Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
Many researchers see the need for reject inference in credit scoring models to come from a sample selection problem whereby a missing variable results in omitted variable bias. Al...
It is well known that many hard tasks considered in machine learning and data mining can be solved in a rather simple and robust way with an instanceand distance-based approach. In...
While many interesting dynamic load balancing schemes have been proposed for efficient use of limited bandwidth and to increase the capacity of congested or hot spots (or cells) in...
Abstract— In this paper, we develop a coded MIMO FHCDMA transceiver that is robust to partial-band jamming and the near-far problem for ad hoc networks with high mobility. Spatia...