1 citations · 2 across the 10 of their papers we have counts for
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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…
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.…
A New Similarity Function for Spectral Clustering with Application to Plant Phenotypic Data
Kapil Ahuja, Mithun Singh, Kuldeep Pathak +1
Clustering species of the same plant into different groups is an important step in developing new species of the concerned plant. Phenotypic (or physical) characteristics of plant…
Cube Sampled K-Prototype Clustering for Featured Data
Seemandhar Jain, Aditya A. Shastri, Kapil Ahuja +2
Clustering large amount of data is becoming increasingly important in the current times. Due to the large sizes of data, clustering algorithm often take too much time. Sampling thi…
Probabilistically Sampled and Spectrally Clustered Plant Genotypes using Phenotypic Characteristics
Aditya A. Shastri, Kapil Ahuja, Milind B. Ratnaparkhe +1
Clustering genotypes based upon their phenotypic characteristics is used to obtain diverse sets of parents that are useful in their breeding programs. The Hierarchical Clustering (…