We consider the problem of detecting a large number of different classes of objects in cluttered scenes. Traditional approaches require applying a battery of different classifier...
Antonio Torralba, Kevin P. Murphy, William T. Free...
Machine-learning algorithms are employed in a wide variety of applications to extract useful information from data sets, and many are known to suffer from superlinear increases in ...
Karthik Nagarajan, Brian Holland, Alan D. George, ...
For large scale automatic semantic video characterization, it is necessary to learn and model a large number of semantic concepts. These semantic concepts do not exist in isolatio...
We develop a high dimensional nonparametric classification method named sparse additive machine (SAM), which can be viewed as a functional version of support vector machine (SVM)...
Autonomous agents that learn about their environment can be divided into two broad classes. One class of existing learners, reinforcement learners, typically employ weak learning ...