A new approach to ensemble learning is introduced that takes ranking rather than classification as fundamental, leading to models on the symmetric group and its cosets. The approa...
A machine learning technique for handling scenarios of interaction between conflicting agents is suggested. Scenarios are represented by directed graphs with labeled vertices (for ...
Boris Galitsky, Sergei O. Kuznetsov, Mikhail V. Sa...
Training principles for unsupervised learning are often derived from motivations that appear to be independent of supervised learning. In this paper we present a simple unificatio...
Active learning [1] is a branch of Machine Learning in which the learning algorithm, instead of being directly provided with pairs of problem instances and their solutions (their l...
We explore algorithms for learning classification procedures that attempt to minimize the cost of misclassifying examples. First, we consider inductive learning of classification ...
Michael J. Pazzani, Christopher J. Merz, Patrick M...