Abstract— This paper proposes a simulation-based active policy learning algorithm for finite-horizon, partially-observed sequential decision processes. The algorithm is tested i...
Ruben Martinez-Cantin, Nando de Freitas, Arnaud Do...
In recent years, spectral clustering method has gained attentions because of its superior performance compared to other traditional clustering algorithms such as K-means algorithm...
We use a reliably annotated corpus to compare metrics of coherence based on Centering Theory with respect to their potential usefulness for text structuring in natural language ge...
Nikiforos Karamanis, Massimo Poesio, Chris Mellish...
My research attempts to address on-line action selection in reinforcement learning from a Bayesian perspective. The idea is to develop more effective action selection techniques b...
Understanding complex 3D virtual models can be difficult, especially when the model has interior components not initially visible and ancillary text. We describe new techniques fo...
Henry Sonnet, M. Sheelagh T. Carpendale, Thomas St...