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02/11/2023
Cross-Modal Fine-Tuning: Align then Refine
Fine-tuning large-scale pretrained models has led to tremendous progress...
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06/08/2021
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing
Tuning hyperparameters is a crucial but arduous part of the machine lear...
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03/29/2021
Rethinking Neural Operations for Diverse Tasks
An important goal of neural architecture search (NAS) is to automate-awa...
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01/30/2021
On Data Efficiency of Meta-learning
Meta-learning has enabled learning statistical models that can be quickl...
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04/16/2020
Geometry-Aware Gradient Algorithms for Neural Architecture Search
Many recent state-of-the-art methods for neural architecture search (NAS...
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03/12/2019
Exploiting Reuse in Pipeline-Aware Hyperparameter Tuning
Hyperparameter tuning of multi-stage pipelines introduces a significant ...
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02/20/2019
Random Search and Reproducibility for Neural Architecture Search
Neural architecture search (NAS) is a promising research direction that ...
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10/13/2018