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Tomorrow's robots will need to distinguish useful information from noise when performing different tasks.
Sparse evolutionary Deep Learning with over one million artificial neurons on commodity hardware
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The Distracting Control Suite – A Challenging Benchmark for Reinforcement Learning from Pixels
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Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, and Sergey Levine. 2018 · 2018
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Decebal Constantin Mocanu, Elena Mocanu, Peter Stone, Phuong H Nguyen, Madeleine Gibescu, and Antonio Liotta. 2018 · 2018
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The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
Jonathan Frankle and Michael Carbin. 2019 · 2019
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Neuroplasticity in adult human visual cortex
Elisa Castaldi, Claudia Lunghi, and Maria Concetta Morrone. 2020 · 2020
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Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch
Aojun Zhou, Yukun Ma, Junnan Zhu, Jianbo Liu, Zhijie Zhang, Kun Yuan, Wenxiu Sun, and Hongsheng Li. 2020 · 2020
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Single-Shot Pruning for Offline Reinforcement Learning
Samin Yeasar Arnob, Riyasat Ohib, Sergey Plis, and Doina Precup. 2021 · 2021
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Nicolò Botteghi, Khaled Alaa, Mannes Poel, Beril Sirmacek, Christoph Brune, Abeje Mersha, and Stefano Stramigioli. 2021 · 2021
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Chasing Sparsity in Vision Transformers: An End-to-End Exploration
Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang, and Zhangyang Wang. 2021 · 2021
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Austin Stone, Oscar Ramirez, Kurt Konolige, and Rico Jonschkowski. 2021 · 2021
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Ke Sun, Yi Liu, Yingnan Zhao, Hengshuai Yao, Shangling Jui, and Linglong Kong. 2021 · 2021
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Quick and Robust Feature Selection: the Strength of Energy-efficient Sparse Training for Autoencoders
Zahra Atashgahi, Ghada Sokar, Tim van der Lee, Elena Mocanu, Decebal Constantin Mocanu, Raymond Veldhuis, and Mykola Pechenizkiy. 2022 · 2022
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Robust Deep Reinforcement Learning for Greenhouse Control and Crop Yield Optimization
Wouter van den Bemd. 2022 · 2022
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Sparsity Winning Twice: Better Robust Generalization from More Efficient Training
Tianlong Chen, Zhenyu Zhang, Pengjun Wang, Santosh Balachandra, Haoyu Ma, Zehao Wang, and Zhangyang Wang. 2022 · 2022
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Magnetic control of tokamak plasmas through deep reinforcement learning
Jonas Degrave, Federico Felici, Jonas Buchli, Michael Neunert, Brendan Tracey, Francesco Carpanese, Timo Ewalds, Roland Hafner, Abbas Abdolmaleki, Diego de Las Casas, et al · 2022
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Laura Graesser, Utku Evci, Erich Elsen, and Pablo Samuel Castro. 2022 · 2022
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Robust Reinforcement Learning: A Review of Foundations and Recent Advances
Janosch Moos, Kay Hansel, Hany Abdulsamad, Svenja Stark, Debora Clever, and Jan Peters. 2022 · 2022
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Dynamic Sparse Training for Deep Reinforcement Learning
Ghada Sokar, Elena Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy, and Peter Stone. 2022b · 2022
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On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning
Marc Aurel Vischer, Robert Tjarko Lange, and Henning Sprekeler. 2022 · 2022
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RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch
Yiqin Tan, Pihe Hu, Ling Pan, and Longbo Huang. 2023 · 2023
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