A fundamental assumption often made in supervised classification is that the problem is static, i.e. the description of the classes does not change with time. However many practi...
It has been widely observed that different NLP applications require different sense granularities in order to best exploit word sense distinctions, and that for many applications ...
Rion Snow, Sushant Prakash, Daniel Jurafsky, Andre...
We present a method for unsupervised discovery of abnormal occurrences of activities in multi-dimensional time series data. Unsupervised activity discovery approaches differ from ...
Several applications would emerge from the development of efficient and robust sound classification systems able to identify the nature of non-speech sound sources. This paper prop...
Mauricio Kugler, Victor Alberto Parcianello Benso,...
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...