Ranjitha Prasad

According to our database, Ranjitha Prasad authored at least 39 papers between 2008 and 2024.

Collaborative distances:

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

2024

On Homomorphic Encryption Based Strategies for Class Imbalance in Federated Learning.

Arpit Guleria, J. Harshan, Ranjitha Prasad, B. N. Bharath

CoRR, 2024

Seeing is Believing: A Federated Learning Based Prototype to Detect Wireless Injection Attacks.

Aadil Hussain, Nitheesh Gundapu, Sarang Drugkar, Suraj Kiran, J. Harshan, Ranjitha Prasad

Proceedings of the 99th IEEE Vehicular Technology Conference, 2024

Importance Sampling Based Federated Unsupervised Representation Learning.

Nazreen Shah, Prachi Goyal, Ranjitha Prasad

Proceedings of the IEEE International Conference on Acoustics, 2024

Over The Air Federated Learning in the Presence of Impulsive Noise.

Zubair Shaban, Ranjitha Prasad, Pooja Kumari

Proceedings of the IEEE International Conference on Acoustics, 2024

Federated Learning for Wireless Applications: A Prototype.

Varun Laxman Muttepawar, Arjun Mehra, Zubair Shaban, Ranjitha Prasad, Jagadeesh Harshan

Proceedings of the 16th International Conference on COMmunication Systems & NETworkS, 2024

Enhancing Federated Learning robustness in Wireless Networks.

Zubair Shaban, Ranjitha Prasad

Proceedings of the 7th Joint International Conference on Data Science & Management of Data (11th ACM IKDD CODS and 29th COMAD), 2024

Exploiting Sparsity in Over-parameterized Federated Learning over Multiple Access Channels.

Gagandeep Kaur, Ranjitha Prasad

Proceedings of the 7th Joint International Conference on Data Science & Management of Data (11th ACM IKDD CODS and 29th COMAD), 2024

2023

Deep Survival Analysis and Counterfactual Inference Using Balanced Representations.

Muskan Gupta, Gokul Kannan, Ranjitha Prasad, Garima Gupta

Proceedings of the IEEE International Conference on Acoustics, 2023

Over-the-air Clustered Wireless Federated Learning.

Ayush Madhan-Sohini, Divin Dominic, Nazreen Shah, Ranjitha Prasad

Proceedings of the IEEE Globecom Workshops 2023, 2023

CLIMAX: An Exploration of Classifier-Based Contrastive Explanations.

Praharsh Nanavati, Ranjitha Prasad

Proceedings of the 5th IEEE International Conference on Cognitive Machine Intelligence, 2023

2022

Path-Aware OMP Algorithms for Provenance Recovery in Wireless Networks.

Shilpi Mishra, J. Harshan, Ranjitha Prasad

Proceedings of the 95th IEEE Vehicular Technology Conference, 2022

Select Wisely and Explain: Active Learning and Probabilistic Local Post-hoc Explainability.

Aditya Saini, Ranjitha Prasad

Proceedings of the AIES '22: AAAI/ACM Conference on AI, Ethics, and Society, Oxford, United Kingdom, May 19, 2022

2021

DAGSurv: Directed Acyclic Graph Based Survival Analysis Using Deep Neural Networks.

Ansh Kumar Sharma, Rahul Kukreja, Ranjitha Prasad, Shilpa Rao

CoRR, 2021

Locally Interpretable Model Agnostic Explanations using Gaussian Processes.

Aditya Saini, Ranjitha Prasad

CoRR, 2021

Path-Aware OMP Algorithms for Provenance Recovery in Vehicular Networks.

Shilpi Mishra, J. Harshan, Ranjitha Prasad

CoRR, 2021

B-Small: A Bayesian Neural Network Approach to Sparse Model-Agnostic Meta-Learning.

Anish Madan, Ranjitha Prasad

Proceedings of the IEEE International Conference on Acoustics, 2021

DAGSurv: Directed Ayclic Graph Based Survival Analysis Using Deep Neural Networks.

Ansh Kumar Sharma, Rahul Kukreja, Ranjitha Prasad, Shilpa Rao

Proceedings of the Asian Conference on Machine Learning, 2021

2020

CAMTA: Casual Attention Model for Multi-touch Attribution.

Sachin Kumar, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff

CoRR, 2020

Hi-CI: Deep Causal Inference in High Dimensions.

Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff

Proceedings of the 2020 KDD Workshop on Causal Discovery (CD@KDD 2020), 2020

CAMTA: Causal Attention Model for Multi-touch Attribution.

Sachin Kumar, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff

Proceedings of the 20th International Conference on Data Mining Workshops, 2020

Variational Student: Learning Compact and Sparser Networks In Knowledge Distillation Framework.

Srinidhi Hegde, Ranjitha Prasad, Ramya Hebbalaguppe, Vishwajeet Kumar

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

MultiMBNN: Matched and Balanced Causal Inference with Neural Networks.

Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff

Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

2019

MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population.

Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff

CoRR, 2019

Variational Student: Learning Compact and Sparser Networks in Knowledge Distillation Framework.

Srinidhi Hegde, Ranjitha Prasad, Ramya Hebbalaguppe, Vishwajith Kumar

CoRR, 2019

CRESA: A Deep Learning Approach to Competing Risks, Recurrent Event Survival Analysis.

Garima Gupta, Vishal Sunder, Ranjitha Prasad, Gautam Shroff

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

2018

Lower Bounds on the Bayes Risk of the Bayesian BTL Model With Applications to Comparison Graphs.

Mine Alsan, Ranjitha Prasad, Vincent Y. F. Tan

IEEE J. Sel. Top. Signal Process., 2018

Unlabelled Sensing: A Sparse Bayesian Learning Approach.

Ranjitha Prasad

CoRR, 2018

Inference Algorithms for the Multiplicative Mixture Mallows Model.

Ranjitha Prasad, Vincent Y. F. Tan

Proceedings of the 2018 International Conference on Signal Processing and Communications (SPCOM), 2018

2017

Lower Bounds on the Bayes Risk of the Bayesian BTL Model with Applications to Random Graphs.

Mine Alsan, Ranjitha Prasad, Vincent Y. F. Tan

CoRR, 2017

2015

Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach.

Ranjitha Prasad, Chandra R. Murthy, Bhaskar D. Rao

IEEE Trans. Signal Process., 2015

Sparse signal recovery in the presence of colored noise and rank-deficient noise covariance matrix: An SBL approach.

Vinuthna Vinjamuri, Ranjitha Prasad, Chandra R. Murthy

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Online Recovery of Temporally Correlated Sparse Signals Using Multiple Measurement Vectors.

Geethu Joseph, Chandra R. Murthy, Ranjitha Prasad, Bhaskar D. Rao

Proceedings of the 2015 IEEE Global Communications Conference, 2015

2014

Joint Approximately Sparse Channel Estimation and Data Detection in OFDM Systems Using Sparse Bayesian Learning.

Ranjitha Prasad, Chandra R. Murthy, Bhaskar D. Rao

IEEE Trans. Signal Process., 2014

Joint channel estimation and data detection in MIMO-OFDM systems using sparse Bayesian learning.

Ranjitha Prasad, Chandra R. Murthy

Proceedings of the Twentieth National Conference on Communications, 2014

Nested Sparse Bayesian Learning for block-sparse signals with intra-block correlation.

Ranjitha Prasad, Chandra R. Murthy, Bhaskar D. Rao

Proceedings of the IEEE International Conference on Acoustics, 2014

2013

Cramér-Rao-Type Bounds for Sparse Bayesian Learning.

Ranjitha Prasad, Chandra R. Murthy

IEEE Trans. Signal Process., 2013

2011

Joint data detection and dominant singular mode estimation in time varying reciprocal MIMO systems.

Ranjitha Prasad, Bettagere Nagaraja Bharath, Chandra R. Murthy

Proceedings of the IEEE International Conference on Acoustics, 2011

2010

Bayesian Learning for Joint Sparse OFDM Channel Estimation and Data Detection.

Ranjitha Prasad, Chandra R. Murthy

Proceedings of the Global Communications Conference, 2010

2008

Robust Channel Tracking in Fast Fading MIMO channels.

Ranjitha Prasad, Krishnamurthy Giridhar

Proceedings of the Global Communications Conference, 2008. GLOBECOM 2008, New Orleans, LA, USA, 30 November, 2008