Prashant Khanduri

Orcid: 0000-0003-3055-2917

According to our database1, Prashant Khanduri authored at least 47 papers between 2014 and 2024.

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

Timeline

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Bibliography

2024
An Introduction to Bilevel Optimization: Foundations and applications in signal processing and machine learning.
IEEE Signal Process. Mag., January, 2024

Byzantine-Robust Decentralized Federated Learning.
CoRR, 2024

SHARE: A Distributed Learning Framework For Multivariate Time-Series Forecasting.
Proceedings of the 25th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2024

Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
FedDRO: Federated Compositional Optimization for Distributionally Robust Learning.
CoRR, 2023

GeoSAM: Fine-tuning SAM with Sparse and Dense Visual Prompting for Automated Segmentation of Mobility Infrastructure.
CoRR, 2023

Interpretability-Aware Vision Transformer.
CoRR, 2023

Auto-Prompting SAM for Mobile Friendly 3D Medical Image Segmentation.
CoRR, 2023

An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning.
CoRR, 2023

Fairness-aware Vision Transformer via Debiased Self-Attention.
CoRR, 2023

FocalUNETR: A Focal Transformer for Boundary-Aware Prostate Segmentation Using CT Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

DIAMOND: Taming Sample and Communication Complexities in Decentralized Bilevel Optimization.
Proceedings of the IEEE INFOCOM 2023, 2023

FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks.
Proceedings of the International Conference on Machine Learning, 2023

Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning.
Proceedings of the International Conference on Machine Learning, 2023

Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach.
Proceedings of the International Conference on Machine Learning, 2023

An Implicit Gradient Method for Constrained Bilevel Problems Using Barrier Approximation.
Proceedings of the IEEE International Conference on Acoustics, 2023

FedAvg for Minimizing Polyak-Łojasiewicz Objectives: The Interpolation Regime.
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

2022
INTERACT: achieving low sample and communication complexities in decentralized bilevel learning over networks.
Proceedings of the MobiHoc '22: The Twenty-third International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, Seoul, Republic of Korea, October 17, 2022

Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization.
Proceedings of the International Conference on Machine Learning, 2022

Anarchic Federated Learning.
Proceedings of the International Conference on Machine Learning, 2022

Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach.
Proceedings of the Tenth International Conference on Learning Representations, 2022

An Implicit Gradient-Type Method for Linearly Constrained Bilevel Problems.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
Joint Collaboration and Compression Design for Distributed Sequential Estimation in a Wireless Sensor Network.
IEEE Trans. Signal Process., 2021

Byzantine Resilient Non-Convex SCSG With Distributed Batch Gradient Computations.
IEEE Trans. Signal Inf. Process. over Networks, 2021

Joint Collaboration and Compression Design for Random Signal Detection in Wireless Sensor Networks.
IEEE Signal Process. Lett., 2021

A Momentum-Assisted Single-Timescale Stochastic Approximation Algorithm for Bilevel Optimization.
CoRR, 2021

A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Distributed Detection with Random Distortion Testing.
Proceedings of the 10th International Symposium on Signal, Image, Video and Communications, 2021

On Distributed Online Convex Optimization with Sublinear Dynamic Regret and Fit.
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020
Distributed Sequential Detection: Dependent Observations and Imperfect Communication.
IEEE Trans. Signal Process., 2020

Distributed Stochastic Non-Convex Optimization: Momentum-Based Variance Reduction.
CoRR, 2020

On Distributed Stochastic Gradient Descent for Nonconvex Functions in the Presence of Byzantines.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Online Design of Optimal Precoders for High Dimensional Signal Detection.
IEEE Trans. Signal Process., 2019

Sequential Random Distortion Testing of Non-Stationary Processes.
IEEE Trans. Signal Process., 2019

Truncated Sequential Non-Parametric Hypothesis Testing Based on Random Distortion Testing.
IEEE Trans. Signal Process., 2019

Parallel Restarted SPIDER - Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity.
CoRR, 2019

Byzantine Resilient Non-Convex SVRG with Distributed Batch Gradient Computations.
CoRR, 2019

Online Linear Compression with Side Information for Distributed Detection of High Dimensional Signals.
Proceedings of the 20th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2019

Distributed Sequential Hypothesis Testing with Dependent Sensor Observations.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018
Why Interpretability in Machine Learning? An Answer Using Distributed Detection and Data Fusion Theory.
CoRR, 2018

Online Design of Precoders for High Dimensional Signal Detection in Wireless Sensor Networks.
Proceedings of the 21st International Conference on Information Fusion, 2018

On Random Distortion Testing Based Sequential Non-Parametric Hypothesis Testing<sup>*</sup>.
Proceedings of the 56th Annual Allerton Conference on Communication, 2018

2017
A unified diversity measure for distributed inference.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016
Universal Collaboration Strategies for Signal Detection: A Sparse Learning Approach.
IEEE Signal Process. Lett., 2016

Detection diversity of spatio-temporal data using Pitman's efficiency for low SNR regimes.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

2014
Coverage analysis and training optimization for uplink cellular networks with practical channel estimation.
Proceedings of the IEEE Global Communications Conference, 2014


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