We pose partitioning a b-bit Internet Protocol (IP) address space as a supervised learning task. Given (IP, property) labeled training data, we develop an IP-specific clustering a...
Sentiment classification aims to automatically predict sentiment polarity (e.g., positive or negative) of users publishing sentiment data (e.g., reviews, blogs). Although traditio...
We present a vision based, adaptive, decision theoretic model of human facial displays in interactions. The model is a partially observable Markov decision process, or POMDP. A POM...
The goal in domain adaptation is to train a model using labeled data sampled from a domain different from the target domain on which the model will be deployed. We exploit unlabel...
Latent semantic indexing (LSI) is a well-known unsupervised approach for dimensionality reduction in information retrieval. However if the output information (i.e. category labels...