Creating and sharing knowledge for telecommunications

Workshop on Quantum Effects in Biological Systems QuEBS 2009

on 07-07-2009

... The identification and study of quantum mechanical phenomena in biological systems is an emerging area of interdisciplinary research spanning physics, chemistry, biology, and quantum information science. In this workshop, we intend to explore the interplay between quantum coherence and environmental effects in both driven and undriven biomolecular systems. In particular, the role of quantum dynamical coherence and decoherence in excitonic energy transfer within chromophoric systems, such as photosynthetic complexes, will be addressed.

Moreover, the existence of quantum entanglement in the dynamics of such systems will also be discussed. Furthermore, this workshop could provide new insight for engineering artificial photosystems, such as quantum dots and dendrimers, to achieve optimal energy transport by exploiting their environmental effects, with potential applications for the development of more efficient solar cells or photosensors.

The workshop will be constituted by both invited and contributed talks, and will include plenty of time for brainstorming and discussions on this novel area.

QuEBS 2009 is the second edition of the Lisbon Quantum Computation, Information and Logic biennial meetings, an initiative of the Security and Quantum Information Group, Instituto de Telecomunicações. The workshop will take place in Lisbon, Portugal.

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Unsupervised Learning: From Single Clustering to Ensemble Methods

on 09-04-2009

... Tutorial: Unsupervised Learning: From Single Clustering to Ensemble Methods

Presenter: Prof. Ana Fred

Date: April 9 2009, 13h-16h

Location: Room 11.26, 11th floor, North Tower, Instituto Superior Técnico

Topics addressed:
1. Basic Concepts of data clustering
1.1 Problem formulation
1.2 Taxonomies of Clustering Techniques
1.3. Difficulties and open problems
2. Clustering Algorithms
2.1 Hierarchical Methods (Single-link; Complete link; Dissimilarity Increments)
2.2 Partitional Methods (K-means; Spectral Clustering; EM Gaussian Mixture Decomposition)
3. Validation of Custering Solutions
3.1. Cluster Validity Measures
4. Clustering Ensemble Methods
4.1. Basic Formulation
4.2. Evidence Accumulation Clustering (EAC)
4.3. Multi-Criteria EAC
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