Reinforcement learning is an effective technique for learning action policies in discrete stochastic environments, but its efficiency can decay exponentially with the size of the ...
Pictorial structure (PS) models are extensively used for part-based recognition of scenes, people, animals and multi-part objects. To achieve tractability, the structure and param...
In practice, learning from data is often hampered by the limited training examples. In this paper, as the size of training data varies, we empirically investigate several probabil...
—Much of previous attention on decision trees focuses on the splitting criteria and optimization of tree sizes. The dilemma between overfitting and achieving maximum accuracy is ...
This study applies Auto Regressive (AR) and Auto Regressive Moving Average (ARMA) modeling to wavelet decomposed terahertz pulsed signals to assist biomedical diagnosis and mail/p...
Bradley Ferguson, Brian Wai-Him Ng, Derek Abbott, ...