Dependent types are useful for statically checking detailed specifications of programs and detecting pattern match or array bounds errors. We propose a novel approach to applicatio...
We study the inference on the interesting association rules. Then we define the concept of the representative basis for interesting association rules extracted from a dataset D, a...
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. Effective models of human dynamics can be learned from motion capture data usi...
Most learning algorithms for undirected graphical models require complete inference over at least one instance before parameter updates can be made. SampleRank is a rankbased lear...
Sameer Singh, Limin Yao, Sebastian Riedel, Andrew ...
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...