Exploring Byzantine Resilient Distributed Optimization Beyond First Order Methods
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- Approximate Byzantine Fault-Tolerance in Distributed Optimization
- Byzantine Resilient
- Deep learning optimizers are often motivated through a mix of convex and approximate second-
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- PODC-2020 paper by Revisiting Asynchronous Fault Tolerant Computation with Optimal
In-Depth Information on Byzantine Resilient Distributed Optimization Beyond First Order Methods
Title: Angelia Nedich, University of Illinois, Urbana-Champaign Parallel and PODC-2020 paper by El-Mhamdi, El-Mahdi; Guerraoui, Rachid; Guirguis, Arsany; Hoang, Lê Nguyên; Rouault, Sébastien. Hello and welcome to our presentation on approximate fault tolerance in
Accompanying lecture notes: https://www.cl.cam.ac.uk/teaching/2122/ConcDisSys/dist-sys-notes.pdf Full lecture series: ...
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