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09/08/2023
On the Efficacy of Multi-scale Data Samplers for Vision Applications
Multi-scale resolution training has seen an increased adoption across mu...
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05/31/2023
Bytes Are All You Need: Transformers Operating Directly On File Bytes
Modern deep learning approaches usually transform inputs into a modality...
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12/20/2022
RangeAugment: Efficient Online Augmentation with Range Learning
State-of-the-art automatic augmentation methods (e.g., AutoAugment and R...
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07/21/2022
SPIN: An Empirical Evaluation on Sharing Parameters of Isotropic Networks
Recent isotropic networks, such as ConvMixer and vision transformers, ha...
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10/08/2021
LCS: Learning Compressible Subspaces for Adaptive Network Compression at Inference Time
When deploying deep learning models to a device, it is traditionally ass...
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02/20/2021
Learning Neural Network Subspaces
Recent observations have advanced our understanding of the neural networ...
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11/18/2020
Layer-Wise Data-Free CNN Compression
We present an efficient method for compressing a trained neural network ...
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05/07/2018