7 papers
An Improved Adaptive PID Optimizer with Enhanced Convergence and Stability for Deep Learning
Saurabh Saini, Kapil Ahuja, Thomas Wick +1
Optimization is essential in deep learning. The foundational method upon which most optimizers are built is momentum-based stochastic gradient descent. However, it suffers from two…
ResGene-T: A Tensor-Based Residual Network Approach for Genomic Prediction
Kuldeep Pathak, Kapil Ahuja, Eric de Sturler
In this work, we propose a new deep learning model for Genomic Prediction (GP), which involves correlating genotypic data with phenotypic. The genotypes are typically fed as a sequ…
Stability Analysis of Inexact Solves in Model Reduction of Non-parametric Second-order Dynamical systems
Kapil Ahuja, Navneet Pratap Singh
Here, we focus on Model Order Reduction (MOR) of non-parametric second-order dynamical systems. In these MOR algorithms, sequences of large and sparse linear systems arise during t…
Chameleon2++: An Efficient and Scalable Variant Of Chameleon Clustering
Priyanshu Singh, Kapil Ahuja
Hierarchical clustering remains a fundamental challenge in data mining, particularly when dealing with large-scale datasets where traditional approaches fail to scale effectively.…
Block-Fused Attention-Driven Adaptively-Pooled ResNet Model for Improved Cervical Cancer Classification
Saurabh Saini, Kapil Ahuja, Akshat S. Chauhan
Cervical cancer is the second most common cancer among women and a leading cause of mortality. Many attempts have been made to develop an effective Computer Aided Diagnosis (CAD) s…
Accurate Thyroid Cancer Classification using a Novel Binary Pattern Driven Local Discrete Cosine Transform Descriptor
Saurabh Saini, Kapil Ahuja, Marc C. Steinbach +1
In this study, we develop a new CAD system for accurate thyroid cancer classification with emphasis on feature extraction. Prior studies have shown that thyroid texture is importan…