Kevin Scaman

ML researcher at INRIA Paris.

[Centre Inria de Paris @inria_paris]

#Article 📰 | Comment repérer des communautés sur les #RS ? Comment garder le contrôle de ses données sur le #web ? Des questions auxquelles la nouvelle équipe ARGO (@Inria/@ENS_ULM) tente de répondre en alliant #algorithmique des #graphes et #ML.
Lire 👉 https://t.co/YMNhEW1P8I

[Sebastien Bubeck @SebastienBubeck]

The Chomsky et al. opinion piece in the @nytimes about ChatGPT is making the rounds. Rather than trying to deconstruct their argument, I asked @bing what it thinks of it.

Now you can judge for yourself who has the moral high ground 😂.

[Marc Lelarge 🌻 @marc_lelarge]

𝗣𝗿𝗼𝗯𝗹𝗲𝗺𝘀 𝘄𝗶𝘁𝗵 𝗴𝗿𝗮𝗱𝗶𝗲𝗻𝘁 𝗱𝗲𝘀𝗰𝗲𝗻𝘁 𝗮𝗻𝗱 𝘀𝘆𝗺𝗺𝗲𝘁𝗿𝘆
If the loss has symmetry, several solutions are equally good, and to converge to the 'right' solution, gradient descent needs additional information.
👇 a simple example below 👇

[Marc Lelarge 🌻 @marc_lelarge]

𝗡𝗮𝗺𝗲𝗱 𝗧𝗲𝗻𝘀𝗼𝗿𝘀 allow users to give explicit names to tensor dimensions.
Named Tensor Notation by @davidweichiang @srush_nlpand @boazbaraktcs are super convenient. Here is a simple transformer encoder block!
👉https://t.co/hHavtr04JQ

[Sophia Sanborn @naturecomputes]

Our workshop on Symmetry and Geometry in Neural Representations has been accepted to @NeurIPSConf 2022!

We've put together a lineup of incredible speakers and panelists from 🧠 neuroscience, 🤖 geometric deep learning, and 🌐 geometric statistics.

[George Dasoulas @GDasoulas]

Today at 8 pm (CEST), I am presenting our work with @giannis_nikole, @KevinScaman, @Monoideabelien, @mvazirg on "Ego-based entropy measures for structural representations on graphs" to #ICASSP2021!
Tune in here: https://t.co/2D9FxE1x38

Proceedings: https://t.co/5ZC3q5h1n3

[Marc Lelarge 🌻 @marc_lelarge]

Understanding convolutional neural networks from first principles. A great opportunity to learn about circulant matrices, shift-equivariant layers, discrete Fourier transform, CNNs, receptive field... and play with @JuliaLanguage
All the details here👇
https://t.co/P5ifI6nhTJ

[George Dasoulas @GDasoulas]

Our work "Lipschitz Normalization for Self-Attention Layers with Application to Graph Neural Networks" has been accepted as a short talk to #ICML2021!
Thanks @Monoideabelien @KevinScaman for the great collaboration!

Check out our paper for more details!
https://t.co/YPhP2TS1hB

[Balázs Kégl @balazskegl]

Please join us tomorrow at 7AM CET for presentations of the 11 @Huawei papers at #NeurIPS2020. The last two papers are from my team @HuaweiFR. @KevinScaman @LDosSantos_ @lgorcolin @merwanbarlier Cedric Malherbe

https://t.co/yd7oc0Zq7f
Conference ID: 579 711 3087
Password: 790071

[Moreau Thomas @tomamoral]

Choosing the best algorithm to solve an optimization problem IN PRACTICE depends a lot on the data/parameters/implementation/etc.

An objective selection needs time consuming benchmarks. This can now be done easily and together on GitHub with BenchOpt!

https://t.co/VGfIAWHAtI

[Francis Bach @BachFrancis]

If you like Gaussian kernels and distributions, you will enjoy this month blog post on Hermite polynomials!
https://t.co/Mgr1sjPhSy

[Ludovic Dos Santos @LDosSantos_]

Please to announce that our paper "A Simple and Efficient Smoothing Method for Accelerated Optimization and Local Exploration" has been accepted to #NeurIPS2020 🥳
Co-authors @lgorcolin @KevinScaman @MerwanBarlier

[Ludovic Dos Santos @LDosSantos_]

#IJCAI proceedings are online. Check out our paper "Coloring Graph Neural Networks for Node Disambiguation" introducing an universal approximator of continuous functions on graphs.

Paper https://t.co/2EVs03Fk1U
With George Dasoulas @Monoideabelien @KevinScaman