Vinay Chakravarthi Gogineni

Orcid: 0000-0003-2171-9623

According to our database1, Vinay Chakravarthi Gogineni authored at least 53 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Lightweight Autonomous Autoencoders for Timely Hyperspectral Anomaly Detection.
IEEE Geosci. Remote. Sens. Lett., 2024

Analyzing the Impact of Partial Sharing on the Resilience of Online Federated Learning Against Model Poisoning Attacks.
CoRR, 2024

Efficient Knowledge Deletion from Trained Models through Layer-wise Partial Machine Unlearning.
CoRR, 2024

2023
Communication-Efficient Online Federated Learning Strategies for Kernel Regression.
IEEE Internet Things J., March, 2023

Algorithm and Architecture Design of Random Fourier Features-Based Kernel Adaptive Filters.
IEEE Trans. Circuits Syst. I Regul. Pap., February, 2023

Communication-Efficient and Privacy-Aware Distributed Learning.
IEEE Trans. Signal Inf. Process. over Networks, 2023

Personalized Graph Federated Learning With Differential Privacy.
IEEE Trans. Signal Inf. Process. over Networks, 2023

Asynchronous Online Federated Learning With Reduced Communication Requirements.
IEEE Internet Things J., 2023

Smoothing ADMM for Sparse-Penalized Quantile Regression with Non-Convex Penalties.
CoRR, 2023

Distributed Quantile Regression with Non-Convex Sparse Penalties.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2023

Resource-Efficient Federated Learning Robust to Communication Errors.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2023

Networked Personalized Federated Learning Using Reinforcement Learning.
Proceedings of the IEEE International Conference on Communications, 2023

Autoencoder-based Hyperspectral Anomaly Detection using Kernel Principal Component Pre-Processing.
Proceedings of the 31st European Signal Processing Conference, 2023

Continual Local Updates for Federated Learning with Enhanced Robustness to Link Noise.
Proceedings of the Asia Pacific Signal and Information Processing Association Annual Summit and Conference, 2023

2022
Novel VLSI Architecture for Fractional-Order Correntropy Adaptive Filtering Algorithm.
IEEE Trans. Very Large Scale Integr. Syst., 2022

Kernel Regression Over Graphs Using Random Fourier Features.
IEEE Trans. Signal Process., 2022

Personalized Online Federated Learning for IoT/CPS: Challenges and Future Directions.
IEEE Internet Things Mag., 2022

Resource-Aware Asynchronous Online Federated Learning for Nonlinear Regression.
Proceedings of the IEEE International Conference on Communications, 2022

Communication-Efficient Online Federated Learning Framework for Nonlinear Regression.
Proceedings of the IEEE International Conference on Acoustics, 2022

Communication-Efficient and Privacy-Aware Distributed LMS Algorithm.
Proceedings of the 25th International Conference on Information Fusion, 2022

ADMM for Sparse-Penalized Quantile Regression with Non-Convex Penalties.
Proceedings of the 30th European Signal Processing Conference, 2022

Dynamic Graph Topology Learning with Non-Convex Penalties.
Proceedings of the 30th European Signal Processing Conference, 2022

Decentralized Graph Federated Multitask Learning for Streaming Data.
Proceedings of the 56th Annual Conference on Information Sciences and Systems, 2022

Clustered Graph Federated Personalized Learning.
Proceedings of the 56th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2022, Pacific Grove, CA, USA, October 31, 2022

2021
Adaptive Graph Filters in Reproducing Kernel Hilbert Spaces: Design and Performance Analysis.
IEEE Trans. Signal Inf. Process. over Networks, 2021

Performance of Clustered Multitask Diffusion LMS Suffering From Inter-Node Communication Delays.
IEEE Trans. Circuits Syst. II Express Briefs, 2021

Data-Driven Personalized Cervical Cancer Risk Prediction: A Graph-Perspective.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2021

Kernel Regression on Graphs in Random Fourier Features Space.
Proceedings of the IEEE International Conference on Acoustics, 2021

Graph Kernel Recursive Least-Squares Algorithms.
Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2021

Recurrent Time-Varying Multi-Graph Convolutional Neural Network for Personalized Cervical Cancer Risk Prediction.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020
Fractional-Order Correntropy Filters for Tracking Dynamic Systems in α-Stable Environments.
IEEE Trans. Circuits Syst., 2020

Improving the Performance of Multitask Diffusion APA via Controlled Inter-Cluster Cooperation.
IEEE Trans. Circuits Syst. I Regul. Pap., 2020

Fractional-Order Correntropy Adaptive Filters for Distributed Processing of $\alpha$-Stable Signals.
IEEE Signal Process. Lett., 2020

Graph Diffusion Kernel LMS using Random Fourier Features.
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019
Robust Proportionate Adaptive Filter Architectures Under Impulsive Noise.
IEEE Trans. Very Large Scale Integr. Syst., 2019

Partial Diffusion Affine Projection Algorithm Over Clustered Multitask Networks.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2019

2018
Algorithm and VLSI Architecture Design of Proportionate-Type LMS Adaptive Filters for Sparse System Identification.
IEEE Trans. Very Large Scale Integr. Syst., 2018

Improved proportionate-type sparse adaptive filtering under maximum correntropy criterion in impulsive noise environments.
Digit. Signal Process., 2018

An adaptive convex combination of APA and ZA-APA for identifying systems having variable sparsity and correlated input.
Digit. Signal Process., 2018

Diffusion Affine Projection Algorithm for Multitask Networks.
Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2018

2017
Algorithm and Architecture Design of Adaptive Filters With Error Nonlinearities.
IEEE Trans. Very Large Scale Integr. Syst., 2017

A Convex Combination of NLMS and ZA-NLMS for Identifying Systems With Variable Sparsity.
IEEE Trans. Circuits Syst. II Express Briefs, 2017

A novel framework for compressed sensing based scalable video coding.
Signal Process. Image Commun., 2017

Constrained Least Mean Logarithmic Square Algorithm: Design and Performance Analysis.
CoRR, 2017

Algorithm/Architecture Co-design of Proportionate-type LMS Adaptive Filters for Sparse System Identification.
CoRR, 2017

Proportionate Adaptive Filtering under Correntropy Criterion in Impulsive Noise Environments.
CoRR, 2017

2016
VLSI Friendly Framework for Scalable Video Coding based on Compressed Sensing.
CoRR, 2016

Performance analysis of proportionate-type LMS algorithms.
Proceedings of the Signal Processing: Algorithms, 2016

2015
Convergence Analysis of Proportionate-type Least Mean Square Algorithms.
CoRR, 2015

Distributed Multi-task APA over Adaptive Networks Based on Partial Diffusion.
CoRR, 2015

Diffusion Adaptation Over Clustered Multitask Networks Based on the Affine Projection Algorithm.
CoRR, 2015

Adaptive Convex Combination of APA and ZA-APA algorithms for Sparse System Identification.
CoRR, 2015

2014
Proportionate-type hard thresholding adaptive filter for sparse system identification.
Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2014


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