El cambio climático, su gestión y mitigación, constituye sin duda uno de los elementos de riesgo más importantes que afrontará nuestra sociedad en las próximas décadas. El sector financiero desempeña un papel fundamental en este reto, tanto por su exposición y las consiguientes...

Climate change and its management and mitigation are unquestionably among the main risks facing our society in the coming decades. The financial sector plays a key role in this challenge, firstly because of its exposure and the consequent capital shocks if this risk crystallises, and secondly...

Any major research institution has a substantial number of computer systems on its campus, often in the scale of tens of thousands. Given that a large amount of scientific computing is appropriate for execution in an opportunistic environment, a campus grid is an inexpensive way to build a...

The study of complex systems should be based on a systems-theoretic framework which requires both self-organizing and symbolic dimensions. An inclusive framework based on the notion of semiotics is advanced to build models capable of representing, as well as evolving in their environments, with...

We identify a general framework for weak planning called bootstrap planning, which is defined as global planning using only a local planner along with some memory for learning intermediate subgoals. We present a family of algorithms for bootstrap planning, and provide some initial theory on...

When large numbers of alerts are reported by intrusion detection (ID) systems in very fine granularity, it prevents system administrators from handling the alerts effectively. This in turn degrades the usability of an intrusion detection system. Aside from detection, timely responses of...

Machine learning has become one of the most active and exciting areas of computer science research, in large part because of its wide-spread applicability to problems as diverse as natural language processing, speech recognition, spam detection, search, computer vision, gene discovery, medical...

Following the events of September 11, 2001, many in the American public falsely believe they must choose between safety and privacy. This paper proposes an approach to technology (termed “Selective Revelation”) that allows data to be shared for surveillance purposes such that shared data...

We describe a class of sparse latent factor models, called graphical factor models (GFMs), and relevant sparse learning algorithms for posterior mode estimation. Linear, Gaussian GFMs have sparse, orthogonal factor loadings matrices, that, in addition to sparsity of the implied covariance...

The research presented here focuses on modeling machine-learning performance. The thesis introduces Seer, a system that generates empirical observations of classification-learning performance and then uses those observations to create statistical models. The models can be used to predict the...