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Feedback Solution to Optimal Switching Problems with Switching Cost
The problem of optimal switching between nonlinear autonomous subsystems...
11/17/2014 ∙ by Ali Heydari, et al. ∙
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On the Tunability of Optimizers in Deep Learning
There is no consensus yet on the question whether adaptive gradient meth...
10/25/2019 ∙ by Prabhu Teja Sivaprasad, et al. ∙
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Deadlock in packet switching networks
A deadlock in a packet switching network is a state in which one or more...
01/15/2021 ∙ by Anna Stramaglia, et al. ∙
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A quest for a fair schedule: The Young Physicists' Tournament
The Young Physicists Tournament is an established team-oriented scientif...
06/03/2020 ∙ by Katarína Cechlárová, et al. ∙
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The Person Index Challenge: Extraction of Persons from Messy, Short Texts
When persons are mentioned in texts with their first name, last name and...
11/16/2020 ∙ by Markus Schröder, et al. ∙
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Provably Efficient Q-Learning with Low Switching Cost
We take initial steps in studying PAC-MDP algorithms with limited adapti...
05/30/2019 ∙ by Yu Bai, et al. ∙
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Hyperparameter Optimization and Boosting for Classifying Facial Expressions: How good can a "Null" Model be?
One of the goals of the ICML workshop on representation and learning is ...
06/14/2013 ∙ by James Bergstra, et al. ∙
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Squirrel: A Switching Hyperparameter Optimizer
12/15/2020 ∙ by Noor Awad, et al. ∙
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In this short note, we describe our submission to the NeurIPS 2020 BBO challenge. Motivated by the fact that different optimizers work well on different problems, our approach switches between different optimizers. Since the team names on the competition's leaderboard were randomly generated "alliteration nicknames", consisting of an adjective and an animal with the same initial letter, we called our approach the Switching Squirrel, or here, short, Squirrel.
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