PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Project summary

The PASCAL Network of Excellence has created a distributed institute pioneering principled methods of pattern analysis, statistical modeling, and computational learning as core enabling technologies for multimodal interfaces that are capable of natural and seamless interaction with and among individual human users. The resulting expertise has been applied to problems relevant to both multi-modal interfaces and cognitive systems. PASCAL2 will enable a refocusing of the Institute towards the emerging challenges created by the ever expanding applications of adaptive systems technology and their central role in the development of large scale cognitive systems. Furthermore, the funding will enable the Institute to engage in technology transfer through an Industrial Club to effect rapid deployment of the developed technologies into a wide variety of applications, while undertaking a brokerage of expertise and public outreach programme to communicate the value and relevance of the achieved results.


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Latest Publications

Learning unknown graphs Nicolò Cesa-Bianchi, Claudio Gentile and Fabio Vitale Conference or Workshop Item Item not available online. (2009)
Probabilistic Non-negative Tensor Factorisation using Markov Chain Monte Carlo Mikkel Schmidt and Shakir Mohamed Conference or Workshop Item (August 2009)
Large Scale Non-parametric Inference: Data Parallelisation in the Indian Buffet Process Finale Doshi, David Knowles, Shakir Mohamed and Zoubin Ghahramani Conference or Workshop Item (December 2009)
Analysis of SVM with indefinite kernels Yiming Ying, Colin Campbell and Mark Girolami Conference or Workshop Item Item not available online. (December 2009)
Sparse Metric Learning via Smooth Optimization Yiming Ying, Kaizhu Huang and Colin Campbell Conference or Workshop Item Item not available online. (December 2009)
Learnability of Gaussians with Flexible Variances Yiming Ying and Ding-Xuan Zhou Article Item not available online. (February 2007)