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ICMLA
2009
15 years 4 months ago
A Syllable-Level Probabilistic Framework for Bird Species Identification
In this paper, we present new probabilistic models for identifying bird species from audio recordings. We introduce the independent syllable model and consider two ways of aggregat...
Balaji Lakshminarayanan, Raviv Raich, Xiaoli Fern
KELSI
2004
Springer
15 years 12 months ago
Multiple-Instance Case-Based Learning for Predictive Toxicology
Predictive toxicology is the task of building models capable of determining, with a certain degree of accuracy, the toxicity of chemical compounds. Machine Learning (ML) in general...
Eva Armengol, Enric Plaza
SAC
2009
ACM
16 years 1 months ago
Evaluating algorithms that learn from data streams
In the past years, the theory and practice of machine learning and data mining have been focused on static and finite data sets from where learning algorithms generate a static m...
João Gama, Pedro Pereira Rodrigues, Raquel ...
ICMLA
2008
15 years 8 months ago
Target Selection: A New Learning Paradigm and Its Application to Genetic Association Studies
In this work, a new learning paradigm called target selection is proposed, which can be used to test for associations between a single genetic variable and a multidimensional, qua...
Johannes Mohr, Sambu Seo, Imke Puis, Andreas Heinz...
AAAI
2011
14 years 6 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