Aditya Ranganath

14 papers B 1C 6Journal 2Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	ProtAlign: Contrastive learning paradigm for Sequence and structure alignment. CoRR Aditya Ranganath, Hasin Us Sami, Kowshik Thopalli, Bhavya Kailkhura, Wesam A. Sakla
2025	—	`conf`	Signal Reconstructions for ECG-Transmembrane Voltage Potentials Using Transformers. ISBI Jocelyn Ornelas Munoz, Gbocho M. Terasaki, Aditya Ranganath, Omar DeGuchy, Roummel F. Marcia
2025	—	`conf`	Symmetric Rank-One Quasi-Newton Methods for Deep Learning Using Cubic Regularization. CAMSAP Aditya Ranganath, Mukesh Singhal, Roummel F. Marcia
2025	J	`jnl`	Symmetric Rank-One Quasi-Newton Methods for Deep Learning Using Cubic Regularization. CoRR Aditya Ranganath, Mukesh Singhal, Roummel F. Marcia
2024	C	`conf`	Quasi-Adam: Accelerating Adam Using Quasi-Newton Approximations. ICMLA Aditya Ranganath, Irabiel Romero Ruiz, Mukesh Singhal, Roummel F. Marcia
2023	—	`—`	Optimization for machine learning: Memory-efficient and tractible solutions to large-scale non-convex systems Aditya Ranganath
2022	C	`conf`	A Novel Approach for Synthetic Reduced Nearest-Neighbor Leveraging Neural Networks. ICMLA Azar Alizadeh, Pooya Tavallali, Vahid Behzadan, Aditya Ranganath, Mukesh Singhal
2022	B	`conf`	Adversarial Label-Poisoning Attacks and Defense for General Multi-Class Models Based on Synthetic Reduced Nearest Neighbor. ICIP Pooya Tavallali, Vahid Behzadan, Azar Alizadeh, Aditya Ranganath, Mukesh Singhal
2022	C	`conf`	Interpretability of ReLU for Inversion. ICMLA Boaz Ilan, Aditya Ranganath, Jacqueline Alvarez, Shilpa Khatri, Roummel F. Marcia
2022	C	`conf`	Novel Adversarial Defense Techniques for White-Box Attacks. ICMLA Jason Van Tuinen, Aditya Ranganath, Goran Konjevod, Mukesh Singhal, Roummel F. Marcia
2022	C	`conf`	Recurrent Nerual Imaging: An Evolutionary Approach for Mixed Possion-Gaussian Image Denoising. ICMLA Aditya Ranganath, Omar DeGuchy, Fabian Santiago, Mukesh Singhal, Roummel F. Marcia
2022	C	`conf`	Stochastic Induction of Decision Trees with Application to Learning Haar Trees. ICMLA Azar Alizadeh, Mukesh Singhal, Vahid Behzadan, Pooya Tavallali, Aditya Ranganath
2021	—	`conf`	Multi-Stage Gaussian Noise Reduction with Recurrent Neural Networks. ACSCC Aditya Ranganath, Omar DeGuchy, Mukesh Singhal, Roummel F. Marcia
2021	—	`conf`	Second-Order Trust-Region Optimization for Data-Limited Inference. EUSIPCO Aditya Ranganath, Omar DeGuchy, Mukesh Singhal, Roummel F. Marcia