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CMA-ES ΓÇô a Stochastic Second-Order Method for Function-Value FreeNumerical Optimization
[SPCL_Bcast] A Paradigm Shift to Second Order Methods for Machine Learning
Peter Richtarik - On Second Order Methods and Randomness
Second Order Optimization
2nd-order Optimization for Neural Network Training
Second order optimizations for scalable training of DNNs by Dr. Andrew Lumsdaine
OWOS: Peter Richtárik - Second Order Methods and Randomness
Second Order Optimization
Second-order Optimization Methods for Machine Learning
Fast and Furious Convergence: Stochastic Second-Order Methods under Interpolation
Second order optimizations for scalable training of DNNs by Dr. Andrew Lumsdaine (alternate camera)
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Last Updated: September 26, 2026
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Fred Roosta, University of Queensland simons.berkeley.edu/talks/ Katya Scheinberg, Lehigh University simons.berkeley.edu/talks/katya-scheinberg-10-03-17 Fast Iterative Speakers: Amir Gholami, Zhewei Yao Venue: SPCL_Bcast, recorded on 24 September, 2020 Abstract: The amount of compute ... Guest talk by Peter Richtarik on the seminar series held by MTL MLOpt. mtl-mlopt.github.io The talk contains material from ... Huabiao zhu Ziyan wang Dongyang lyu Nan wang Lei wang. Given their success in other domains, Abstract: With the increasing availability of scalable computing platforms (including accelerators), there is an opportunity for more ... Short presentation of our paper appearing at AISTATS 2020. Paper: arxiv.org/abs/1910.04920 Code: ...
Stochastic Second Order Optimization Methods Ii.pdf
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