Lukasz Dudziak | DeepAI

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∙ 06/15/2023

Neural Fine-Tuning Search for Few-Shot Learning

In few-shot recognition, a classifier that has been trained on one set o...

0 Panagiotis Eustratiadis, et al. ∙

∙ 10/13/2022

BLOX: Macro Neural Architecture Search Benchmark and Algorithms

Neural architecture search (NAS) has been successfully used to design nu...

7 Thomas Chun Pong Chau, et al. ∙

∙ 06/22/2022

FedorAS: Federated Architecture Search under system heterogeneity

Federated learning (FL) has recently gained considerable attention due t...

0 Lukasz Dudziak, et al. ∙

∙ 05/06/2022

EdgeViTs: Competing Light-weight CNNs on Mobile Devices with Vision Transformers

Self-attention based models such as vision transformers (ViTs) have emer...

18 Junting Pan, et al. ∙

∙ 09/28/2021

Smart at what cost? Characterising Mobile Deep Neural Networks in the wild

With smartphones' omnipresence in people's pockets, Machine Learning (ML...

0 Mario Almeida, et al. ∙

∙ 06/12/2021

Zero-Cost Proxies Meet Differentiable Architecture Search

Differentiable neural architecture search (NAS) has attracted significan...

4 Lichuan Xiang, et al. ∙

∙ 01/20/2021

Zero-Cost Proxies for Lightweight NAS

Neural Architecture Search (NAS) is quickly becoming the standard method...

14 Mohamed S. Abdelfattah, et al. ∙

∙ 10/27/2020

μNAS: Constrained Neural Architecture Search for Microcontrollers

IoT devices are powered by microcontroller units (MCUs) which are extrem...

0 Edgar Liberis, et al. ∙

∙ 08/06/2020

Iterative Compression of End-to-End ASR Model using AutoML

Increasing demand for on-device Automatic Speech Recognition (ASR) syste...

10 Abhinav Mehrotra, et al. ∙

∙ 07/16/2020

BRP-NAS: Prediction-based NAS using GCNs

Neural architecture search (NAS) enables researchers to automatically ex...

0 Thomas Chau, et al. ∙

∙ 07/08/2020

Journey Towards Tiny Perceptual Super-Resolution

Recent works in single-image perceptual super-resolution (SR) have demon...

0 Royson Lee, et al. ∙

∙ 02/11/2020

Best of Both Worlds: AutoML Codesign of a CNN and its Hardware Accelerator

Neural architecture search (NAS) has been very successful at outperformi...

0 Mohamed S. Abdelfattah, et al. ∙

∙ 08/21/2019

MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors

In recent years, convolutional networks have demonstrated unprecedented ...

0 Royson Lee, et al. ∙

∙ 07/08/2019

ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning

End-to-end automatic speech recognition (ASR) models are increasingly la...

0 Lukasz Dudziak, et al. ∙

∙ 10/12/2018

Dynamic Channel Pruning: Feature Boosting and Suppression

Making deep convolutional neural networks more accurate typically comes ...

0 Xitong Gao, et al. ∙

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