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05/29/2023
Brainformers: Trading Simplicity for Efficiency
Transformers are central to recent successes in natural language process...
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04/23/2023
LayerNAS: Neural Architecture Search in Polynomial Complexity
Neural Architecture Search (NAS) has become a popular method for discove...
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02/03/2023
PyGlove: Efficiently Exchanging ML Ideas as Code
The increasing complexity and scale of machine learning (ML) has led to ...
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06/04/2021
RL-DARTS: Differentiable Architecture Search for Reinforcement Learning
We introduce RL-DARTS, one of the first applications of Differentiable A...
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02/17/2021
Rethinking Co-design of Neural Architectures and Hardware Accelerators
Neural architectures and hardware accelerators have been two driving for...
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01/21/2021
PyGlove: Symbolic Programming for Automated Machine Learning
Neural networks are sensitive to hyper-parameter and architecture choice...
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01/19/2021
ES-ENAS: Combining Evolution Strategies with Neural Architecture Search at No Extra Cost for Reinforcement Learning
We introduce ES-ENAS, a simple neural architecture search (NAS) algorith...
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01/08/2021
Evolving Reinforcement Learning Algorithms
We propose a method for meta-learning reinforcement learning algorithms ...
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11/11/2020
Towards NNGP-guided Neural Architecture Search
The predictions of wide Bayesian neural networks are described by a Gaus...
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06/05/2020
AutoHAS: Differentiable Hyper-parameter and Architecture Search
Neural Architecture Search (NAS) has achieved significant progress in pu...
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11/16/2018