In this paper we study a paradigm to generalize online classification algorithms for binary classification problems to multiclass problems. The particular hypotheses we investig...
Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being...
Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Y...
We prove the strongest known bound for the risk of hypotheses selected from the ensemble generated by running a learning algorithm incrementally on the training data. Our result i...
In this paper, we demonstrate how Functional Reactive Programming (FRP), a framework for the description of interactive systems, can be extended to encompass parallel systems. FRP ...
Classifying the endgame positions in Chess can be challenging for humans and is known to be a difficult task in machine learning. An evolutionary algorithm would seem to be the ide...