We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
We compare the purposes, inputs, representations, and assumptions of three methods to evaluate the fine-grained interactions of intelligent tutors with their students. One method i...
Standard optical flow methods for motion or disparity estimation use a brightness constancy constraint equation (BCCE). This BCCE either handles a moving camera imaging a non-movi...
Most of the work which attempts to give bounds on the generalization error of the hypothesis generated by a learning algorithm is based on methods from the theory of uniform conve...
The use of multiple features by a classifier often leads to a reduced probability of error, but the design of an optimal Bayesian classifier for multiple features is dependent on t...