Abstract. We propose a thresholded ensemble model for ordinal regression problems. The model consists of a weighted ensemble of confidence functions and an ordered vector of thres...
This paper proposes a learning scheme based still image super-resolution reconstruction algorithm. Superresolution reconstruction is proposed as a binary classification problem an...
A number of supervised learning methods have been introduced in the last decade. Unfortunately, the last comprehensive empirical evaluation of supervised learning was the Statlog ...
Attributed graphs are increasingly more common in many application domains such as chemistry, biology and text processing. A central issue in graph mining is how to collect inform...
Abstract We present a new ranking algorithm that combines the strengths of two previous methods: boosted tree classification, and LambdaRank, which has been shown to be empiricall...
Qiang Wu, Christopher J. C. Burges, Krysta Marie S...