We explore the problem of budgeted machine learning, in which the learning algorithm has free access to the training examples’ labels but has to pay for each attribute that is s...
Kun Deng, Chris Bourke, Stephen D. Scott, Julie Su...
Abstract. For large state-space Markovian Decision Problems MonteCarlo planning is one of the few viable approaches to find near-optimal solutions. In this paper we introduce a new...
When equipped with kernel functions, online learning algorithms are susceptible to the "curse of kernelization" that causes unbounded growth in the model size. To addres...
: This paper proposes twin prototype support vector machine (TVM), a constant space and sublinear time support vector machine (SVM) algorithm for online learning. TVM achieves its ...