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Accurate modeling of geographic distributions of species is crucial to various applications in ecology and conservation. The best performing techniques often require some parameter tuning, which may be prohibitively time-consuming to do separately for each species, or unreliable for small or biased datasets. Additionally, even with the abundance of good(More)
Novel methods improve prediction of species' distributions from occurrence data. Á/ Ecography 29: 129 Á/151. Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on(More)
We study the problem of modeling species geographic distributions, a critical problem in conservation biology. We propose the use of maximum-entropy techniques for this problem, specifically, sequential-update algorithms that can handle a very large number of features. We describe experiments comparing maxent with a standard distribution-modeling tool,(More)
Most methods for modeling species distributions from occurrence records require additional data representing the range of environmental conditions in the modeled region. These data, called background or pseudo-absence data, are usually drawn at random from the entire region, whereas occurrence collection is often spatially biased toward easily accessed(More)
We present a unified and complete account of maximum entropy density estimation subject to constraints represented by convex potential functions or, alternatively, by convex regularization. We provide fully general performance guarantees and an algorithm with a complete convergence proof. As special cases, we easily derive performance guarantees for many(More)
One of the oldest and simplest variants of multiprocessor scheduling is the on-line scheduling problem studied by Graham in 1966. In this problem, the jobs arrive on-line and must be scheduled non-preemptively on m identical machines so as to minimize the makespan. The size of a job is known on arrival. Graham proved that the List Processing Algorithm which(More)
We consider the problem of estimating an unknown probability distribution from samples using the principle of maximum entropy (maxent). To alleviate overfitting with a very large number of features, we propose applying the maxent principle with relaxed constraints on the expectations of the features. By convex duality, this turns out to be equivalent to(More)
We introduce a new way of measuring and optimizing connectivity in conservation landscapes through time, accounting for both the biological needs of multiple species and the social and financial constraint of minimizing land area requiring additional protection. Our method is based on the concept of network flow; we demonstrate its use by optimizing(More)
The inheritance of obesity has been analyzed in an intercross between the lean 129/Sv mouse strain and the obesity-prone EL/Suz mouse strain. The weights of three major fat pads were determined on 4-month-old mice, and the sum of these weights, divided by body weight, was used as an adiposity index. The strategy of selective DNA pooling was used as a(More)