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Multi-Scale Reversible Chaos Game Representation: A Unified Framework for Sequence Classification
Sarwan Ali, Taslim Murad
Biological classification with interpretability remains a challenging task. For this, we introduce a novel encoding framework, Multi-Scale Reversible Chaos Game Representation (MS-…
DPSR: Differentially Private Sparse Reconstruction via Multi-Stage Denoising for Recommender Systems
Sarwan Ali
Differential privacy (DP) has emerged as the gold standard for protecting user data in recommender systems, but existing privacy-preserving mechanisms face a fundamental challenge:…
Boosting t-SNE Efficiency for Sequencing Data: Insights from Kernel Selection
Avais Jan, Prakash Chourasia, Sarwan Ali +1
Dimensionality reduction techniques are essential for visualizing and analyzing high-dimensional biological sequencing data. t-distributed Stochastic Neighbor Embedding (t-SNE) is…
Murmur2Vec: A Hashing Based Solution For Embedding Generation Of COVID-19 Spike Sequences
Sarwan Ali, Taslim Murad
Early detection and characterization of coronavirus disease (COVID-19), caused by SARS-CoV-2, remain critical for effective clinical response and public-health planning. The global…
Sequence-to-Image Transformation for Sequence Classification Using Rips Complex Construction and Chaos Game Representation
Sarwan Ali, Taslim Murad, Imdadullah Khan
Traditional feature engineering approaches for molecular sequence classification suffer from sparsity issues and computational complexity, while deep learning models often underper…
Robust Gradient Descent via Heavy-Ball Momentum with Predictive Extrapolation
Sarwan Ali
Accelerated gradient methods like Nesterov's Accelerated Gradient (NAG) achieve faster convergence on well-conditioned problems but often diverge on ill-conditioned or non-convex l…