Ranjitha Prasad

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 33

Top Topics

Directed Acyclic

Causal Inference

Survival Analysis

Top Venues

IEEE Trans. Signal Process.

Publications

Gagandeep Kaur, Ranjitha Prasad
Exploiting Sparsity in Over-parameterized Federated Learning over Multiple Access Channels. COMAD/CODS (2024)
Nazreen Shah, Prachi Goyal, Ranjitha Prasad
Importance Sampling Based Federated Unsupervised Representation Learning. ICASSP (2024)
Varun Laxman Muttepawar, Arjun Mehra, Zubair Shaban, Ranjitha Prasad, Jagadeesh Harshan
Federated Learning for Wireless Applications: A Prototype. COMSNETS (2024)
Zubair Shaban, Ranjitha Prasad
Enhancing Federated Learning robustness in Wireless Networks. COMAD/CODS (2024)
Aadil Hussain, Nitheesh Gundapu, Sarang Drugkar, Suraj Kiran, J. Harshan, Ranjitha Prasad
Seeing is Believing: A Federated Learning Based Prototype to Detect Wireless Injection Attacks. CoRR (2023)
Praharsh Nanavati, Ranjitha Prasad
CLIMAX: An Exploration of Classifier-Based Contrastive Explanations. CogMI (2023)
Muskan Gupta, Gokul Kannan, Ranjitha Prasad, Garima Gupta
Deep Survival Analysis and Counterfactual Inference Using Balanced Representations. ICASSP (2023)
Varun Laxman Muttepawar, Arjun Mehra, Zubair Shaban, Ranjitha Prasad, Harshan Jagadeesh
Federated Learning for Wireless Applications: A Prototype. CoRR (2023)
Ayush Madhan-Sohini, Divin Dominic, Nazreen Shah, Ranjitha Prasad
Over-the-air Clustered Wireless Federated Learning. GLOBECOM (Workshops) (2023)
Praharsh Nanavati, Ranjitha Prasad
CLIMAX: An exploration of Classifier-Based Contrastive Explanations. CoRR (2023)
Ayush Madhan-Sohini, Divin Dominic, Nazreen Shah, Ranjitha Prasad
Over-The-Air Clustered Wireless Federated Learning. CoRR (2022)
Shilpi Mishra, J. Harshan, Ranjitha Prasad
Path-Aware OMP Algorithms for Provenance Recovery in Wireless Networks. VTC Spring (2022)
Aditya Saini, Ranjitha Prasad
Select Wisely and Explain: Active Learning and Probabilistic Local Post-hoc Explainability. AIES (2022)
Anish Madan, Ranjitha Prasad
B-Small: A Bayesian Neural Network Approach to Sparse Model-Agnostic Meta-Learning. ICASSP (2021)
Ansh Kumar Sharma, Rahul Kukreja, Ranjitha Prasad, Shilpa Rao
DAGSurv: Directed Ayclic Graph Based Survival Analysis Using Deep Neural Networks. ACML (2021)
Shilpi Mishra, J. Harshan, Ranjitha Prasad
Path-Aware OMP Algorithms for Provenance Recovery in Vehicular Networks. CoRR (2021)
Aditya Saini, Ranjitha Prasad
Locally Interpretable Model Agnostic Explanations using Gaussian Processes. CoRR (2021)
Ansh Kumar Sharma, Rahul Kukreja, Ranjitha Prasad, Shilpa Rao
DAGSurv: Directed Acyclic Graph Based Survival Analysis Using Deep Neural Networks. CoRR (2021)
Anish Madan, Ranjitha Prasad
B-SMALL: A Bayesian Neural Network approach to Sparse Model-Agnostic Meta-Learning. CoRR (2021)
Srinidhi Hegde, Ranjitha Prasad, Ramya Hebbalaguppe, Vishwajeet Kumar
Variational Student: Learning Compact and Sparser Networks In Knowledge Distillation Framework. ICASSP (2020)
Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff
Hi-CI: Deep Causal Inference in High Dimensions. CoRR (2020)
Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff
MultiMBNN: Matched and Balanced Causal Inference with Neural Networks. CoRR (2020)
Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff
Hi-CI: Deep Causal Inference in High Dimensions. CD@KDD (2020)
Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff
MultiMBNN: Matched and Balanced Causal Inference with Neural Networks. ESANN (2020)
Sachin Kumar, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff
CAMTA: Casual Attention Model for Multi-touch Attribution. CoRR (2020)
Sachin Kumar, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff
CAMTA: Causal Attention Model for Multi-touch Attribution. ICDM (Workshops) (2020)
Ankit Sharma, Garima Gupta, Ranjitha Prasad, Arnab Chatterjee, Lovekesh Vig, Gautam Shroff
MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population. CoRR (2019)
Garima Gupta, Vishal Sunder, Ranjitha Prasad, Gautam Shroff
CRESA: A Deep Learning Approach to Competing Risks, Recurrent Event Survival Analysis. PAKDD (2) (2019)
Srinidhi Hegde, Ranjitha Prasad, Ramya Hebbalaguppe, Vishwajith Kumar
Variational Student: Learning Compact and Sparser Networks in Knowledge Distillation Framework. CoRR (2019)
Mine Alsan, Ranjitha Prasad, Vincent Y. F. Tan
Lower Bounds on the Bayes Risk of the Bayesian BTL Model With Applications to Comparison Graphs. IEEE J. Sel. Top. Signal Process. 12 (5) (2018)
Ranjitha Prasad
Unlabelled Sensing: A Sparse Bayesian Learning Approach. CoRR (2018)
Ranjitha Prasad, Vincent Y. F. Tan
Inference Algorithms for the Multiplicative Mixture Mallows Model. SPCOM (2018)
Mine Alsan, Ranjitha Prasad, Vincent Y. F. Tan
Lower Bounds on the Bayes Risk of the Bayesian BTL Model with Applications to Random Graphs. CoRR (2017)
Ranjitha Prasad, Chandra R. Murthy, Bhaskar D. Rao
Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach. IEEE Trans. Signal Process. 63 (20) (2015)
Vinuthna Vinjamuri, Ranjitha Prasad, Chandra R. Murthy
Sparse signal recovery in the presence of colored noise and rank-deficient noise covariance matrix: An SBL approach. ICASSP (2015)
Geethu Joseph, Chandra R. Murthy, Ranjitha Prasad, Bhaskar D. Rao
Online Recovery of Temporally Correlated Sparse Signals Using Multiple Measurement Vectors. GLOBECOM (2015)
Ranjitha Prasad, Chandra R. Murthy
Joint channel estimation and data detection in MIMO-OFDM systems using sparse Bayesian learning. NCC (2014)
Ranjitha Prasad, Chandra R. Murthy, Bhaskar D. Rao
Nested Sparse Bayesian Learning for block-sparse signals with intra-block correlation. ICASSP (2014)
Ranjitha Prasad, Chandra R. Murthy, Bhaskar D. Rao
Joint Approximately Sparse Channel Estimation and Data Detection in OFDM Systems Using Sparse Bayesian Learning. IEEE Trans. Signal Process. 62 (14) (2014)
Ranjitha Prasad, Chandra R. Murthy
Cramér-Rao-Type Bounds for Sparse Bayesian Learning. IEEE Trans. Signal Process. 61 (3) (2013)
Ranjitha Prasad, Chandra R. Murthy
Cramer Rao-Type Bounds for Sparse Bayesian Learning CoRR (2012)
Ranjitha Prasad, Bettagere Nagaraja Bharath, Chandra R. Murthy
Joint data detection and dominant singular mode estimation in time varying reciprocal MIMO systems. ICASSP (2011)
Ranjitha Prasad, Chandra R. Murthy
Bayesian Learning for Joint Sparse OFDM Channel Estimation and Data Detection. GLOBECOM (2010)
Ranjitha Prasad, Krishnamurthy Giridhar
Robust Channel Tracking in Fast Fading MIMO channels. GLOBECOM (2008)