Prashant Khanduri

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 53

Top Topics

Hypothesis Test

Signal Detection

Convex Optimization

Top Venues

IEEE Trans. Signal Process.

Publications

Minghong Fang, Zifan Zhang, Hairi, Prashant Khanduri, Jia Liu, Songtao Lu, Yuchen Liu, Neil Zhenqiang Gong
Byzantine-Robust Decentralized Federated Learning. CoRR (2024)
Haibo Yang, Peiwen Qiu, Prashant Khanduri, Minghong Fang, Jia Liu
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation. CoRR (2024)
Yihua Zhang, Prashant Khanduri, Ioannis C. Tsaknakis, Yuguang Yao, Mingyi Hong, Sijia Liu
An Introduction to Bilevel Optimization: Foundations and applications in signal processing and machine learning. IEEE Signal Process. Mag. 41 (1) (2024)
Yao Qiang, Chengyin Li, Prashant Khanduri, Dongxiao Zhu
Fairness-aware Vision Transformer via Debiased Self-Attention. CoRR (2023)
Prashant Khanduri, Chengyin Li, Rafi Ibn Sultan, Yao Qiang, Jörg Kliewer, Dongxiao Zhu
FedDRO: Federated Compositional Optimization for Distributionally Robust Learning. CoRR (2023)
Peiwen Qiu, Yining Li, Zhuqing Liu, Prashant Khanduri, Jia Liu, Ness B. Shroff, Elizabeth Serena Bentley, Kurt A. Turck
DIAMOND: Taming Sample and Communication Complexities in Decentralized Bilevel Optimization. INFOCOM (2023)
Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, Jia Liu
Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning. ICML (2023)
Chengyin Li, Yao Qiang, Rafi Ibn Sultan, Hassan Bagher-Ebadian, Prashant Khanduri, Indrin J. Chetty, Dongxiao Zhu
FocalUNETR: A Focal Transformer for Boundary-Aware Prostate Segmentation Using CT Images. MICCAI (3) (2023)
Ioannis C. Tsaknakis, Prashant Khanduri, Mingyi Hong
An Implicit Gradient Method for Constrained Bilevel Problems Using Barrier Approximation. ICASSP (2023)
Bingqing Song, Prashant Khanduri, Xinwei Zhang, Jinfeng Yi, Mingyi Hong
FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks. ICML (2023)
Shruti M., Prashant Khanduri, B. N. Bharath
FedAvg for Minimizing Polyak-Łojasiewicz Objectives: The Interpolation Regime. ACSSC (2023)
Yao Qiang, Chengyin Li, Prashant Khanduri, Dongxiao Zhu
Interpretability-Aware Vision Transformer. CoRR (2023)
Chengyin Li, Prashant Khanduri, Yao Qiang, Rafi Ibn Sultan, Indrin J. Chetty, Dongxiao Zhu
Auto-Prompting SAM for Mobile Friendly 3D Medical Image Segmentation. CoRR (2023)
Rafi Ibn Sultan, Chengyin Li, Hui Zhu, Prashant Khanduri, Marco Brocanelli, Dongxiao Zhu
GeoSAM: Fine-tuning SAM with Sparse and Dense Visual Prompting for Automated Segmentation of Mobility Infrastructure. CoRR (2023)
Yihua Zhang, Prashant Khanduri, Ioannis C. Tsaknakis, Yuguang Yao, Mingyi Hong, Sijia Liu
An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning. CoRR (2023)
Prashant Khanduri, Ioannis C. Tsaknakis, Yihua Zhang, Jia Liu, Sijia Liu, Jiawei Zhang, Mingyi Hong
Linearly Constrained Bilevel Optimization: A Smoothed Implicit Gradient Approach. ICML (2023)
Prashant Khanduri, Haibo Yang, Mingyi Hong, Jia Liu, Hoi-To Wai, Sijia Liu
Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach. ICLR (2022)
Haibo Yang, Xin Zhang, Prashant Khanduri, Jia Liu
Anarchic Federated Learning. ICML (2022)
Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, Jia Liu
INTERACT: achieving low sample and communication complexities in decentralized bilevel learning over networks. MobiHoc (2022)
Ioannis C. Tsaknakis, Prashant Khanduri, Mingyi Hong
An Implicit Gradient-Type Method for Linearly Constrained Bilevel Problems. ICASSP (2022)
Yihua Zhang, Guanhua Zhang, Prashant Khanduri, Mingyi Hong, Shiyu Chang, Sijia Liu
Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization. ICML (2022)
Peiwen Qiu, Yining Li, Zhuqing Liu, Prashant Khanduri, Jia Liu, Ness B. Shroff, Elizabeth Serena Bentley, Kurt Turck
DIAMOND: Taming Sample and Communication Complexities in Decentralized Bilevel Optimization. CoRR (2022)
Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, Jia Liu
INTERACT: Achieving Low Sample and Communication Complexities in Decentralized Bilevel Learning over Networks. CoRR (2022)
Sabrina Bourmani, François-Xavier Socheleau, Dominique Pastor, Prashant Khanduri, Pramod K. Varshney
On Distributed Detection with Random Distortion Testing. ISIVC (2021)
Saikiran Bulusu, Prashant Khanduri, Swatantra Kafle, Pranay Sharma, Pramod K. Varshney
Byzantine Resilient Non-Convex SCSG With Distributed Batch Gradient Computations. IEEE Trans. Signal Inf. Process. over Networks 7 (2021)
Pranay Sharma, Prashant Khanduri, Lixin Shen, Donald J. Bucci, Pramod K. Varshney
On Distributed Online Convex Optimization with Sublinear Dynamic Regret and Fit. ACSCC (2021)
Prashant Khanduri, Pranay Sharma, Haibo Yang, Mingyi Hong, Jia Liu, Ketan Rajawat, Pramod K. Varshney
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning. NeurIPS (2021)
Prashant Khanduri, Siliang Zeng, Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang
A Momentum-Assisted Single-Timescale Stochastic Approximation Algorithm for Bilevel Optimization. CoRR (2021)
Yihua Zhang, Guanhua Zhang, Prashant Khanduri, Mingyi Hong, Shiyu Chang, Sijia Liu
Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization. CoRR (2021)
Haibo Yang, Xin Zhang, Prashant Khanduri, Jia Liu
Anarchic Federated Learning. CoRR (2021)
Xiancheng Cheng, Baocheng Geng, Prashant Khanduri, Baixiao Chen, Pramod K. Varshney
Joint Collaboration and Compression Design for Random Signal Detection in Wireless Sensor Networks. IEEE Signal Process. Lett. 28 (2021)
Prashant Khanduri, Siliang Zeng, Mingyi Hong, Hoi-To Wai, Zhaoran Wang, Zhuoran Yang
A Near-Optimal Algorithm for Stochastic Bilevel Optimization via Double-Momentum. NeurIPS (2021)
Xiancheng Cheng, Prashant Khanduri, Baixiao Chen, Pramod K. Varshney
Joint Collaboration and Compression Design for Distributed Sequential Estimation in a Wireless Sensor Network. IEEE Trans. Signal Process. 69 (2021)
Prashant Khanduri, Pranay Sharma, Haibo Yang, Mingyi Hong, Jia Liu, Ketan Rajawat, Pramod K. Varshney
STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning. CoRR (2021)
Prashant Khanduri, Pranay Sharma, Swatantra Kafle, Saikiran Bulusu, Ketan Rajawat, Pramod K. Varshney
Distributed Stochastic Non-Convex Optimization: Momentum-Based Variance Reduction. CoRR (2020)
Saikiran Bulusu, Prashant Khanduri, Pranay Sharma, Pramod K. Varshney
On Distributed Stochastic Gradient Descent for Nonconvex Functions in the Presence of Byzantines. ICASSP (2020)
Pranay Sharma, Prashant Khanduri, Lixin Shen, Donald J. Bucci Jr., Pramod K. Varshney
On Distributed Online Convex Optimization with Sublinear Dynamic Regret and Fit. CoRR (2020)
Shan Zhang, Prashant Khanduri, Pramod K. Varshney
Distributed Sequential Detection: Dependent Observations and Imperfect Communication. IEEE Trans. Signal Process. 68 (2020)
Prashant Khanduri, Lakshmi Narasimhan Theagarajan, Pramod K. Varshney
Online Design of Optimal Precoders for High Dimensional Signal Detection. IEEE Trans. Signal Process. 67 (15) (2019)
Prashant Khanduri, Lakshmi Narasimhan Theagarajan, Pramod K. Varshney
Online Linear Compression with Side Information for Distributed Detection of High Dimensional Signals. SPAWC (2019)
Pranay Sharma, Prashant Khanduri, Saikiran Bulusu, Ketan Rajawat, Pramod K. Varshney
Parallel Restarted SPIDER - Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity. CoRR (2019)
Prashant Khanduri, Dominique Pastor, Vinod Sharma, Pramod K. Varshney
Truncated Sequential Non-Parametric Hypothesis Testing Based on Random Distortion Testing. IEEE Trans. Signal Process. 67 (15) (2019)
Prashant Khanduri, Dominique Pastor, Vinod Sharma, Pramod K. Varshney
Sequential Random Distortion Testing of Non-Stationary Processes. IEEE Trans. Signal Process. 67 (21) (2019)
Prashant Khanduri, Saikiran Bulusu, Pranay Sharma, Pramod K. Varshney
Byzantine Resilient Non-Convex SVRG with Distributed Batch Gradient Computations. CoRR (2019)
Shan Zhang, Prashant Khanduri, Pramod K. Varshney
Distributed Sequential Hypothesis Testing with Dependent Sensor Observations. ACSSC (2019)
Prashant Khanduri, Dominique Pastor, Vinod Sharma, Pramod K. Varshney
. Allerton (2018)
Prashant Khanduri, Lakshmi Narasimhan Theagarajan, Pramod K. Varshney
Online Design of Precoders for High Dimensional Signal Detection in Wireless Sensor Networks. FUSION (2018)
Kush R. Varshney, Prashant Khanduri, Pranay Sharma, Shan Zhang, Pramod K. Varshney
Why Interpretability in Machine Learning? An Answer Using Distributed Detection and Data Fusion Theory. CoRR (2018)
Prashant Khanduri, Dominique Pastor, Vinod Sharma, Pramod K. Varshney
On Sequential Random Distortion Testing of Non-Stationary Processes. ICASSP (2018)
Prashant Khanduri, Aditya Vempaty, Pramod K. Varshney
A unified diversity measure for distributed inference. ICASSP (2017)
Prashant Khanduri, Vinod Sharma, Pramod K. Varshney
Detection diversity of spatio-temporal data using Pitman's efficiency for low SNR regimes. GlobalSIP (2016)
Prashant Khanduri, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Pramod K. Varshney
Universal Collaboration Strategies for Signal Detection: A Sparse Learning Approach. IEEE Signal Process. Lett. 23 (10) (2016)
Prashant Khanduri, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Pramod K. Varshney
Universal Collaboration Strategies for Signal Detection: A Sparse Learning Approach. CoRR (2016)
Prashant Khanduri, Bettagere Nagaraja Bharath, Chandra R. Murthy
Coverage analysis and training optimization for uplink cellular networks with practical channel estimation. GLOBECOM (2014)