MAP-tele Seminars 2014/2015
The MAP-Tele Seminars includes a series of invited talks, and a module on Research Methods on Engineering.
The talks are on telecommunications with an emphasis on Future Internet Technologies.
MAP-Tele Seminars grading takes into account the participation in both the talks and the module.
Talks scheduled for 2014/2015:
1 |
Speaker: João Álvaro Carvalho, UM/Algoritmi
Title: Creating scientific knowledge: challenges to the technological areas (Part I) |
17.10.2014, 11h00 |
2 |
Speaker: Paulo Cortez, UM/Algoritmi
Title: Data mining and computer networks |
24.10.2014, 11h00 |
3 |
Speaker: João Álvaro Carvalho, UM/Algoritmi
Title: Creating scientific knowledge: challenges to the technological areas (Part II) |
31.10.2014, 11h00 |
4 |
Speaker: Pétia Georgieva, UA
Title: Machine learning for Big Data processing |
14.11.2014, 11h15 |
5 |
Speaker: Paulo Ferreira, UA
Title: An introduction to probabilistic methods and network applications |
20.11.2014, 11h15 |
6 |
Speaker: Pétia Georgieva, UA
Title: Artificial neural networks for advanced signal processing |
21.11.2014, 14h30 |
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Seminar 1
Speaker: João Álvaro Carvalho, UM/Algoritmi
Title: Creating scientific knowledge: challenges to the technological areas (Part I)
Abstract:
The seminar addresses
several aspect related to the creation of technological knowledge, namely: the
scientific method - a general process model for the creation of scientific
knowledge - and its adaptation for areas that involve the creation of
technological knowledge; main differences between the research process and the
engineering design process (and other professions that also involve design);
criteria for the validation of technological knowledge; different types of
scientific research; broad view of research methods, i.e., methods for the validation
of scientific knowledge.
Seminar 2
Speaker: Paulo Cortez, UM/Algoritmi
Title: Data mining and computer networks
Abstract:
This seminar starts by
briefly presenting the area of Data Mining. Then, data mining applications to
the computer network field are presented (e.g., Internet Traffic Forecasting,
Spam Email detection using Network Level properties).
Seminar 3
Speaker: João Álvaro Carvalho, UM/Algoritmi
Title: Creating scientific knowledge: challenges to the technological areas (Part II)
Abstract:
The seminar addresses
several aspect related to the creation of technological knowledge, namely: the
scientific method - a general process model for the creation of scientific
knowledge - and its adaptation for areas that involve the creation of
technological knowledge; main differences between the research process and the
engineering design process (and other professions that also involve design);
criteria for the validation of technological knowledge; different types of
scientific research; broad view of research methods, i.e., methods for the
validation of scientific knowledge.
Seminar 4
Speaker: Pétia Georgieva, UA
Title: Machine learning for Big Data processing
Abstract:
Machine Learning (ML) is a
subfield of artificial intelligence that is concerned with the design,
analysis, implementation, and applications of programs that learn from examples
or experience. Learning from data is commercially and scientifically important.
ML consists of methods and respective software that extract automatically
interesting knowledge (patterns, models, relationships) in large databases of
sometimes chaotic and redundant information. ML is a data-based
knowledge-discovering process that has the potential not only to analyze events
in retrospect but also to predict future events or important alterations. The objective of this lecture is to introduce
the PhD students to the research area of ML. The lecture will give a flavor of
Supervised (classification and regression) versus Unsupervised (clustering)
learning paradigms. Distance (similarity) measures, instance based classifiers,
Bayesian statistical learning, and performance evaluation (confusion matrix).
ML applications, such as text mining, image classification, brain data
processing will be discussed.
Seminar 5
Speaker: Paulo Ferreira, UA
Title: An introduction to probabilistic methods and network applications
Abstract:
The
goal of the talk is to overview some of the probabilistic method more often
used in network applications, in a big data context, or in connection with the
web graph. I will discuss probabilistic counting and cardinality estimation and
some of the basic underlying ideas. I will also address set membership
determination and some of its applications in networking. The problem of
estimating the elements of a set as well as their frequencies of occurrence
will also be debated. Finally, some attention will be given to fountain codes
and the probabilistic ideas behind them. The talk will be of interest to
students with a basic knowledge about probability and an interest in topics
such as coding, peer-to-peer networks, big data, data mining, routing, query optimisation,
data summarisation, page ranking and large-scale problems on the web.
Seminar 6
Speaker: Pétia Georgieva, UA
Title: Artificial neural networks for advanced signal processing
Abstract:
Artificial Neural Networks
(ANN) is a computational and engineering methodology whose design is based on
models taken from neurobiology and on the notion of learning, in particular, the
brain's massively parallel and learning aspects. The use of neural networks is becoming
increasingly widespread, with applications in many areas. The objective of this
lecture is to introduce the PhD students to the research area of ANNs and to
some of their most successful applications as in advanced signal processing. The
lecture is going to consider typical ANN architectures (Feedforward ANN, Radial
Basis ANN, Recurrent ANN) and associated computational algorithms for accomplishing
learning (Gradient Descent and Back propagation error correction learning). ANN for classification and regression will also be
discussed.
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