2018 Interns hours

We have a special team meeting on Tuesday, 17th of July 2018 dedicated to interns who have joined our team in 2018. Some of them have already left before this date, but we don't forget them even though they won't present their work on this occasion. So thank you to …

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ai

AI labs in France

Map of French AI labs LORIA is leading AI research in the north-east of France... AI labs map

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Chunyang Xiao defence

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

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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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