Train local experts to help conserve forests
نویسندگان
چکیده
منابع مشابه
Using Relevance to Train a Linear Mixture of Experts
A linear mixture of experts is used to combine three standard IR systems. The parameters for the mixture are determined automatically through training on document relevance assessments via optimization of a rank-order statistic which is empirically correlated with average precision. The mixture improves performance in some cases and degrades it in others, with the degradations possibly due to t...
متن کاملCan retention forestry help conserve biodiversity? A meta-analysis
Industrial forestry typically leads to a simplified forest structure and altered species composition. Retention of trees at harvest was introduced about 25 years ago to mitigate negative impacts on biodiversity, mainly from clearcutting, and is now widely practiced in boreal and temperate regions. Despite numerous studies on response of flora and fauna to retention, no comprehensive review has ...
متن کاملMixing Carrots and Sticks to Conserve Forests in the Brazilian Amazon: A Spatial Probabilistic Modeling Approach
Annual forest loss in the Brazilian Amazon had in 2012 declined to less than 5,000 sqkm, from over 27,000 in 2004. Mounting empirical evidence suggests that changes in Brazilian law enforcement strategy and the related governance system may account for a large share of the overall success in curbing deforestation rates. At the same time, Brazil is experimenting with alternative approaches to co...
متن کاملEnsemble Learning with Local Experts
Ensemble learning methods have received considerable attention in the past few years. Various methods for combining several learning experts have been developed and used in different domains of machine learning. Many works have focused on decision fusion of different exports. Some methods try to train all the experts on the same training data and then use statistical techniques to combine the r...
متن کاملAdaptive Mixtures of Local Experts
We present a new supervised learning procedure for systems composed of many separate networks, each of which learns to handle a subset of the complete set of training cases. The new procedure can be viewed either as a modular version of a multilayer supervised network, or as an associative version of competitive learning. It therefore provides a new link between these two apparently different a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Nature
سال: 2012
ISSN: 0028-0836,1476-4687
DOI: 10.1038/481443b