A 11.ª temporada dos seminários de aprendizagem automática com almoço grátis patrocinados pela Priberam teve início no dia 18 do mês passado.
Por norma, os seminários decorrem quinzenalmente às terças-feiras, das 13h às 14h, no campus da Alameda do Instituto Superior Técnico, mas, em tempo de COVID-19, os seminários irão ocorrer remotamente, por videoconferência (via Zoom), com a mesma periodicidade.
Contrariamente ao que é habitual, os almoços não serão fornecidos, mas fique à vontade para trazer o seu e almoçar ao mesmo tempo que assiste ao seminário!
Os interessados podem inscrever-se aqui ou obter mais informação aqui.
Há 10 anos que a Priberam disponibiliza seminários e almoços grátis!
Hoje decorre mais uma sessão da décima temporada dos seminários de aprendizagem automática patrocinados pela Priberam, a decorrer agora na primeira e na terceira quinta-feira de cada mês, das 13h às 14h, no anfiteatro PA2 (piso -1, Pavilhão de Matemática) do campus da Alameda do Instituto Superior Técnico.
Os seminários são encontros informais que permitem a apresentação e a discussão de vários tópicos relacionados com a aprendizagem automática (machine learning, em inglês) e disponibilizam uma refeição grátis a todos os participantes inscritos.
Mais informação aqui (em inglês).
A nona temporada de seminários de aprendizagem automática patrocinados pela Priberam, a decorrer quinzenalmente às terças-feiras, das 13h às 14h, no campus da Alameda do Instituto Superior Técnico, tem início no próximo dia 20 deste mês.
Os seminários são encontros informais que permitem a apresentação e a discussão de vários tópicos relacionados com a aprendizagem automática (machine learning, em inglês) e disponibilizam uma refeição grátis a todos os participantes inscritos.
Mais informação aqui (em inglês).
Pelo oitavo ano consecutivo, a Priberam patrocina encontros informais que promovem o diálogo entre a academia e a indústria sobre diversas áreas relacionadas com a aprendizagem automática ( machine learning, em inglês), como processamento de sinais, visão computacional, processamento em linguagem natural, redes neurais artificiais, biologia computacional, etc.
Os seminários são gratuitos, realizam-se quinzenalmente, à terça-feira, das 13h às 14h, no campus da Alameda do Instituto Superior Técnico, e disponibilizam uma refeição grátis a todos os participantes inscritos.
Mais informação aqui (em inglês).
Pelo sétimo ano consecutivo, a Priberam patrocina encontros informais que promovem a divulgação e o debate entre a academia e a indústria em diversas áreas relacionadas com a aprendizagem automática ( machine learning, em inglês).
Os seminários são gratuitos (não é necessária inscrição), realizam-se quinzenalmente, à terça-feira, das 13h às 14h, no campus da Alameda do Instituto Superior Técnico e disponibilizam uma refeição grátis aos participantes.
Mais informação aqui (em inglês).
Amanhã, dia 28, tem início a sexta temporada dos Priberam Machine Learning Seminars. Pelo sexto ano consecutivo, a Priberam patrocina estes encontros informais que promovem a divulgação e o debate entre a academia e a indústria em diversas áreas relacionadas com a aprendizagem automática ( machine learning, em inglês).
O primeiro seminário estará a cargo de Michael Unser, professor e director do Laboratório de Imagem Biomédica, da Escola Politécnica Federal de Lausana.
A periodicidade dos seminários mantém-se quinzenal, à terça-feira, das 13h às 14h, no campus da Alameda do Instituto Superior Técnico. Os seminários estão abertos a todos os que queiram participar (não é necessária inscrição) e disponibilizam uma refeição grátis aos participantes. Mais informação aqui (em inglês).
Começa hoje a quinta temporada dos Priberam Machine Learning Seminars, um espaço que promove a divulgação e o debate entre a academia e a indústria em diversas áreas relacionadas com a aprendizagem automática ( machine learning).
A periodicidade dos seminários mantém-se quinzenal, à terça-feira, das 13h às 14h, no campus da Alameda do Instituto Superior Técnico. Os seminários estão abertos a todos os que queiram participar (não é necessária inscrição) e disponibilizam uma refeição grátis aos participantes. Mais informação (em inglês), aqui.
Os seminários, patrocinados pela Priberam, decorrem quinzenalmente à terça-feira, das 13h às 14h, no campus da Alameda do Instituto Superior Técnico (edifício de pós-graduação, sala PA2). Estão abertos a todos os que queiram participar (não é necessária inscrição) e disponibilizam uma refeição grátis aos participantes. Mais informação (em inglês), aqui.
Os interessados em assistir ou em fazer uma apresentação podem subscrever a lista de contactos enviando um email para seminarios-mlpb-request@freelists.org com “Subscribe” no campo 'Assunto' ou visitando a página da lista em http://www.freelists.org/list/seminarios-mlpb. A discussão relativa à organização dos seminários e ao calendário das apresentações será feita através da lista. Todas as sugestões são bem-vindas!
 Priberam Machine Learning Lunch Seminar Speaker: Ramon Astudillo (INESC-ID) Venue: IST Alameda, Sala PA2 (Edifício de Pós-Graduação) Date: Tuesday, March 6th, 2012 Time: 13:00 Lunch will be provided Title: Integration of Fourier Domain Speech Enhancement and Automatic Speech Recognition through Uncertainty Propagation Abstract: Speech enhancement techniques aim to recover the original clean signal underlying corrupted speech. Such techniques typically operate in the short-time Fourier transform (STFT) domain where phenomena like additivity of background noises, interfering speakers and echoes are easier to model. By contrast, automatic speech recognition (ASR), and in general most speech-related machine learning applications, operate on feature spaces that are non-linear transformations of the STFT. The reason for this is that such spaces provide a more compact representation of the acoustic space, the space of all acoustic realizations for a given task, and thus lead to simpler models. This talk discusses the integration of STFT speech enhancement and ASR using the concept of uncertainty propagation and decoding. This will include conventional speech enhancement in STFT domain, its associated uncertainty and various closed-form solutions for propagation into domains suitable for ASR.
 Priberam Machine Learning Lunch Seminar Speaker: Miguel Almeida (IST/UTL and Aalto University, Finland) Venue: IST Alameda, Sala PA2 (Edifício de Pós-Graduação) Date: Tuesday, January 24th, 2012 Time: 13:00 Lunch will be provided Title: SSS: Separation of Synchronous Sources Abstract: The problem of separating synchronous sources (SSS) is a case of blind source separation (BSS) where independence of the sources is not satisfied. In SSS, the sources are assumed to be complex-valued, and different sources are phase-locked, which means that the relative phase lag between two sources is not uniform in [0,2*pi[. For this reason, the typical independent component analysis (ICA) tools are theoretically not applicable, and experiments show that they perform poorly in this task. In the SSS model, we assume that the phase lag between any two sources is constant. The only important assumption regarding the amplitudes of the sources is linear independence, although some nice results can be proven if the amplitudes are statistically independent. In this talk, I'll start by briefly discussing ICA, since it is relatively familiar in the Machine Learning community. I will then formulate the problem of SSS and detail the similarities and differences to the ICA problem. Afterwards, I will present two algorithms that were developed to tackle this problem, along with some nice theoretical properties of those algorithms. We will visit some very simple optimization problems and a little bit of complex algebra. Nothing complicated, I promise! I will finalize by presenting some simulated results, on 1) data which exactly follows the SSS model, and 2) data which deviates from the SSS model. -- Bio: Miguel Almeida is currently a joint PhD student at IST-UTL, Portugal, and at Aalto University (AU), Finland (formerly Helsinki University of Technology), under joint supervision of Prof. José Bioucas-Dias (IST), Prof. Ricardo Vigário (AU), and Prof. Erkki Oja (AU). He started his doctoral project in 2008 and spent the first two years of his PhD at AU. He has been at IST since 2010, and plans to finish his degree in the first semester of 2012. His PhD topic revolves around the SSS problem, and fits under the general topic of Machine Learning. More specifically, this project involves considerable amounts of Signal Processing and Optimization. Miguel holds an MSc in Physics and Technology Engineering (IST, 2006) and an advanced post-graduate degree in Biophysics (FC-UL, 2007).
 A terceira série de seminários sobre aprendizagem automática ( machine learning), patrocinados pela Priberam, tem início no próximo dia 10 de Janeiro. O principal objectivo destes seminários é possibilitar um espaço de divulgação e de debate entre a academia e a indústria nas áreas científicas em que operam (aprendizagem automática, processamento de língua natural, robótica, etc.). Para além de contrariar a ideia de que os percursos das universidades e das empresas não se cruzam, esta iniciativa pretende ainda estreitar laços entre os diferentes grupos de investigação. Os seminários decorrem quinzenalmente à terça-feira, às 13h, no campus da Alameda do Instituto Superior Técnico (edifício de pós-graduação, sala PA2), são gratuitos e abertos a todos os que queiram participar (não é necessária inscrição). Mais informação, aqui. Os interessados em assistir ou em fazer uma apresentação podem subscrever a lista de contactos enviando um email para seminarios-mlpb-request@freelists.org com “Subscribe” no campo 'Assunto' ou visitando a página da lista em http://www.freelists.org/list/seminarios-mlpb. A discussão relativa à organização dos seminários e calendário das apresentações terá lugar na lista. Todas as sugestões são bem-vindas! Como nas edições anteriores, os seminários disponibilizam uma refeição grátis servida aos participantes.
 Priberam Machine Learning Lunch Seminar Speaker: Kalyanmoy Deb (http://www.iitk.ac.in/kangal/deb.htm) Host: Sara Silva (KDBIO/INESC-ID) Venue: IST Alameda, Sala Qa1.3 (Torre Sul) ***NOTE SPECIAL VENUE!*** Date: Monday, April 4th, 2011 ***NOTE SPECIAL DATE!*** Time: 12:00 ***NOTE SPECIAL TIME!*** Lunch will be provided Title: Innovization: Revealing Innovative Design Principles through Multi-Objective Optimization Abstract: Designing a component, process or a control system to achieve minimum or maximum of a single objective (or goal) often results in a single optimum solution describing the shape, dimensions, process or strategy of solving the task. Although such an optimized solution may already provide a new and innovative way of achieving the best objective value, it is almost never the case that practitioners are solely interested in a single objective. Moreover, a single optimum solution does not often provide adequate information to *learn* much about the problem, a matter which is ideally desired in engineering and scientific problem-solving tasks. In this seminar, we shall discuss an "innovization" procedure involving a multi-objective optimization algorithm for finding a set of trade-off optimal solutions. An investigation of such solutions is then expected to reveal useful design principles common to high-performing solutions. A number of interesting engineering case studies will be discussed to demonstrate how useful and innovative design principles can be deciphered by considering two or three-objective optimization problems. Such design innovations are difficult to achieve by any other means and the proposed systematic procedure should find a wide-spread applicability in the coming years. -- Bio: Kalyanmoy Deb is currently a Professor of Mechanical Engineering at Indian Institute of Technology Kanpur, India and is the director of Kanpur Genetic Algorithms Laboratory (KanGAL). He is the recipient of the prestigious Shanti Swarup Bhatnagar Prize in Engineering Sciences for the year 2005. He is a fellow of Indian National Science Academy (INSA), Indian National Academy of Engineering (INAE), Indian National Academy of Sciences (IASc), and International Society of Genetic and Evolutionary Computation (ISGEC). He has received Fredrick Wilhelm Bessel Research award from Alexander von Humboldt Foundation, Germany in 2003. His main research interests are in the area of optimization, optimal modeling and design and evolutionary algorithms. He has written two text books on optimization and more than 275 international journal and conference research papers. He is associated with 17 international journals. He has pioneered and a leader in the field of evolutionary multi-objective optimization. More information about his research can be found from http://www.iitk.ac.in/kangal/deb.htm.
 Priberam Machine Learning Lunch Seminar Speaker: André Lourenço (IT) Venue: IST Alameda, Sala PA2 (Edifício de Pós-Graduação) Date: Tuesday, March 29th, 2011 Time: 13:00 Lunch will be provided Title: Towards a Finger Based ECG Biometric System Abstract: The electrocardiographic (ECG) signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this talk we review the state of the art on using ECG as biometric trait. We present a finger based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. -- Bio: André Lourenço is a phd student of Electrical and Computer Engineering at IST-IT (Instituto Superior Técnico – Instituto de Telecomunicações), under the supervision of prof. Ana Fred. He is also assistant professor at ISEL (Instituto Superior de Engenharia de Lisboa). His main research interests are pattern recognition and machine learning.
 Priberam Machine Learning Lunch Seminar Speaker: Jorge Marques (ISR) Venue: IST Alameda, Sala EA3 (Torre Norte) Date: Tuesday, March 15th, 2011 Time: 13:00 Lunch will be provided Title: Project ARGUS: Characterizing People Activities Using Multiple Motion Fields Abstract: Surveillance systems aim to characterize human activities and to detect abnormal behaviors. This task is specially challenging if the camera field of view is wide and the objects are far from the camera. In such operating conditions, it is not possible to extract detailed descriptions of the objects such as shape and color. In this case, most of the information is conveyed by the object trajectory and motion parameters. We therefore need to characterize trajectories and to be able to discriminate normal from abnormal behaviors. This talk presents a new representation for human activity analysis based on multiple motion fields, equipped with space-varying switching mechanisms. We will show that this description is flexible and intuitive. The model parameters have a meaning and they can be used to understand how people behave in a scene. Parameter estimation will be addressed using the EM method and several extensions will be discussed. -- Bio: Jorge Marques received the Ph.D degree and Aggregation title in Electrical and Computer Engineering from IST. He is currently with the department of Electrical and Computer Engineering, IST, where he is Associate Professor. His research interests are in the area of Image Processing and Pattern Recognition.
 Priberam Machine Learning Lunch Seminar Speaker: Artur Ferreira (IT/ISEL) Venue: IST Alameda, Sala PA2 (Edifício de Pós-Graduação) Date: Tuesday, March 1st, 2011 Time: 13:00 Lunch will be provided Title: Unsupervised feature discretization and selection for sparse data Abstract: In many applications, we deal with high dimensional datasets with sparse data (many features have zero value with high probability). For instance, in text classification and information retrieval problems, we have large collections of documents. Each text is usually represented by a bag-of-words or similar representation, with a large number of features (terms). Many of these features may be irrelevant (or even detrimental) for the learning tasks. This excessive number of features carries the problem of memory usage in order to represent and deal with these collections, clearly showing the need for adequate methods for feature representation, reduction, and selection, to both improve the classification accuracy and the memory requirements for the storage of these datasets. This talk focuses on techniques for unsupervised Feature Discretization (FD) and Feature Selection (FS). The proposed FD technique uses the Lloyd-Max algorithm along with a new criterion for FS based on the discretized features. The FS methods rely on the use of dispersion measures to compute feature relevance. The recent topic of compressed learning (CL), i.e., learning in a domain of reduced dimensionality obtained by random projections (RP) is explored under the framework of feature reduction. We show some experimental results on standard datasets. -- Bio: Artur Ferreira is adjunct professor at ISEL (Instituto Superior de Engenharia de Lisboa) and a PhD student of Electrical and Computer Engineering at IST-IT (Instituto Superior Técnico – Instituto de Telecomunicações), under the supervision of prof. Mário Figueiredo. He holds a MSc on Electrical and Computer Engineering by IST. His main research interests are data compression, pattern recognition and machine learning
Priberam Machine Learning Lunch Seminar
Speaker: Andras Hartmann (INESC-ID)
Venue: IST Alameda, Sala PA2 (Edifício de Pós-Graduação)
Date: Tuesday, November 2nd, 2010
Time: 13:00
Lunch will be provided
Title: "Mind The Gap: Reconstruction of missing cardiovascular signals using adaptive filtering"
Abstract:
In this talk I will introduce a robust method for filling in short missing segments in multiparameter Intensive Care Unit cardiovascular data. This work was inspired by the ``PhysioNet/Computing in Cardiology Challenge 2010: Mind the Gap''.
The interconnections between the signals were identified in the form of composite IIR transfer functions using the signals' history. A genetic algorithm was applied for inferring the filter coefficients. Assuming that the connections do not vary in time, we managed to reconstruct the missing signals using the yet available parallel measured signals and the transfer functions.
The results are promising, as this method achieved the 5th place among 53 participants of the challenge. We concluded that this approach can be efficient in reconstructing and even detecting missing or corrupted cardiovascular signals or other type of datasets with several modalities and strong interconnections between them.
--
Bio: András Hartmann received his MSc degree from Budapest University of Technology and Economics in Information Systems and Computational Engineering with specialization in software design in 2005. In 2008 he gained his MSc, this time in Biomedical Engineering in a joint program of Semmelweis Medical University and Budapest University of Technology and Economics. Since July 2009 he is a member of the INESC-ID KDBIO Group, working on the project DynaMo - Dynamical modeling, control and optimization of metabolic networks.
He is interested in modeling complex biological and physiological systems, in particular: identification and dynamic modeling of metabolic networks; spatial and temporal connectivity in human brain; and dynamic modeling of cardiovascular system.
 Depois do sucesso da primeira série de seminários sobre aprendizagem automática ( machine learning), propostos pelo investigador André Martins e patrocinados pela Priberam, é já na próxima terça-feira, dia 2 de Novembro, que começa a segunda temporada. Os seminários decorrem quinzenalmente à terça-feira, às 13h, no campus da Alameda do Instituto Superior Técnico (edifício de pós-graduação, sala PA2), são gratuitos e abertos a todos os que queiram participar (não é necessária inscrição). Mais informação, aqui. Os interessados podem subscrever a lista de contactos enviando um email para seminarios-mlpb-request@freelists.org com “subscribe” no campo 'Assunto' ou visitando a página da lista em http://www.freelists.org/list/seminarios-mlpb. A discussão relativa à organização dos seminários e calendário das apresentações terá lugar na lista. Todas as sugestões são bem-vindas! E porque estes seminários também são conhecidos pela qualidade da comida grátis servida aos participantes, aqui fica o menu para a próxima terça-feira: - panini vegetariano ou focaccia de frango fumado - mascarpone com framboesa - sumo natural
Priberam Machine Learning Lunch Seminar
Speaker: Ricardo Vigário (Aalto University School of Science and Technology, Finland)
Venue: IST Alameda, Sala EA4 (Torre Norte)
Date: Friday, July 2nd, 2010
Time: 13:00
Lunch will be provided
Title: "From elements to networks of neuronal activity – a machine learning approach"
Abstract:
Neuroinformatics “combines neuroscience and the information sciences to develop and apply advanced tools for a major advancement in understanding the structure and function of the brain.” After introducing the speaker’s neuroinformatics research group, we will address issues related to the use and misuse of independent component analysis.
Departing from the traditionally simple evoked response paradigm, into the more natural neurocinematics one, also the neuronal responses are expected to take on rather complex network configurations. We will review two approaches to identify such communication strategies. In a functional magnetic resonance imaging setup, the first one is a hierarchical method, and assumes the existence of basic focal activation areas, which are combined to account for the complex neuronal responses.
Additional information is gathered directly from the stimuli. The second uses phase synchrony as the acting principle for the extraction of communication/control in high temporal resolution data, such as electro- and magnetoencephalograms.
Bio: Ricardo Vigário, D.Sc., is a docent and senior researcher at the Aalto University School of Science and Technology, Finland, where he teaches and leads a research group in Neuroinformatics. He has a basic degree in Applied Physics and a M.Sc. in Biomedical Engineering from the Faculty of Sciences of the University of Lisbon and a D.Sc. (tech) in Computer Science from the Helsinki University of Technology (current Aalto University), from 1992, 1994 and 1999, respectively. He has held a Marie Curie post-doctoral position in GMD – FIRST, Germany; was a visiting lecturer in Graz, Austria and Zaragoza, Spain; and a visiting associate professor in Grenoble, France. He was a pioneer in the independent component analysis of electrophysiological data. His fields of interest include statistical machine learning; the analysis of neuronal responses to natural stimuli; and various communication strategies within the central
nervous system.
 Priberam Machine Learning Lunch Seminar Speaker: João Graça (L2F, INESC-ID) Venue: IST Alameda, Sala PA2 (Edifício de Pós-Graduação) Date: Tuesday, June 22th, 2010 Time: 13:00 Lunch will be provided Title: "Posterior Regularization Framework: Learning Tractable Models with Intractable Constraints" Abstract: Unsupervised Learning of probabilistic structured models presents a fundamental trade- off between richness of captured constraints and correlations versus efficiency and tractability of inference. In this thesis, we propose a new learning framework called Posterior Regulariza- tion that incorporates side-information into unsupervised estimation in the form of constraints on the model’s posteriors. The underlying model remains unchanged, but the learning method changes. During learning, our method is similar to the EM algorithm, but we solve a problem similar to Maximum Entropy inside the E-Step to enforce the constraints. We apply the PR framework to two different large scale tasks: Statistical Word Alignments and Unsupervised Part of Speech Induction. In the former, we incorporate two constraints: bijectivity and symme- try. Training using these constraints produces a significant boost in performance as measured by both precision and recall against manually annotated alignments for six language pairs. In the latter we enforce sparsity on the word tag distribution which is overestimated using the default training method. Experiments on six languages achieve dramatic improvements over state-of-the-art results. Bio: I am currently a 4th year PhD student (with MSc degree) in Computer Science Engineering at Instituto Superior Técnico, Technical University of Lisbon and a visiting student at University of Pennsylvania. My advisors are Luisa Coheur, Fernando Pereira and Ben Taskar. My main research interests are Machine Learning and Natural Language Processing. My current focus in on unsupervised learning with high level supervision in the form of constraints. I am a proud member of the Spoken Language Systems Lab (L2F) in Lisbon and of the Penn Research in Machine Learning (PRiML).
O título deste post já foi usado várias vezes neste mesmo blogue para anunciar os seminários de aprendizagem automática patrocinados pela Priberam, a decorrer quinzenalmente no Instituto Superior Técnico. Hoje é novamente usado, a propósito da notícia publicada no Jornal de Negócios sobre investigação e parcerias internacionais entre universidades e empresas. 
Para os mais distraídos, ou para quem só reparou nos propalados almoços grátis (sim, há almoços grátis!), o principal objectivo destes seminários, propostos pelo investigador da Priberam André Martins, é possibilitar um espaço de divulgação e de debate entre a academia e a indústria nas áreas científicas em que operam (aprendizagem automática, processamento de língua natural, robótica, etc.). Para além de contrariar a ideia de que os percursos das universidades e das empresas não se cruzam, esta iniciativa pretende ainda estreitar laços entre os diferentes grupos de investigação. Nem que seja pela partilha de brownies ao almoço.
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