Mischief is a system to support traditional classroom practices between a remote instructor and a group of collocated students. Meant for developing regions, each student in the c...
Neema Moraveji, Taemie Kim, James Ge, Udai Singh P...
In this paper we show how common speech recognition training criteria such as the Minimum Phone Error criterion or the Maximum Mutual Information criterion can be extended to inco...
We present the machine learning framework that we are developing, in order to support explorative search for non-trivial linguistic configurations in low-density languages (langua...
Exponentially growing photo collections motivate the needs for automatic image annotation for effective manipulations (e.g., search, browsing). Most of the prior works rely on sup...
We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in paramet...