Chunyang Xiao defence

Chunyang Xiao has succesfully defended his Ph.D. thesis last Thursday: congratulations ! link

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job

Intership + Ph.D. available

URGENT We have two positions available in the field of deep learning applied to NLP: One Ph.D. funded by ITEA/FUI PAPUD project One internship of 5 months likely followed by a Ph.D. co-supervised with PagesJaunes Rennes Please send us your CV as soon as possible at cerisara …

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git

How to migrate git repos onto gitlab

It's possible to automatically create a repository on gitlab, without using any web interface, thanks to gitlab API. In order to use the gitlba API, you must first create a "secret token" that authenticates your script when it connects to gitlab API. You can create such a token from your …

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PAPUD project accepted

The new ITEA3 project PAPUD has been accepted and is funded by FUI, thanks to the efforts of Samuel Cruz-Lara: thank you @Samuel ! We are thrilled to be part of it and to start working on this challenging topic. If you have or plan to obtain a Ph.D. in …

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Welcome to our new members !

LORIA news After welcoming Denis Paperno and Bart Lamiroy a few months ago, we are very glad to welcome Chloé Braud and Yannick Parmentier as new permanent members in our team ! Welcome !

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FAQ Synalp website

Here is a small FAQ about the website: Q: How do I add a new post ? See this tuto Q: I've added a post; how do I check it is OK ? After modifying the web site, it is best practice to check that the web site is still compiling before …

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Team meetings

Some team meetings: Thursday August, 31st at 10 AM in room B011. It will feature a discussion about the new team website and a presentation of its current status. Thursday October, 5th at 10:30 in A008 Wednesday October, 18th at 10:45 in B011. Denis' talk

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New team website

A first complete version of the new Synalp website is available. Come to the next team meeting (2017/08/31) for an overview :-) Should be able to be deployed after every push

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Experimental evaluation with cross-validation

It is extremely easy to make methodological mistakes when evaluating some machine learning system and comparing it with others. Especially when using cross-validation ! A must-read paper about this topic is: On Over-fitting in model selection and subsequent selection bias in performance evaluation So even though you are short of time …

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