YouTube video by Ernest Ryu
Optimization Algorithm Design via Electric Circuits (Ernest Ryu, 02.19.2025)
Last week, I visited UCSD under Prof. Yang Zhengβs invitation to speak about this work. The following is a re-recording of the talk:
youtu.be/NcI-qxTqgn8?...
(2/3)
25.02.2025 16:03 β π 0 π 0 π¬ 1 π 0
Your optimization algorithm is a circuit!
In our NeurIPS 2024 Spotlight paper with Stephen Boyd, Tetiana Parshakova, Jaewook Suh, we present a framework for designing optimization algorithms using (electric) circuit theory.
(Video and paper links in reply)
25.02.2025 16:03 β π 4 π 1 π¬ 1 π 0
Yesterday, Kevin Shu (Caltech) visited UCLA and gave a wonderful talk at the Mathematics Colloquium titled Algebraic Methods in Convex Optimization!
You can check out the recording here:
youtu.be/e10y8fJdZ2Y
14.02.2025 18:07 β π 1 π 0 π¬ 0 π 0
In that sense, this is control theory. The authors have EE backgrounds, so we were more comfortable expressing things with RLC components rather than, say, springs and dampers.
14.12.2024 18:49 β π 4 π 0 π¬ 0 π 0
Optimization Algorithm Design via Electric Circuits @StephenPBoyd1
13.12.2024 21:35 β π 14 π 1 π¬ 1 π 0
YouTube video by Ernest Ryu
Aaron Defazio Talk (12.06.2024, UCLA)
Aaron gave a truly amazing talk. Very clear and super informative π
youtu.be/QUgi3-XuZ3g
07.12.2024 20:09 β π 4 π 0 π¬ 0 π 0
Shuvomoy Das Gupta (Columbia) and I (UCLA) are starting an optimization seminar series! Our first speaker, Aaron Defazio (Meta), presented Schedules & Schedule-Free Learning.
Aaron will give his NeurIPS 2024 Oral work next week. This is a longer version. (Video link in reply)
07.12.2024 20:09 β π 4 π 0 π¬ 1 π 0
Can you add me plz? Thanks!
26.11.2024 15:35 β π 1 π 0 π¬ 1 π 0
AI & Transportation | MIT Associate Professor
Interests: AI for good, sociotechnical systems, machine learning, optimization, reinforcement learning, public policy, gov tech, open science.
Science is messy and beautiful.
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Professor, Programmer in NYC.
Cornell, Hugging Face π€
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Scientist at Champalimaud Foundation (polaviejalab.org) and co-founder of Algebraic AI (algebraic.ai). #Maths4AI #AI4Science, #BehaviorAI #NeuroAI #CognitionAI #CollectiveBehavior
Laplace Junior Chair, Machine Learning
ENS Paris. (prev ETH Zurich, Edinburgh, Oxford..)
Working on mathematical foundations/probabilistic interpretability of ML (what NNs learnπ€·ββοΈ, disentanglementπ€, king-man+woman=queen?πβ¦)
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Computer Vision, Computational Neuroscience
Professor of Applied Physics at Stanford | Venture Partner a16z | Research in AI, Neuroscience, Physics
Chief AI Scientist at Databricks. Founding team at MosaicML. MIT/Princeton alum. Lottery ticket enthusiast. Working on data intelligence.
stealth // Gemini RL+inference @ Google DeepMind // Conversational AI @ Meta // RL Agents @ EA // ML+Information Theory @ MIT+Harvard+Duke // Georgia Tech PhD // Ψ²Ω Ψ²ΩΨ―Ϊ―Ϋ Ψ’Ψ²Ψ§Ψ―Ϋ
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a mediocre combination of a mediocre AI scientist, a mediocre physicist, a mediocre chemist, a mediocre manager and a mediocre professor.
see more at https://kyunghyuncho.me/
Researcher @MSFTResearch; Prof @UWMadison (on leave); learning in context; thinking about reasoning; babas of Inez Lily.
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Professor, Stanford University, Statistics and Mathematics. Opinions are my own.
Director, Princeton Language and Intelligence. Professor of CS.
ML Research @ Apple.
Understanding deep learning (generalization, calibration, diffusion, etc).
preetum.nakkiran.org
Machine learning researcher. Professor in ML department at CMU.
UC Berkeley Professor working on AI. Co-Director: National AI Institute on the Foundations of Machine Learning (IFML). http://BespokeLabs.ai cofounder
work on theoretical foundations of AI, MLLM reliability/Eval, optimization, high dimensional probability/statistics, AI for science/healthcare; director of center on AIF4S @USC π²ποΈπ₯ΎπββοΈ
Assistant Prof at Penn CIS | Postdoc at Microsoft Research | PhD from UT Austin CS | Co-founder LeT-All
Research Scientist @ Google DeepMind. Physics of learning, ML / AI, condensed matter. Prev Ph.D. Physics @ UC Berkeley.
