2010
Springer
Traditional machine-learned ranking algorithms for web search are trained in batch mode, which assume static relevance of documents for a given query. Although such a batch-learni...
CIKM
2009
Springer
14 years 2 months ago
2009
Springer
Traditional boosting algorithms for the ranking problems usually employ the pairwise approach and convert the document rating preference into a binary-value label, like RankBoost....
GECCO
2009
Springer
14 years 2 months ago
2009
Springer
This paper presents an approach to automatically optimize the retrieval quality of ranking functions. Taking a Swarm Intelligence perspective, we present a novel method, SwarmRank...
ACSW
2004
13 years 9 months ago
2004
This paper describes an approach to the use of gradient descent search in genetic programming (GP) for object classification problems. In this approach, pixel statistics are used ...