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07/25/2023
Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filtering
Differential privacy is a widely accepted measure of privacy in the cont...
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07/15/2023
Creating a Dataset for High-Performance Computing Code Translation: A Bridge Between HPC Fortran and C++
In this study, we present a novel dataset for training machine learning ...
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05/20/2023
Dynamic Gradient Balancing for Enhanced Adversarial Attacks on Multi-Task Models
Multi-task learning (MTL) creates a single machine learning model called...
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11/30/2022
Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off
Over-parameterization of deep neural networks (DNNs) has shown high pred...
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10/15/2021
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm
Various pruning approaches have been proposed to reduce the footprint re...
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12/18/2020
A Surrogate Lagrangian Relaxation-based Model Compression for Deep Neural Networks
Network pruning is a widely used technique to reduce computation cost an...
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07/16/2020
