While large data sets have enabled machine learning algorithms to act intelligently in complex domains, standard machine learning algorithms perform poorly in situations in which little data exists for the desired target ...

Semantic analysis is a core area of natural language understanding that has typically focused on predicting domain-independent representations. However, such representations are unable to fully realize the rich diversity ...

This thesis addresses the tasks of place discovery and place recognition - learning and recognizing places significant to a user - by analyzing GPS location and GSM cell tower data collected from the user's mobile phone. ...

In medical image analysis, registration is necessary to establish spatial correspondences across two or more images. Registration is rarely the end-goal, but instead, the results of image registration are used in other ...

Movement recorded from motion capture can be decomposed along two separate dimensions. It can be divided into shorter units of motion with respect to time. Secondly, a movement can also be decomposed into a base motion and ...

We develop a method for extracting and internalizing web site form submissions which we refer to as web operations. To begin the process, a user performs a sample submission of the form. From that submission, our system ...

One of the classical goals of research in artificial intelligence is to construct systems that automatically recover the meaning of natural language text. Machine learning methods hold significant potential for addressing ...

I describe a semi-supervised regression algorithm that learns to transform one time series into another time series given examples of the transformation. I apply this algorithm to tracking, where one transforms a time ...

Before we can create intelligent systems that exhibit the versatility of the human intellect, we must understand how our command of language enables the uniquely broad scope of our reasoning ability. To pursue such an ...