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Category Archives: news
Special session in IPIN2021
We are happy to announce that Greg is organising the Special Session "Data Compression, Data Augmentation and Generative Modeling in Indoor Positioning" in the upcoming Indoor Positioning and Indoor Navigation Conference (IPIN2021).
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Kanerva++ at ICLR21
The ICLR21 conference is still a few weeks away but to wet your appetite already, we are glad to let you know that Jason Ramapuram will be presenting there his new paper Kanerva++: Extending the Kanerva Machine With Differentiable, Locally Block Allocated Latent Memory. The paper is a result of a successful collaboration with Yan Wu from Deepmind.
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Tagged conference, ICLR, Jason, Jason Ramapuram, Kanerva++, paper
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PhD Thesis defense of Amina Mollaysa
Amina Mollaysa will defend her PhD Thesis entitled "Structural and Functional Regularization of Deep Learning Models" on Friday 26/02/2021, at 15h00 CET. If you are interested in attending the PhD defence of Amina Mollaysa, please send an email with the title "Thesis defense Mollaysa - Zoom" to alexandros.kalousis@hesge.ch to receive the Zoom link.
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Tagged Amina, Amina Mollaysa, deep leaning, generative modeling, phd, phd in machine learning, Thesis, VAE
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2020 Retrospective
What a year this was...! This retrospective though, won't be about the unprecedented situation that we all went through. We'll take some time to revisit the highlights of our group's activities throughout this year. Let's go!
Papers in NeurIPS 2020
We are very happy to announce that the members of our team have had two accepted papers in NeurIPS 2020!
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Tagged Alexandros Kalousis, Amina, Amina Mollaysa, internships, Jason, Jason Ramapuram, NeurIPS, NIPS, NIPS conference, papers
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Welcome to Naoya
We have the pleasure to welcome Naoya Takeishi as a new postdoc into our team. His expertise and experience with integrating the theoretical understanding of physical systems into machine learning as well as with data-driven analysis of nonlinear dynamical systems is a strong contribution to our research portfolio and we are looking forward to inspiring and enriching discussions and collaborations. Naoya will also reinforce our team in the industrial project IAI: Industrial Artificial Intelligence for intelligent machines and manufacturing digitalization. In addition to all the science he is about to immerse to, we wish he enjoys his stay with us and in Geneva, Switzerland and we hope to learn from him a little more about Japan and its culture. ようこそ!
Statistical Learning Workshop – Tentative program available
The tentative program of the Statistical Learning Workshop, which takes place on-line the whole day of the 18th of September, is now available on the workshop's site http://dmml.ch/statistical-learning-workshop/!
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Tagged invited talk, machine learning, phd student, presentation, statistical learning, Talk, workshop
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SNSF Spark project granted to Dr. Grigorios Anagnostopoulos
We are delighted to announce that Dr. Grigorios Anagnostopoulos has been awarded a funding under the Spark funding scheme of the Swiss Nation Science Foundation (SNSF), for his project "Eratosthenes: Deep generative modeling for indoor and outdoor positioning with fingerprinting methods".
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Tagged eratosthenes, grant, Greg, Grigorios G. Anagostopoulos, project, research project, snsf, spark
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Jason to present DAB
A couple of months ago Jason Ramapuram interned in Apple Machine Learning Research. Among other things, he worked with Russ Webb on a novel method allowing for the use of simple non-differentiable functions at intermediary layers of deep neural networks. … Continue reading
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Tagged collaboration, conference, deep leaning, Jason, Jason Ramapuram, paper, presentation
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Statistical Learning Workshop – 18 September 2020
In this workshop we bring together the research communities of statistics and machine learning to foster a discussion between the two fields and develop research synergies. The workshop takes place on-line the whole day of 18/September. Depending on the COVID-19 status at the time a restricted physical presence version might also take place.
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Tagged invited talk, machine learning, Seminar, statistical learning, statistics, Talk, workshop
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