Kernel machines have recently been considered as a promising solution for implicit surface modelling. A key challenge of machine learning solutions is how to fit implicit shape mo...
Tree-structured probabilistic models admit simple, fast inference. However, they are not well suited to phenomena such as occlusion, where multiple components of an object may dis...
We present a simple and efficient entropy coder that combines run-length and Golomb-Rice encoders. The encoder automatically switches between the two modes according to simple rul...
We propose a robust circuit-based Boolean Satisfiability (SAT) solver, QuteSAT, that can be applied to complex circuit netlist structure. Several novel techniques are proposed in ...
The objective of data reduction is to obtain a compact representation of a large data set to facilitate repeated use of non-redundant information with complex and slow learning alg...