The problem of time series classification has attracted great interest in the last decade. However current research assumes the existence of large amounts of labeled training data...
Training a system to recognize handwritten words is a task that requires a large amount of data with their correct transcription. However, the creation of such a training set, inc...
The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
Abstract. People-centric sensor-based applications targeting mobile device users offer enormous potential. However, learning inference models in this setting is hampered by the lac...
Nicholas D. Lane, Hong Lu, Shane B. Eisenman, Andr...
Many approaches to active learning involve periodically training one classifier and choosing data points with the lowest confidence. An alternative approach is to periodically cho...