Many real-world domains present the problem of imbalanced data sets, where examples of one classes significantly outnumber examples of other classes. This makes learning difficu...
This paper explores the use of alternating sequential patterns of local features and saccading actions to learn robust and compact object representations. The temporal encoding rep...
Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
Abstract. We present a survey of recent results concerning the theoretical and empirical performance of algorithms for learning regularized least-squares classifiers. The behavior ...
We consider the task of learning to accurately follow a trajectory in a vehicle such as a car or helicopter. A number of dynamic programming algorithms such as Differential Dynami...
J. Zico Kolter, Adam Coates, Andrew Y. Ng, Yi Gu, ...