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Spectral Algorithms for learning Hidden Markov Models

In this seminar I will talk about the work of Hsu and Kakade (2009) on spectral methods for leaning a Hidden Markov Model (HMM). I will introduce and exemplify this method and describe how we can estimate the best set … Read More

Speech Translation: Modeling and Conversion of speaking style across languages

In this talk I will describe our recent efforts within the PT-STAR project for speech translation across languages. I will begin with brief descriptions about the component systems for speech recognition, machine translation and speech synthesis and talk in greater … Read More

Privacy enhancement in biometrics

Biometrics, as an authentication tool, provides several advantages over conventional what you know (e.g., password, PIN) and what you possess (e.g., keys, tokens) authentication methods. However, a biometrics is an irrevocable password as we can’t change the biometrics easily. If … Read More

Semantics and Fitness Landscapes in Genetic Programming

Moraglio et al. have recently introduced new genetic operators for genetic programming, called geometric semantic operators. It is possible to prove that these operators induce a unimodal fitness landscape for all the problems consisting in matching input data with known … Read More

Effects of Wifi Internet Usage on Academic Performance in a University Setting

The Internet is an essential tool but can be disruptive distraction. Using wifi usage and student grade data from the Faculdade de Engeneharia da Universidade do Porto (FEUP) in Portugal, we find a consistent, positive correlation between Internet usage and … Read More

Exploratory EEG Analysis Using Clustering and Phase-Locking Factor

Emotion recognition is essential for psychological and psychiatric applications and for improving the quality of human-machine interaction. Therefore, a simple and reliable method is needed to automatically assess the emotional state of a subject. This paper presents an application of … Read More

Towards automatic identification of independent components representing EEG artifacts

Independent component analysis (ICA) is a blind source separation technique that allows the separation of linear mixtures of signals into maximal statistically independent sources, normally called independent components (ICs). This technique relies on several mathematical assumptions which need to be … Read More

Cross-Language Alignments: Challenges, Guidelines and Gold Sets

In this presentation I will describe the key cross-language annotation guidelines to provide support for state-of-the art machine translation systems. The guidelines aim at improving the quality of the statistical machine translation output by using linguistically-informed and motivated annotation of … Read More

Modeling Subcellular Location from Images and Other Sources of Information

Subcellular location is an important property of proteins, carefully regulated by the cell machinery. To determine subcellular location on a proteome-wide scale, fluorescent image data is most commonly used and a classification system is employed for analysis. These systems assign … Read More

A New Approach to Cross-Modal Multimedia Retrieval

The problem of cross-modal retrieval from multimedia repositories is considered. This problem addresses the design of retrieval systems that support queries across content modalities, e.g. using text to search for images. A mathematical formulation is proposed, equating the design of … Read More