On-line boosting allows to adapt a trained classifier to changing environmental conditions or to use sequentially available training data. Yet, two important problems in the on-li...
Helmut Grabner, Horst Bischof, Jan Sochman, Jiri M...
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
Abstract: An emerging practice in e-commerce systems is to conduct interviews with buyers in order to identify their needs. The goal of such an interview is to determine sets of pr...
Sequential change diagnosis is the joint problem of detection and identification of a sudden and unobservable change in the distribution of a random sequence. In this problem, the...
Savas Dayanik, Christian Goulding, H. Vincent Poor
There is an ongoing explosion of interactive Internet applications. By nature, these applications require responsive clientserver data exchange and lossless, in-order delivery. In...