Aditya Ranganath

According to our database, Aditya Ranganath authored at least 12 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Symmetric Rank-One Quasi-Newton Methods for Deep Learning Using Cubic Regularization.

Aditya Ranganath, Mukesh Singhal, Roummel F. Marcia

CoRR, February, 2025

Signal Reconstructions for ECG-Transmembrane Voltage Potentials Using Transformers.

Jocelyn Ornelas Munoz, Gbocho M. Terasaki, Aditya Ranganath, Omar DeGuchy, Roummel F. Marcia

Proceedings of the 22nd IEEE International Symposium on Biomedical Imaging, 2025

2024

Quasi-Adam: Accelerating Adam Using Quasi-Newton Approximations.

Aditya Ranganath, Irabiel Romero Ruiz, Mukesh Singhal, Roummel F. Marcia

Proceedings of the International Conference on Machine Learning and Applications, 2024

2023

Optimization for machine learning: Memory-efficient and tractible solutions to large-scale non-convex systems

Aditya Ranganath

PhD thesis, 2023

2022

Novel Adversarial Defense Techniques for White-Box Attacks.

Jason Van Tuinen, Aditya Ranganath, Goran Konjevod, Mukesh Singhal, Roummel F. Marcia

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

Recurrent Nerual Imaging: An Evolutionary Approach for Mixed Possion-Gaussian Image Denoising.

Aditya Ranganath, Omar DeGuchy, Fabian Santiago, Mukesh Singhal, Roummel F. Marcia

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

Interpretability of ReLU for Inversion.

Boaz Ilan, Aditya Ranganath, Jacqueline Alvarez, Shilpa Khatri, Roummel F. Marcia

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

A Novel Approach for Synthetic Reduced Nearest-Neighbor Leveraging Neural Networks.

Azar Alizadeh, Pooya Tavallali, Vahid Behzadan, Aditya Ranganath, Mukesh Singhal

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

Stochastic Induction of Decision Trees with Application to Learning Haar Trees.

Azar Alizadeh, Mukesh Singhal, Vahid Behzadan, Pooya Tavallali, Aditya Ranganath

Proceedings of the 21st IEEE International Conference on Machine Learning and Applications, 2022

Adversarial Label-Poisoning Attacks and Defense for General Multi-Class Models Based on Synthetic Reduced Nearest Neighbor.

Pooya Tavallali, Vahid Behzadan, Azar Alizadeh, Aditya Ranganath, Mukesh Singhal

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

2021

Second-Order Trust-Region Optimization for Data-Limited Inference.

Aditya Ranganath, Omar DeGuchy, Mukesh Singhal, Roummel F. Marcia

Proceedings of the 29th European Signal Processing Conference, 2021

Multi-Stage Gaussian Noise Reduction with Recurrent Neural Networks.

Aditya Ranganath, Omar DeGuchy, Mukesh Singhal, Roummel F. Marcia

Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021