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...
This paper presents a new way of thinking for IR metric optimization. It is argued that the optimal ranking problem should be factorized into two distinct yet interrelated stages:...
It is important for any data language that it enables many people to derive correct information from a databases in a simple, effective way with predictable performance. In an ana...
We present a novel method for predicting the secondary structure of a protein from its amino acid sequence. Most existing methods predict each position in turn based on a local wi...
Scott C. Schmidler, Jun S. Liu, Douglas L. Brutlag
— In this paper we present a general framework for predicting the positioning uncertainty of underwater vehicles. We apply this framework to common examples from marine robotics:...