Martin Takac

228 posts

Martin Takac

Martin Takac

@TakacMartin

Katılım Nisan 2013
140 Takip Edilen359 Takipçiler
Martin Takac retweetledi
MBZUAI
MBZUAI@mbzuai·
MBZUAI is proud to be part of Spring School - AI For Impact, convening the brightest minds in AI to tackle real-world challenges in social impact. Day 1 – March 23 🎙️ Round Table: AI Foundations (11:15 – 12:15) Moderated by MBZUAI's Department Chair and Professor of Machine Learning Eric Moulines, featuring Assistant Professor of Machine Learning Salem Lahlou and Associate Department Chair and Associate Professor of Machine Learning Martin Takáč alongside leading voices from University of California, Berkeley, Google DeepMind, Inria, and CentraleSupélec. Day 2 – March 24 🔬 GFlowNets for Diverse Generation (09:45 – 10:30) Salem Lahlou ⚙️ From Distributed Optimization to Federated Learning (10:30 – 11:15) Martin Takáč Day 3 – March 25 🧠 AI Foundation Models (14:00 – 15:00)- MBZUAI President and University Professor Eric Xing ⚡ Debate: World Models (15:00 – 16:30) - Eric Xing & Yann LeCun More information here: ai4impact2026.com #MBZUAI #AIForImpact #ArtificialIntelligence #AIResearch
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Martin Takac retweetledi
Martin Takac retweetledi
Peter Richtarik
Peter Richtarik@peter_richtarik·
Call for participation:  KAUST Workshop on Distributed Training in the Era of Large Models kaust.edu.sa/events/dtelm25/ location: KAUST, Saudi Arabia dates: Nov 24-26, 2025. There will be a chance for some participants to present a poster and/or give a lightning talk.
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Martin Takac
Martin Takac@TakacMartin·
We have started the #icomp conference with prof. Daniel Kuhn talk about contextual stochastic bilevel optimization icomp.cc
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Martin Takac retweetledi
BRAInLab
BRAInLab@Lab4BRAIn·
Struggling with data heterogeneity in your deep learning projects? We introduce ALSO, a new, practical Distributionally Robust Optimizer (DRO)🚀 📜 Paper thread for "Aligning Distributionally Robust Optimization with Practical Deep Learning Needs"
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Martin Takac
Martin Takac@TakacMartin·
Our paper introduces the first Quasi-Newton method with global convergence as fast as - and even faster than - gradient descent! ✅O(1/k) global rate ⚡Accelerated version: O(1/k²) 🧠Adaptive, cubic regularization for stability & speed Quasi-Newton finally catches up with theory.
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Martin Takac retweetledi
Tahnoon Bin Zayed Al Nahyan
The upcoming launch of the "K2 Think" model will mark a significant step in advancing artificial intelligence from the UAE to the world, reflecting our leadership's vision for technological progress. K2 Think will combine the efficiency of smaller models with world-class performance and superior inference speeds, surpassing larger systems to set a new global benchmark for open-source reasoning Developed through the partnership of @MBZUAl and @G42ai, it showcases the strength of cooperation between academia, public institutions, and the private sector in turning national aspirations into reality. We congratulate the UAE and its leadership on this achievement, as our nation continues to enhance its global standing across all fields.
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Martin Takac
Martin Takac@TakacMartin·
New Quasi-Newton method CEQN offers a simple, explicit stepsize with guaranteed global convergence for convex optimization, matching accelerated methods’ rates even with inexact Hessians. #Optimization #MBZUAI arxiv.org/pdf/2508.19712
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Martin Takac
Martin Takac@TakacMartin·
Join the workshop at #icml25
Martin Takac tweet mediaMartin Takac tweet media
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Martin Takac
Martin Takac@TakacMartin·
Opening
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Martin Takac
Martin Takac@TakacMartin·
We are #hiring for MBZUAI Postdoctoral Opening—Graph AI for Materials & Catalysis at MBZUAI. Message me if you're interested in joining our team. We are attending International Conference on Machine Learning 2025 if you would like to meet! - via #Whova event app
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Dmitry Kamzolov
Dmitry Kamzolov@KamzolovDmitry·
I’m pleased to invite you to visit our poster at #ICLR2025! My co-author Artem Agafonov will present our #OPTAMI paper on global superlinear convergence of second-order methods and a PyTorch library for high-order methods. 📌Hall 3 + Hall 2B #563 📅Thu 24 Apr 10:00
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