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Volkan Cevher
@CevherLIONS
Professor of Electrical Engineering, EPFL. Amazon Scholar (AGI Foundations). IEEE Fellow. ELLIS Fellow.
Lausanne, Switzerland
Joined January 2013
Posts
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    Batch size is one of the most important and most debated questions in large-scale training. We still rely on heuristics: linear scaling (Goyal et al) critical batch size (McClandlish et al.) hyperparameter transfer (Yang et al.) We show that under a fixed token budget, there
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    🔥 Want to train large neural networks WITHOUT Adam while using less memory and getting better results? ⚡ Check out SCION: a new optimizer that adapts to the geometry of your problem using norm-constrained linear minimization oracles (LMOs): 🧵👇
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    I have postdoc and PhD positions on optimization, RL, and deep learning theory in my group lions.epfl.ch at EPFL. Send me an email if you are interested in meeting with me in person at ICML. Please share to potentially interested parties.
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    When the meta-reviewer rejects a paper with 10,7,6,5 scores. Cmon @NeurIPSConf.
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    I am quite excited to announce that 12 papers from the LIONS group have been accepted to the 2022 edition of NeurIPS conference. Congratulations to my group and our collaborators! Below is a list of the accepted papers: actu.epfl.ch/news/lions-neu…
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    🚀 Curious about how Linear Transformers perform on bi-directional tasks and how to adapt them? Meet LION (arxiv.org/abs/2502.16249) 🦁, our new framework for bi-directional sequence modeling that supports: + Full LInear AttentiON (LION) + Bi-directional RNN + Chunkwise Parallel
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    Good news: Two of my postdocs got faculty offers (Technion & Linkoping). Better news (please retweet): My group has postdoc positions in the general area of Machine Learning with emphasis on optimization, deep learning, and reinforcement learning. Other areas are also possible.
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    The level to publish at NeurIPS/ICML over the years.
    The increase in the amount of data required for publishing
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    00:00
    Overtime
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    Dear @icmlconf AC's, In the "view author feedback" menu, you can ask further questions to authors to give them another chance to clarify additional issues that may arise during the discussion period. As an AC myself, I cannot emphasize how impactful this is. Use it! Do it now!
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    Congratulations to my (former) PhD student Dr. Paul Rolland who has successfully defended his thesis w/the committee Pradeep Ravikumar, @gabrielpeyre, Nicolas Flammarion, and Martin Jaggi. Looking forward to seeing his next steps!
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    My (former) PhD student @yapinghsieh receives the EPFL PhD thesis Distinction in Electrical Engineering 2020. This distinction is awarded to the 8 % best PhD theses of each EPFL Doctoral Programme. Congratulations! The thesis: infoscience.epfl.ch/record/280224
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    Happy to announce our accepted #NeurIPS2021 papers. A great team effort by the members of my group and our collaborators. Thank you all!
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    A huge effort finally paid off: Robust reinforcement learning via adversarial training with Langevin dynamics will be presented @NeurIPSConf arxiv.org/abs/2002.06063. It also has some elementary results on why adversarial training is hard for first order methods.
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    I am happy to share some more good news: My group (lions.epfl.ch) has 6 papers at @icmlconf 2020: actu.epfl.ch/news/lions-icm…