Abstract. We address the problem of selecting a subset of the most relevant features from a set of sample data in cases where there are multiple (equally reasonable) solutions. In ...
We present a new method to estimate the intrinsic dimensionality of a submanifold M in Rd from random samples. The method is based on the convergence rates of a certain U-statisti...
We propose a feature selection method that constructs each new feature by analysis of tight error clusters. This is a greedy, time-efficient forward selection algorithm that itera...
This paper gives an algorithm for detecting and reading text in natural images. The algorithm is intended for use by blind and visually impaired subjects walking through city scen...
We propose an efficient sampling based outlier detection method for large high-dimensional data. Our method consists of two phases. In the first phase, we combine a "sampling...
Timothy de Vries, Sanjay Chawla, Pei Sun, Gia Vinh...