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» Listwise approach to learning to rank: theory and algorithm
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NIPS
2003
13 years 10 months ago
Online Learning via Global Feedback for Phrase Recognition
We present a system to recognize phrases based on perceptrons, and a global online learning algorithm to train them together. The recognition strategy applies learning in two laye...
Xavier Carreras, Lluís Màrquez
VIP
2003
13 years 10 months ago
Optimal Selection of Image Segmentation Algorithms Based on Performance Prediction
Using different algorithms to segment different images is a quite straightforward strategy for automated image segmentation. But the difficulty of the optimal algorithm selection ...
Yong Xia, David Dagan Feng, Rongchun Zhao
WWW
2011
ACM
13 years 4 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...
CIKM
2001
Springer
14 years 1 months ago
Merging Techniques for Performing Data Fusion on the Web
Data fusion on the Web refers to the merging, into a unified single list, of the ranked document lists, which are retrieved in response to a user query by more than one Web search...
Theodora Tsikrika, Mounia Lalmas
ALDT
2009
Springer
207views Algorithms» more  ALDT 2009»
14 years 3 months ago
Anytime Self-play Learning to Satisfy Functional Optimality Criteria
We present an anytime multiagent learning approach to satisfy any given optimality criterion in repeated game self-play. Our approach is opposed to classical learning approaches fo...
Andriy Burkov, Brahim Chaib-draa