Romain Tavenard

Prof. @UnivRennes_2.
ML for time series.
Maintainer of #tslearn package

[Romain Tavenard @rtavenar]

Today's blog post deals with the (non-)differentiability of Dynamic Time Warping.

https://t.co/BMc74qoMkc

Feedback is, once again, very welcome!

[Samuel Vaiter @vaiter]

📣 New preprint 📣

**Differentiable Generalized Sliced Wasserstein Plans**

w/
L. Chapel
@rtavenar

We propose a Generalized Sliced Wasserstein method that provides an approximated transport plan and which admits a differentiable approximation.

https://t.co/81C9BGRtko 1/5

[Romain Tavenard @rtavenar]

Come work with us on tslearn in beautiful Rennes!

(deadline for application is soon!)

https://t.co/Mv3SAEtjL4

[Romain Tavenard @rtavenar]

Come work with us on tslearn in beautiful Rennes!

(deadline for application is soon!)

https://t.co/Mv3SAEtjL4

[Nicolas Keriven @n_keriven]

Our @TmlrOrg paper "Gradient scarcity with Bilevel Optimization for Graph Learning" (w/ H Ghanem,
@vaiter ) was accepted as an oral presentation at @LogConference 🤓 100% free and online, come check it out!

https://t.co/ggi3dvWwCt

[Samuel Vaiter @vaiter]

I have multiple openings for M2 internship / PhD / postdoc in Nice (France) on topics related to bilevel optimization, automatic differentiation and safe machine learning. More details on my webpage https://t.co/t0CKDae3D2

Contact me by email, and feel free to forward/RT :)

[Nicolas Keriven @n_keriven]

I have several internship/PhD positions on Graph ML available with ERC MALAGA 🤓 See details here:

https://t.co/cJwHKJFKYK

Don't hesitate to contact me! (same if you are interested in a post-doc related to graph ML)

[Bliss Chapman @chapman_bliss]

Cool work on a differentiable variant of dynamic time warping by @rtavenar
https://t.co/z8IlFjTYAw

[Samuel Vaiter @vaiter]

A Monge map, i.e., a solution to optimal transport Monge problems, may not always exist, be unique, or be symmetric with respect to the source and target distributions. It was one of the motivation to introduce Kantorovich relaxation. https://t.co/zwzUyJh68m

[Samuel Vaiter @vaiter]

Brenier's theorem states that the optimal transport map between two probability measures for quadratic cost is the gradient of a convex function. Moreover, it is uniquely defined up to a Lebesgue negligible set. https://t.co/pZD2W8LPQS

[Samuel Vaiter @vaiter]

Bilevel optimization problems with multiple inner solutions come typically in two flavors: optimistic and pessimistic. Optimistic assumes the inner problem selects the best solution for the outer objective, while pessimistic assumes the worst-case solution is chosen.

[Samuel Vaiter @vaiter]

Congratulations to Dr. Dagréou @Mat_Dag for a brillant PhD defense! @tomamoral, @PierreAblin and I were lucky to have you as a student.

[Sibylle Marcotte @SibylleMarcotte]

🏆Didn't get the Physics Nobel Prize this year, but really excited to share that I've been named one of the #FWIS2024 @FondationLOreal-@UNESCO French Young Talents alongside 34 amazing young researchers! This award recognizes my research on deep learning theory #WomenInScience 👩‍💻

[Björn Michele @Bjoern_Michele]

🚨 Interested in domain adaptation and generalization for 3D data? 🚨

It’s tough to keep up with all the new amazing work.

That’s why I’ve curated a comprehensive, easy-to-navigate list of publications. 📚

👉 Repo: https://t.co/k9a64VG3od

[Ievgen Redko @IevgenRedko]

A simple, yet overlooked idea: LLMs with a finite vocabulary and context window are (finite) Markov chains :)

An 🤩 internship of @oussamazekri_in collaboration with now officially our 1st year Ph.D. student @AmbroiseOdonnat @abenechehab @bleistein_linus & N. Boullé

A 🧵⬇️

[Stat.ML Papers @StatMLPapers]

Large Language Models as Markov Chains https://t.co/kmqfTAqS7q

[Samuel Vaiter @vaiter]

Stein's Lemma states that for a normally distributed variable X, the expected value E[Xg(X)] = E[g’(X)] for any g absolutely continuous (derivative a.e.) such that E[|g’(X)|] < ∞. It is a central result for characterizing Gaussian data https://t.co/cZxglDHKnx

[Ambroise Odonnat @AmbroiseOdonnat]

🤗Officially started Ph.D. with @IevgenRedko, @rtavenar and Laetitia Chapel @Inria @irisa_lab on Transformers & Distribution Shifts

🥳🇨🇦 Also, 2 papers accepted at #NeurIPS2024

📈 *Spotlight* https://t.co/kphqSjHRHG
✋🏾 MaNO https://t.co/pzojhoYA0R

More details soon!

[Nicolas Keriven @n_keriven]

I'm thrilled to announce that my #ERCStG project has been accepted 🤓

**MALAGA: Reinventing the Theory of Machine Learning on Large Graphs**

Many job openings coming up, see https://t.co/uZ3SuJBt9H for updates! Thank you @ERC_Research and all my collaborators past and future

[Gael Varoquaux 🦋 @GaelVaroquaux]

Un évènement sur l'IA où je participais a été chamboulé par Extinction Rébellion (mauvaise cible: ça parlait des limites de l'IA).

C'est symptomatique du contexte de communication contrôlée ne laissant aux voix dissonantes uniquement une place violente.

[Ambroise Odonnat @AmbroiseOdonnat]

🎤 Very happy to get to present SAMformer at @CriteoAILab two weeks ago! Thanks again for the invitation @LDosSantos_ and @jy_franceschi 🙏

Slides on my website https://t.co/9nw7Ncu5W9

Bonus: SAMformer poster session at #icml2024 with @IevgenRedko 📢