We propose a fast iterative classification algorithm for Kernel Fisher Discriminant (KFD) using heterogeneous kernel models. In contrast with the standard KFD that requires the us...
We consider learning in a Markov decision process where we are not explicitly given a reward function, but where instead we can observe an expert demonstrating the task that we wa...
A number of reinforcement learning algorithms have been developed that are guaranteed to converge to the optimal solution when used with lookup tables. It is shown, however, that ...
Performance profiling consists of monitoring a software system during execution and then analyzing the obtained data. There are two ways to collect profiling data: event tracing t...
Edu Metz, Raimondas Lencevicius, Teofilo F. Gonzal...
We provide approximate expressions for the covariance matrix of kinetic parameter estimators based on time activity curve (TAC) reconstructions when TACs are modeled as a linear c...
Sangtae Ahn, Jeffrey A. Fessler, Thomas E. Nichols...