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KDD
2007
ACM
192views Data Mining» more  KDD 2007»
15 years 10 months ago
Active exploration for learning rankings from clickthrough data
We address the task of learning rankings of documents from search engine logs of user behavior. Previous work on this problem has relied on passively collected clickthrough data. ...
Filip Radlinski, Thorsten Joachims
KDD
2005
ACM
158views Data Mining» more  KDD 2005»
15 years 10 months ago
Adversarial learning
Many classification tasks, such as spam filtering, intrusion detection, and terrorism detection, are complicated by an adversary who wishes to avoid detection. Previous work on ad...
Daniel Lowd, Christopher Meek
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
15 years 10 months ago
Query chains: learning to rank from implicit feedback
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
Filip Radlinski, Thorsten Joachims
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
15 years 4 months ago
Learning noise
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Michael D. Schmidt, Hod Lipson
ECLIPSE
2006
ACM
15 years 3 months ago
A focused learning environment for Eclipse
The support available in Eclipse to help software developers learn complex APIs and development tools is inadequate; the support is largely passive and the support typically opera...
Izzet Safer, Gail C. Murphy, Julie Waterhouse, Jin...