Domain adaptation is an important problem in natural language processing (NLP) due to the lack of labeled data in novel domains. In this paper, we study the domain adaptation prob...
We present our efforts to create a large-scale, semi-automatically annotated parallel corpus of cleft constructions. The corpus is intended to reduce or make more effective the ma...
Crowdsourcing has recently become popular among machine learning researchers and social scientists as an effective way to collect large-scale experimental data from distributed w...
Mobile usage patterns often entail high and fluctuating levels of difficulty as well as dual tasking. One major theme explored in this research is whether a flexible multimodal in...
Sharon L. Oviatt, Rachel Coulston, Rebecca Lunsfor...
Many modern visual recognition algorithms incorporate a step of spatial `pooling', where the outputs of several nearby feature detectors are combined into a local or global `...