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08/04/2022
HPO: We won't get fooled again
Hyperparameter optimization (HPO) is a well-studied research field. Howe...
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03/23/2022
DynamicEarthNet: Daily Multi-Spectral Satellite Dataset for Semantic Change Segmentation
Earth observation is a fundamental tool for monitoring the evolution of ...
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01/17/2022
Landscape of Neural Architecture Search across sensors: how much do they differ ?
With the rapid rise of neural architecture search, the ability to unders...
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11/05/2021
A Data-driven Approach to Neural Architecture Search Initialization
Algorithmic design in neural architecture search (NAS) has received a lo...
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11/02/2021
Fitness Landscape Footprint: A Framework to Compare Neural Architecture Search Problems
Neural architecture search is a promising area of research dedicated to ...
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08/20/2021
Lessons from the Clustering Analysis of a Search Space: A Centroid-based Approach to Initializing NAS
Lots of effort in neural architecture search (NAS) research has been ded...
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06/29/2021
Reliable and Fast Recurrent Neural Network Architecture Optimization
This article introduces Random Error Sampling-based Neuroevolution (RESN...
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01/29/2020
Bayesian Neural Architecture Search using A Training-Free Performance Metric
Recurrent neural networks (RNNs) are a powerful approach for time series...
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10/12/2019
JSDoop and TensorFlow.js: Volunteer Distributed Web Browser-Based Neural Network Training
In 2019, around 57% of the population of the world has broadband access ...
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09/04/2019
A Specialized Evolutionary Strategy Using Mean Absolute Error Random Sampling to Design Recurrent Neural Networks
Recurrent neural networks have demonstrated to be good at solving predic...
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07/10/2018
DLOPT: Deep Learning Optimization Library
Deep learning hyper-parameter optimization is a tough task. Finding an a...
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05/18/2018
