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Cited By

SwiftLearn: A Data-Efficient Training Method of Deep Learning Models
using Importance Sampling

SwiftLearn: A Data-Efficient Training Method of Deep Learning Models using Importance Sampling

25 November 2023

Habib Hajimolahoseini

Omar Mohamed Awad

Mohammad Hassanpour

Farnoosh Javadi

Foozhan Ataiefard

Yang Liu

ArXiv (abs)PDF HTML Github

Papers citing "SwiftLearn: A Data-Efficient Training Method of Deep Learning Models using Importance Sampling"

4 / 4 papers shown

Slamming: Training a Speech Language Model on One GPU in a Day

Slamming: Training a Speech Language Model on One GPU in a DayAnnual Meeting of the Association for Computational Linguistics (ACL), 2025

Avishai Elmakies

400

12

0

19 Feb 2025

Is 3D Convolution with 5D Tensors Really Necessary for Video Analysis?

Is 3D Convolution with 5D Tensors Really Necessary for Video Analysis?

Habib Hajimolahoseini

Yang Liu

309

0

0

23 Jul 2024

Improving Resnet-9 Generalization Trained on Small Datasets

Improving Resnet-9 Generalization Trained on Small Datasets

Omar Mohamed Awad

Habib Hajimolahoseini

293

2

0

07 Sep 2023

Training Acceleration of Low-Rank Decomposed Networks using Sequential Freezing and Rank Quantization

Training Acceleration of Low-Rank Decomposed Networks using Sequential Freezing and Rank Quantization

Habib Hajimolahoseini

243

10

0

07 Sep 2023

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