Coverage analysis and training optimization for uplink cellular networks with practical channel estimation. - Prashant Khanduri; Bettagere Nagaraja Bharath; Chandra R. Murthy (GLOBECOM, 2014)

Detection diversity of spatio-temporal data using Pitman's efficiency for low SNR regimes. - Prashant Khanduri; Vinod Sharma; Pramod K. Varshney (GlobalSIP, 2016)

Universal Collaboration Strategies for Signal Detection: A Sparse Learning Approach. - Prashant Khanduri; Bhavya Kailkhura; Jayaraman J. Thiagarajan; Pramod K. Varshney (IEEE Signal Process. Lett., 2016)

A unified diversity measure for distributed inference. - Prashant Khanduri; Aditya Vempaty; Pramod K. Varshney (ICASSP, 2017)

On Random Distortion Testing Based Sequential Non-Parametric Hypothesis Testing*. - Prashant Khanduri; Dominique Pastor; Vinod Sharma; Pramod K. Varshney (Allerton, 2018)

Online Design of Precoders for High Dimensional Signal Detection in Wireless Sensor Networks. - Prashant Khanduri; Lakshmi Narasimhan Theagarajan; Pramod K. Varshney (FUSION, 2018)

Why Interpretability in Machine Learning? An Answer Using Distributed Detection and Data Fusion Theory. - Kush R. Varshney; Prashant Khanduri; Pranay Sharma; Shan Zhang 007; Pramod K. Varshney (CoRR, 2018)

Distributed Sequential Hypothesis Testing with Dependent Sensor Observations. - Shan Zhang 007; Prashant Khanduri; Pramod K. Varshney (ACSSC, 2019)

Online Linear Compression with Side Information for Distributed Detection of High Dimensional Signals. - Prashant Khanduri; Lakshmi Narasimhan Theagarajan; Pramod K. Varshney (SPAWC, 2019)

Byzantine Resilient Non-Convex SVRG with Distributed Batch Gradient Computations. - Prashant Khanduri; Saikiran Bulusu; Pranay Sharma; Pramod K. Varshney (CoRR, 2019)

Parallel Restarted SPIDER - Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity. - Pranay Sharma; Prashant Khanduri; Saikiran Bulusu; Ketan Rajawat; Pramod K. Varshney (CoRR, 2019)

Truncated Sequential Non-Parametric Hypothesis Testing Based on Random Distortion Testing. - Prashant Khanduri; Dominique Pastor; Vinod Sharma; Pramod K. Varshney (IEEE Trans. Signal Process., 2019)

Sequential Random Distortion Testing of Non-Stationary Processes. - Prashant Khanduri; Dominique Pastor; Vinod Sharma; Pramod K. Varshney (IEEE Trans. Signal Process., 2019)

Online Design of Optimal Precoders for High Dimensional Signal Detection. - Prashant Khanduri; Lakshmi Narasimhan Theagarajan; Pramod K. Varshney (IEEE Trans. Signal Process., 2019)

On Distributed Stochastic Gradient Descent for Nonconvex Functions in the Presence of Byzantines. - Saikiran Bulusu; Prashant Khanduri; Pranay Sharma; Pramod K. Varshney (ICASSP, 2020)

Distributed Stochastic Non-Convex Optimization: Momentum-Based Variance Reduction. - Prashant Khanduri; Pranay Sharma; Swatantra Kafle; Saikiran Bulusu; Ketan Rajawat; Pramod K. Varshney (CoRR, 2020)

Distributed Sequential Detection: Dependent Observations and Imperfect Communication. - Shan Zhang 007; Prashant Khanduri; Pramod K. Varshney (IEEE Trans. Signal Process., 2020)

On Distributed Online Convex Optimization with Sublinear Dynamic Regret and Fit. - Pranay Sharma; Prashant Khanduri; Lixin Shen; Donald J. Bucci; Pramod K. Varshney (ACSCC, 2021)

On Distributed Detection with Random Distortion Testing. - Sabrina Bourmani; François-Xavier Socheleau; Dominique Pastor; Prashant Khanduri; Pramod K. Varshney (ISIVC, 2021)

STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning. - Prashant Khanduri; Pranay Sharma; Haibo Yang 001; Mingyi Hong 001; Jia Liu 002; Ketan Rajawat; Pramod K. Varshney (NeurIPS, 2021)

A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum. - Prashant Khanduri; Siliang Zeng; Mingyi Hong 001; Hoi-To Wai; Zhaoran Wang 001; Zhuoran Yang (NeurIPS, 2021)

A Momentum-Assisted Single-Timescale Stochastic Approximation Algorithm for Bilevel Optimization. - Prashant Khanduri; Siliang Zeng; Mingyi Hong 001; Hoi-To Wai; Zhaoran Wang 001; Zhuoran Yang (CoRR, 2021)

Joint Collaboration and Compression Design for Random Signal Detection in Wireless Sensor Networks. - Xiancheng Cheng; Baocheng Geng; Prashant Khanduri; Baixiao Chen; Pramod K. Varshney (IEEE Signal Process. Lett., 2021)

Byzantine Resilient Non-Convex SCSG With Distributed Batch Gradient Computations. - Saikiran Bulusu; Prashant Khanduri; Swatantra Kafle; Pranay Sharma; Pramod K. Varshney (IEEE Trans. Signal Inf. Process. over Networks, 2021)

Joint Collaboration and Compression Design for Distributed Sequential Estimation in a Wireless Sensor Network. - Xiancheng Cheng; Prashant Khanduri; Baixiao Chen; Pramod K. Varshney (IEEE Trans. Signal Process., 2021)

An Implicit Gradient-Type Method for Linearly Constrained Bilevel Problems. - Ioannis C. Tsaknakis; Prashant Khanduri; Mingyi Hong 001 (ICASSP, 2022)

Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach. - Prashant Khanduri; Haibo Yang 001; Mingyi Hong 001; Jia Liu 002; Hoi-To Wai; Sijia Liu 001 (ICLR, 2022)

Anarchic Federated Learning. - Haibo Yang 001; Xin Zhang 054; Prashant Khanduri; Jia Liu 002 (ICML, 2022)

Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization. - Yihua Zhang; Guanhua Zhang; Prashant Khanduri; Mingyi Hong 001; Shiyu Chang; Sijia Liu 001 (ICML, 2022)

INTERACT: achieving low sample and communication complexities in decentralized bilevel learning over networks. - Zhuqing Liu; Xin Zhang 054; Prashant Khanduri; Songtao Lu; Jia Liu 002 (MobiHoc, 2022)

FedAvg for Minimizing Polyak-Łojasiewicz Objectives: The Interpolation Regime. - Shruti M.; Prashant Khanduri; B. N. Bharath 001 (ACSSC, 2023)

An Implicit Gradient Method for Constrained Bilevel Problems Using Barrier Approximation. - Ioannis C. Tsaknakis; Prashant Khanduri; Mingyi Hong 001 (ICASSP, 2023)

Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach. - Prashant Khanduri; Ioannis C. Tsaknakis; Yihua Zhang; Jia Liu 002; Sijia Liu 001; Jiawei Zhang 007; Mingyi Hong 001 (ICML, 2023)

Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning. - Zhuqing Liu; Xin Zhang 054; Prashant Khanduri; Songtao Lu; Jia Liu 002 (ICML, 2023)

FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks. - Bingqing Song; Prashant Khanduri; Xinwei Zhang 001; Jinfeng Yi; Mingyi Hong 001 (ICML, 2023)

DIAMOND: Taming Sample and Communication Complexities in Decentralized Bilevel Optimization. - Peiwen Qiu; Yining Li; Zhuqing Liu; Prashant Khanduri; Jia Liu 002; Ness B. Shroff; Elizabeth Serena Bentley; Kurt A. Turck (INFOCOM, 2023)

FocalUNETR: A Focal Transformer for Boundary-Aware Prostate Segmentation Using CT Images. - Chengyin Li; Yao Qiang; Rafi Ibn Sultan; Hassan Bagher-Ebadian; Prashant Khanduri; Indrin J. Chetty; Dongxiao Zhu (MICCAI (3), 2023)

An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning. - Yihua Zhang; Prashant Khanduri; Ioannis C. Tsaknakis; Yuguang Yao; Mingyi Hong 001; Sijia Liu 001 (CoRR, 2023)

Auto-Prompting SAM for Mobile Friendly 3D Medical Image Segmentation. - Chengyin Li; Prashant Khanduri; Yao Qiang; Rafi Ibn Sultan; Indrin J. Chetty; Dongxiao Zhu (CoRR, 2023)

Interpretability-Aware Vision Transformer. - Yao Qiang; Chengyin Li; Prashant Khanduri; Dongxiao Zhu (CoRR, 2023)

GeoSAM: Fine-tuning SAM with Sparse and Dense Visual Prompting for Automated Segmentation of Mobility Infrastructure. - Rafi Ibn Sultan; Chengyin Li; Hui Zhu 016; Prashant Khanduri; Marco Brocanelli; Dongxiao Zhu (CoRR, 2023)

FedDRO: Federated Compositional Optimization for Distributionally Robust Learning. - Prashant Khanduri; Chengyin Li; Rafi Ibn Sultan; Yao Qiang; Jörg Kliewer; Dongxiao Zhu (CoRR, 2023)

Byzantine-Robust Decentralized Federated Learning. - Minghong Fang; Zifan Zhang; Hairi; Prashant Khanduri; Jia Liu 002; Songtao Lu; Yuchen Liu 001; Neil Gong 001 (CCS, 2024)

Fairness-Aware Vision Transformer via Debiased Self-Attention. - Yao Qiang; Chengyin Li; Prashant Khanduri; Dongxiao Zhu (ECCV (37), 2024)

Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation. - Haibo Yang 001; Peiwen Qiu; Prashant Khanduri; Minghong Fang; Jia Liu 002 (ICML, 2024)

SHARE: A Distributed Learning Framework For Multivariate Time-Series Forecasting. - Wei Ye 009; Prashant Khanduri; Jiangweizhi Peng; Feng Tian; Jun Gao; Jie Ding 002; Zhi-Li Zhang; Mingyi Hong 001 (SPAWC, 2024)

MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training. - Chengyin Li; Hui Zhu 016; Rafi Ibn Sultan; Hassan Bagher-Ebadian; Prashant Khanduri; Indrin J. Chetty; Kundan Thind; Dongxiao Zhu (CoRR, 2024)

An Introduction to Bilevel Optimization: Foundations and applications in signal processing and machine learning. - Yihua Zhang; Prashant Khanduri; Ioannis C. Tsaknakis; Yuguang Yao; Mingyi Hong 001; Sijia Liu 001 (IEEE Signal Process. Mag., 2024)

AutoProSAM: Automated Prompting SAM for 3D Multi-Organ Segmentation. - Chengyin Li; Rafi Ibn Sultan; Prashant Khanduri; Yao Qiang; Chetty J. Indrin; Dongxiao Zhu (WACV, 2025)

MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training. - Chengyin Li; Hui Zhu 016; Rafi Ibn Sultan; Hassan Bagher-Ebadian; Prashant Khanduri; Chetty J. Indrin; Kundan Thind; Dongxiao Zhu (WACV, 2025)

Linear Convergence of Decentralized FedAvg for PL Objectives: The Interpolation Regime. - Shruti P. Maralappanavar; Prashant Khanduri; B. N. Bharath 001 (Trans. Mach. Learn. Res., 2025)

Automatic Calibration for Membership Inference Attack on Large Language Models. - Saleh Zare Zade; Yao Qiang; Xiangyu Zhou; Hui Zhu 016; Mohammad Amin Roshani; Prashant Khanduri; Dongxiao Zhu (CoRR, 2025)

Not All Tokens Are Meant to Be Forgotten. - Xiangyu Zhou; Yao Qiang; Saleh Zare Zade; Douglas Zytko; Prashant Khanduri; Dongxiao Zhu (CoRR, 2025)