The effort necessary to construct labeled sets of examples in a supervised learning scenario is often disregarded, though in many applications, it is a time-consuming and expensi...
The kernel Perceptron is an appealing online learning algorithm that has a drawback: whenever it makes an error it must increase its support set, which slows training and testing ...
To contribute to HCI investigation and interface design that develops interactive systems for creative solutions, I attempt to formulate a model of the human capability to combine...
In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
Basis functions derived from an undirected graph connecting nearby samples from a Markov decision process (MDP) have proven useful for approximating value functions. The success o...