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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
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Published Paper Details:
Paper Title
Optimizing Neural Network Training With Gradient Boosting Techniques
Authors
Adigicherla Venkatesh, Dr. Meeravali Shaik
Keywords
Gradient Boosting, Deep Learning, GB-RNN, GB-DNN, Image Classification, CIFAR-10, Ensemble Learning, Pseudo-Residual Learning, Layer Freezing, Dense Layers, Overfitting Reduction, Sequential Modeling, Fine-Tuning, Residual Correction, Performance Evaluation.
Abstract
This study introduces two novel training frameworks--Gradient Boosted Recurrent Neural Network (GB-RNN) and Gradient Boosted Deep Neural Network (GB-DNN)--that synergize the principles of ensemble learning with deep learning models. By employing a stage-wise refinement strategy inspired by boosting, these models incrementally construct layered architectures that address limitations often seen in conventional neural networks, such as excessive model complexity, unstable gradients, and susceptibility to overfitting. Each layer in the network is trained to improve upon the residual shortcomings of previous iterations, enabling more efficient learning. Experimental validation is conducted using the CIFAR-10 image dataset, and performance is assessed using comprehensive classification metrics, demonstrating the effectiveness of the proposed approach
IJCRT's Publication Details
Unique Identification Number - IJCRT25A6079
Paper ID - 290240
Page Number(s) - j249-j272
Pubished in - Volume 13 | Issue 6 | June 2025
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Adigicherla Venkatesh, Dr. Meeravali Shaik, "Optimizing Neural Network Training With Gradient Boosting Techniques", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 6, pp.j249-j272, June 2025, Available at :http://www.ijcrt.org/papers/IJCRT25A6079.pdf
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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