Ranjitha Prasad

57 papers A 1B 4C 2Misc 10Journal 26Unranked 14

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Informative Perturbation Selection for Uncertainty-Aware Post-hoc Explanations. CoRR Sumedha Chugh, Ranjitha Prasad, Nazreen Shah
2026	Misc	`conf`	Nishpaksh: TEC Standard-Compliant Framework for Fairness Auditing and Certification of AI Models. COMSNETS Shashank Prakash, Ranjitha Prasad, Avinash Agarwal
2026	J	`jnl`	Nishpaksh: TEC Standard-Compliant Framework for Fairness Auditing and Certification of AI Models. CoRR Shashank Prakash, Ranjitha Prasad, Avinash Agarwal
2025	J	`jnl`	Noise Resilient Over-The-Air Federated Learning In Heterogeneous Wireless Networks. CoRR Zubair Shaban, Nazreen Shah, Ranjitha Prasad
2025	A	`conf`	On the Convergence of Continual Federated Learning Using Incrementally Aggregated Gradients. AISTATS Satish Kumar Keshri, Nazreen Shah, Ranjitha Prasad
2025	J	`jnl`	Representation Learning Preserving Ignorability and Covariate Matching for Treatment Effects. CoRR Praharsh Nanavati, Ranjitha Prasad, Karthikeyan Shanmugam
2025	Misc	`conf`	Robust Over-The-Air Federated Learning In Heterogeneous Networks. ICASSP Zubair Shaban, Nazreen Shah, Ranjitha Prasad
2024	—	`conf`	Continual Federated Learning with Aggregated Gradients. COMAD/CODS (December) Satish Kumar Keshri, Nazreen Shah, Ranjitha Prasad
2024	—	`conf`	Enhancing Federated Learning robustness in Wireless Networks. COMAD/CODS Zubair Shaban, Ranjitha Prasad
2024	—	`conf`	Exploiting Sparsity in Over-parameterized Federated Learning over Multiple Access Channels. COMAD/CODS Gagandeep Kaur, Ranjitha Prasad
2024	Misc	`conf`	Federated Learning for Wireless Applications: A Prototype. COMSNETS Varun Laxman Muttepawar, Arjun Mehra, Zubair Shaban, Ranjitha Prasad, Jagadeesh Harshan
2024	—	`conf`	Federated Probabilistic Representation Learning using Information Geometric Approach. COMAD/CODS (December) Nazreen Shah, Ranjitha Prasad
2024	Misc	`conf`	Importance Sampling Based Federated Unsupervised Representation Learning. ICASSP Nazreen Shah, Prachi Goyal, Ranjitha Prasad
2024	J	`jnl`	On Homomorphic Encryption Based Strategies for Class Imbalance in Federated Learning. CoRR Arpit Guleria, J. Harshan, Ranjitha Prasad, B. N. Bharath
2024	J	`jnl`	On the Convergence of Continual Federated Learning Using Incrementally Aggregated Gradients. CoRR Satish Kumar Keshri, Nazreen Shah, Ranjitha Prasad
2024	—	`conf`	Over The Air Federated Learning in the Presence of Impulsive Noise. ICASSP Workshops Zubair Shaban, Ranjitha Prasad, Pooja Kumari
2024	—	`conf`	Seeing is Believing: A Federated Learning Based Prototype to Detect Wireless Injection Attacks. VTC Spring Aadil Hussain, Nitheesh Gundapu, Sarang Drugkar, Suraj Kiran, J. Harshan, Ranjitha Prasad
2023	—	`conf`	CLIMAX: An Exploration of Classifier-Based Contrastive Explanations. CogMI Praharsh Nanavati, Ranjitha Prasad
2023	J	`jnl`	CLIMAX: An exploration of Classifier-Based Contrastive Explanations. CoRR Praharsh Nanavati, Ranjitha Prasad
2023	Misc	`conf`	Deep Survival Analysis and Counterfactual Inference Using Balanced Representations. ICASSP Muskan Gupta, Gokul Kannan, Ranjitha Prasad, Garima Gupta
2023	J	`jnl`	Federated Learning for Wireless Applications: A Prototype. CoRR Varun Laxman Muttepawar, Arjun Mehra, Zubair Shaban, Ranjitha Prasad, Harshan Jagadeesh
2023	—	`conf`	Over-the-air Clustered Wireless Federated Learning. GLOBECOM (Workshops) Ayush Madhan-Sohini, Divin Dominic, Nazreen Shah, Ranjitha Prasad
2023	J	`jnl`	Seeing is Believing: A Federated Learning Based Prototype to Detect Wireless Injection Attacks. CoRR Aadil Hussain, Nitheesh Gundapu, Sarang Drugkar, Suraj Kiran, J. Harshan, Ranjitha Prasad
2022	J	`jnl`	Over-The-Air Clustered Wireless Federated Learning. CoRR Ayush Madhan-Sohini, Divin Dominic, Nazreen Shah, Ranjitha Prasad
2022	—	`conf`	Path-Aware OMP Algorithms for Provenance Recovery in Wireless Networks. VTC Spring Shilpi Mishra, J. Harshan, Ranjitha Prasad
2022	C	`conf`	Select Wisely and Explain: Active Learning and Probabilistic Local Post-hoc Explainability. AIES Aditya Saini, Ranjitha Prasad
2021	J	`jnl`	B-SMALL: A Bayesian Neural Network approach to Sparse Model-Agnostic Meta-Learning. CoRR Anish Madan, Ranjitha Prasad
2021	Misc	`conf`	B-Small: A Bayesian Neural Network Approach to Sparse Model-Agnostic Meta-Learning. ICASSP Anish Madan, Ranjitha Prasad
2021	J	`jnl`	DAGSurv: Directed Acyclic Graph Based Survival Analysis Using Deep Neural Networks. CoRR Ansh Kumar Sharma, Rahul Kukreja, Ranjitha Prasad, Shilpa Rao
2021	C	`conf`	DAGSurv: Directed Ayclic Graph Based Survival Analysis Using Deep Neural Networks. ACML Ansh Kumar Sharma, Rahul Kukreja, Ranjitha Prasad, Shilpa Rao
2021	J	`jnl`	Locally Interpretable Model Agnostic Explanations using Gaussian Processes. CoRR Aditya Saini, Ranjitha Prasad
2021	J	`jnl`	Path-Aware OMP Algorithms for Provenance Recovery in Vehicular Networks. CoRR Shilpi Mishra, J. Harshan, Ranjitha Prasad
2020	J	`jnl`	CAMTA: Casual Attention Model for Multi-touch Attribution. CoRR Sachin Kumar, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff
2020	—	`conf`	CAMTA: Causal Attention Model for Multi-touch Attribution. ICDM (Workshops) Sachin Kumar, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff
2020	—	`conf`	Hi-CI: Deep Causal Inference in High Dimensions. CD@KDD Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff
2020	J	`jnl`	Hi-CI: Deep Causal Inference in High Dimensions. CoRR Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff
2020	B	`conf`	MultiMBNN: Matched and Balanced Causal Inference with Neural Networks. ESANN Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff
2020	J	`jnl`	MultiMBNN: Matched and Balanced Causal Inference with Neural Networks. CoRR Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff
2020	Misc	`conf`	Variational Student: Learning Compact and Sparser Networks In Knowledge Distillation Framework. ICASSP Srinidhi Hegde, Ranjitha Prasad, Ramya Hebbalaguppe, Vishwajeet Kumar
2019	—	`conf`	CRESA: A Deep Learning Approach to Competing Risks, Recurrent Event Survival Analysis. PAKDD (2) Garima Gupta, Vishal Sunder, Ranjitha Prasad, Gautam Shroff
2019	J	`jnl`	MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population. CoRR Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff
2019	J	`jnl`	Variational Student: Learning Compact and Sparser Networks in Knowledge Distillation Framework. CoRR Srinidhi Hegde, Ranjitha Prasad, Ramya Hebbalaguppe, Vishwajith Kumar
2018	—	`conf`	Inference Algorithms for the Multiplicative Mixture Mallows Model. SPCOM Ranjitha Prasad, Vincent Y. F. Tan
2018	J	`jnl`	Lower Bounds on the Bayes Risk of the Bayesian BTL Model With Applications to Comparison Graphs. IEEE J. Sel. Top. Signal Process. Mine Alsan, Ranjitha Prasad, Vincent Y. F. Tan
2018	J	`jnl`	Unlabelled Sensing: A Sparse Bayesian Learning Approach. CoRR Ranjitha Prasad
2017	J	`jnl`	Lower Bounds on the Bayes Risk of the Bayesian BTL Model with Applications to Random Graphs. CoRR Mine Alsan, Ranjitha Prasad, Vincent Y. F. Tan
2015	J	`jnl`	Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach. IEEE Trans. Signal Process. Ranjitha Prasad, Chandra R. Murthy, Bhaskar D. Rao
2015	B	`conf`	Online Recovery of Temporally Correlated Sparse Signals Using Multiple Measurement Vectors. GLOBECOM Geethu Joseph, Chandra R. Murthy, Ranjitha Prasad, Bhaskar D. Rao
2015	Misc	`conf`	Sparse signal recovery in the presence of colored noise and rank-deficient noise covariance matrix: An SBL approach. ICASSP Vinuthna Vinjamuri, Ranjitha Prasad, Chandra R. Murthy
2014	J	`jnl`	Joint Approximately Sparse Channel Estimation and Data Detection in OFDM Systems Using Sparse Bayesian Learning. IEEE Trans. Signal Process. Ranjitha Prasad, Chandra R. Murthy, Bhaskar D. Rao
2014	—	`conf`	Joint channel estimation and data detection in MIMO-OFDM systems using sparse Bayesian learning. NCC Ranjitha Prasad, Chandra R. Murthy
2014	Misc	`conf`	Nested Sparse Bayesian Learning for block-sparse signals with intra-block correlation. ICASSP Ranjitha Prasad, Chandra R. Murthy, Bhaskar D. Rao
2013	J	`jnl`	Cramér-Rao-Type Bounds for Sparse Bayesian Learning. IEEE Trans. Signal Process. Ranjitha Prasad, Chandra R. Murthy
2012	J	`jnl`	Cramer Rao-Type Bounds for Sparse Bayesian Learning CoRR Ranjitha Prasad, Chandra R. Murthy
2011	Misc	`conf`	Joint data detection and dominant singular mode estimation in time varying reciprocal MIMO systems. ICASSP Ranjitha Prasad, Bettagere Nagaraja Bharath, Chandra R. Murthy
2010	B	`conf`	Bayesian Learning for Joint Sparse OFDM Channel Estimation and Data Detection. GLOBECOM Ranjitha Prasad, Chandra R. Murthy
2008	B	`conf`	Robust Channel Tracking in Fast Fading MIMO channels. GLOBECOM Ranjitha Prasad, Krishnamurthy Giridhar