Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
Neural spike trains present challenges to analytical efforts due to their noisy, spiking nature. Many studies of neuroscientific and neural prosthetic importance rely on a smooth...
John P. Cunningham, Byron M. Yu, Krishna V. Shenoy...
We exploit some useful properties of Gaussian process (GP) regression models for reinforcement learning in continuous state spaces and discrete time. We demonstrate how the GP mod...
We propose Gaussian processes for regression as a novel nonlinear equalizer for digital communications receivers. GPR's main advantage, compared to previous nonlinear estimat...
: Classification methods are vital for efficient access of knowledge hidden in biomedical publications. Support vector machines (SVMs) are modern non-parametric deterministic clas...