On Graduated Optimization for Stochastic Non-Convex Problems
On Graduated Optimization for Stochastic Non-Convex Problems Elad Hazan EHAZAN@CS.PRINCETON.EDU Princeton University Kfir Y. Levy KFIRYL@TX.TECHNION.AC.IL Technion - Israel Institute of Technology Shai Shalev-Shwartz SHAIS@CS.HUJI.AC.IL The Hebrew University of Jerusalem, Israel Abstract The graduated optimization approach, also known as the continuation method, is a pop- ular heuristic to solving
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Gradient-based Hyperparameter Optimization through Reversible Learning
Robust partially observable Markov decision process
https://jmlr.org/proceedings/papers/v31/eriksson13a.pdf
https://jmlr.org/proceedings/papers/v37/bahadori15.pdf