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Creativity in Machine Learning
Recent machine learning techniques can be modified to produce creative r...
01/12/2016 ∙ by Martin Thoma, et al. ∙
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Beyond Exponentially Discounted Sum: Automatic Learning of Return Function
In reinforcement learning, Return, which is the weighted accumulated fut...
05/28/2019 ∙ by Yufei Wang, et al. ∙
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On Axiomatization of Lewis' Conditional Logics
This paper first shows that the popular axiomatic systems proposed by Nu...
10/14/2019 ∙ by Xuefeng Wen, et al. ∙
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Incrementally Learning Functions of the Return
Temporal difference methods enable efficient estimation of value functio...
07/05/2019 ∙ by Brendan Bennett, et al. ∙
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Modeling Risk and Return using Dirichlet Process Prior
In this paper, we showed that the no-arbitrage condition holds if the ma...
05/01/2018 ∙ by Sourish Das, et al. ∙
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The Potential of the Return Distribution for Exploration in RL
This paper studies the potential of the return distribution for explorat...
06/11/2018 ∙ by Thomas M. Moerland, et al. ∙
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Return to Bali
09/01/2020 ∙ by Marc Böhlen, et al. ∙
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This paper gives an overview of the project Return to Bali that seeks to create a living dataset of ethnobotanically significant flora on the island of Bali and new methods through which underrepresented forms of knowledge can be documented, shared and made compatible within the logics of machine learning while considering practical approaches to benefit multiple stakeholders and preventing unintended harm.
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