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AAAI
2011
12 years 7 months ago
Logistic Methods for Resource Selection Functions and Presence-Only Species Distribution Models
In order to better protect and conserve biodiversity, ecologists use machine learning and statistics to understand how species respond to their environment and to predict how they...
Steven Phillips, Jane Elith
ALS
2003
Springer
14 years 26 days ago
Not Everything We Know We Learned
This is foremost a methodological contribution. It focuses on the foundation of anticipation and the pertinent implications that anticipation has on learning (theory and experiment...
Mihai Nadin
EMNLP
2008
13 years 9 months ago
Learning with Probabilistic Features for Improved Pipeline Models
We present a novel learning framework for pipeline models aimed at improving the communication between consecutive stages in a pipeline. Our method exploits the confidence scores ...
Razvan C. Bunescu
ESWA
2008
140views more  ESWA 2008»
13 years 7 months ago
Web taxonomy integration with hierarchical shrinkage algorithm and fine-grained relations
We address the problem of integrating web taxonomies from different real Internet applications. Integrating web taxonomies is to transfer instances from a source to target taxonom...
Chia-Wei Wu, Richard Tzong-Han Tsai, Cheng-Wei Lee...
CIKM
2008
Springer
13 years 9 months ago
Learning a two-stage SVM/CRF sequence classifier
Learning a sequence classifier means learning to predict a sequence of output tags based on a set of input data items. For example, recognizing that a handwritten word is "ca...
Guilherme Hoefel, Charles Elkan