A Non-parametric Multi-stage Learning Framework for Cognitive Spectrum Access in IoT Networks. - Thulasi Tholeti; Vishnu Raj; Sheetal Kalyani (CoRR, 2018)

Spectrum Access In Cognitive Radio Using a Two-Stage Reinforcement Learning Approach. - Vishnu Raj; Irene Dias; Thulasi Tholeti; Sheetal Kalyani (IEEE J. Sel. Top. Signal Process., 2018)

Concavifiability and convergence: necessary and sufficient conditions for gradient descent analysis. - Thulasi Tholeti; Sheetal Kalyani (CoRR, 2019)

What is the optimal depth for deep-unfolding architectures at deployment? - Nancy Nayak; Thulasi Tholeti; Muralikrishnan Srinivasan; Sheetal Kalyani (CoRR, 2020)

Tune Smarter Not Harder: A Principled Approach to Tuning Learning Rates for Shallow Nets. - Thulasi Tholeti; Sheetal Kalyani (IEEE Trans. Signal Process., 2020)

On the Differentially Private Nature of Perturbed Gradient Descent. - Thulasi Tholeti; Sheetal Kalyani (CoRR, 2021)

How to boost autoencoders? - Sai Krishna; Thulasi Tholeti; Sheetal Kalyani (CoRR, 2021)

The robust way to stack and bag: the local Lipschitz way. - Thulasi Tholeti; Sheetal Kalyani (CoRR, 2022)

Introducing the Huber mechanism for differentially private low-rank matrix completion. - R. Adithya Gowtham; Gokularam Muthukrishnan; Thulasi Tholeti; Sheetal Kalyani (CoRR, 2022)

Probabilistic learning rate scheduler with provable convergence. - Dahlia Devapriya; Thulasi Tholeti; Janani Suresh; Sheetal Kalyani (CoRR, 2024)

Binarized ResNet: Enabling Robust Automatic Modulation Classification at the Resource-Constrained Edge. - Nitin Priyadarshini Shankar; Deepsayan Sadhukhan; Nancy Nayak; Thulasi Tholeti; Sheetal Kalyani (IEEE Trans. Cogn. Commun. Netw., 2024)

Online waveform selection for cognitive radar. - Thulasi Tholeti; Avinash Rangarajan; Sheetal Kalyani (ICASSP, 2025)

Unequal Opportunities: Examining the Bias in Geographical Recommendations by Large Language Models. - Shiran Dudy; Thulasi Tholeti; Resmi Ramachandranpillai; Muhammad Ali; Toby Jia-Jun Li; Ricardo Baeza-Yates (IUI, 2025)