Journal of Computer Science & Systems Biology

Department of Business Information Systems, Pantheon-Sorbonne University, 12 Pl. du Panthéon, 75231 Paris, France

Publications

• Mini Review   
  Exploring the Role of Sparsity in Deep Neural Networks for Improved Performance
  Author(s): Mark Daniel*
  
  Deep Neural Networks (DNNs) have achieved remarkable success in various domains, ranging from computer vision to natural language processing. However, their increasing complexity poses challenges in terms of model size, memory requirements, and computational costs. To address these issues, researchers have turned their attention to sparsity, a technique that introduces structural zeros into the network, thereby reducing redundancy and improving efficiency. This research article explores the role of sparsity in DNNs and its impact on performance improvement. We review existing literature, discuss sparsity-inducing methods, and analyze the benefits and trade-offs associated with sparse networks. Furthermore, we present experimental results that demonstrate the effectiveness of sparsity in improving performance metrics such as accuracy, memory footprint, and compu.. Read More»
  DOI: 10.37421/0974-7230.2023.16.462

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