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ORCIDPrashant Khanduri
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2020 – today
- 2024
[j9]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): 38-59 (2024)- [c29]Minghong Fang, Zifan Zhang, Hairi, Prashant Khanduri, Jia Liu, Songtao Lu, Yuchen Liu, Neil Gong:
Byzantine-Robust Decentralized Federated Learning. CCS 2024: 2874-2888 - [c28]Yao Qiang, Chengyin Li, Prashant Khanduri, Dongxiao Zhu:
Fairness-Aware Vision Transformer via Debiased Self-Attention. ECCV (37) 2024: 358-376 - [c27]Haibo Yang, Peiwen Qiu, Prashant Khanduri, Minghong Fang, Jia Liu:
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation. ICML 2024 - [c26]Wei Ye, Prashant Khanduri, Jiangweizhi Peng, Feng Tian, Jun Gao, Jie Ding, Zhi-Li Zhang, Mingyi Hong:
SHARE: A Distributed Learning Framework For Multivariate Time-Series Forecasting. SPAWC 2024: 76-80 - [i21]Haibo Yang, Peiwen Qiu, Prashant Khanduri, Minghong Fang, Jia Liu:
Understanding Server-Assisted Federated Learning in the Presence of Incomplete Client Participation. CoRR abs/2405.02745 (2024) - [i20]Minghong Fang, Zifan Zhang, Hairi, Prashant Khanduri, Jia Liu, Songtao Lu, Yuchen Liu, Neil Zhenqiang Gong:
Byzantine-Robust Decentralized Federated Learning. CoRR abs/2406.10416 (2024) - [i19]Chengyin Li, Hui Zhu, Rafi Ibn Sultan, Hassan Bagher-Ebadian, Prashant Khanduri, Indrin J. Chetty, Kundan Thind, Dongxiao Zhu:
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating Training. CoRR abs/2411.15576 (2024) - 2023
- [c25]Shruti M., Prashant Khanduri, B. N. Bharath:
FedAvg for Minimizing Polyak-Łojasiewicz Objectives: The Interpolation Regime. ACSSC 2023: 607-613 - [c24]Ioannis C. Tsaknakis, Prashant Khanduri, Mingyi Hong:
An Implicit Gradient Method for Constrained Bilevel Problems Using Barrier Approximation. ICASSP 2023: 1-5 - [c23]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: 16291-16325 - [c22]Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, Jia Liu:
Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning. ICML 2023: 22420-22453 - [c21]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: 32304-32330 - [c20]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: 1-10 - [c19]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: 592-602 - [i18]Yao Qiang, Chengyin Li, Prashant Khanduri, Dongxiao Zhu:
Fairness-aware Vision Transformer via Debiased Self-Attention. CoRR abs/2301.13803 (2023) - [i17]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 abs/2308.00788 (2023) - [i16]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 abs/2308.14936 (2023) - [i15]Yao Qiang, Chengyin Li, Prashant Khanduri, Dongxiao Zhu:
Interpretability-Aware Vision Transformer. CoRR abs/2309.08035 (2023) - [i14]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 abs/2311.11319 (2023) - [i13]Prashant Khanduri, Chengyin Li, Rafi Ibn Sultan, Yao Qiang, Jörg Kliewer, Dongxiao Zhu:
FedDRO: Federated Compositional Optimization for Distributionally Robust Learning. CoRR abs/2311.12652 (2023) - 2022
- [c18]Ioannis C. Tsaknakis, Prashant Khanduri, Mingyi Hong:
An Implicit Gradient-Type Method for Linearly Constrained Bilevel Problems. ICASSP 2022: 5438-5442 - [c17]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 - [c16]Haibo Yang, Xin Zhang, Prashant Khanduri, Jia Liu:
Anarchic Federated Learning. ICML 2022: 25331-25363 - [c15]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: 26693-26712 - [c14]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: 61-70 - [i12]Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, Jia Liu:
INTERACT: Achieving Low Sample and Communication Complexities in Decentralized Bilevel Learning over Networks. CoRR abs/2207.13283 (2022) - [i11]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. CoRR abs/2212.02376 (2022) - 2021
- [j8]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: 1630-1634 (2021) - [j7]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: 754-766 (2021) - [j6]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: 5448-5462 (2021) - [c13]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: 1013-1017 - [c12]Sabrina Bourmani, François-Xavier Socheleau, Dominique Pastor, Prashant Khanduri, Pramod K. Varshney:
On Distributed Detection with Random Distortion Testing. ISIVC 2021: 1-6 - [c11]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: 6050-6061 - [c10]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: 30271-30283 - [i10]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 abs/2102.07367 (2021) - [i9]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 abs/2106.10435 (2021) - [i8]Haibo Yang, Xin Zhang, Prashant Khanduri, Jia Liu:
Anarchic Federated Learning. CoRR abs/2108.09875 (2021) - [i7]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 abs/2112.12376 (2021) - 2020
- [j5]Shan Zhang, Prashant Khanduri, Pramod K. Varshney:
Distributed Sequential Detection: Dependent Observations and Imperfect Communication. IEEE Trans. Signal Process. 68: 830-842 (2020) - [c9]Saikiran Bulusu, Prashant Khanduri, Pranay Sharma, Pramod K. Varshney:
On Distributed Stochastic Gradient Descent for Nonconvex Functions in the Presence of Byzantines. ICASSP 2020: 3137-3141 - [i6]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 abs/2001.03166 (2020) - [i5]Prashant Khanduri, Pranay Sharma, Swatantra Kafle, Saikiran Bulusu, Ketan Rajawat, Pramod K. Varshney:
Distributed Stochastic Non-Convex Optimization: Momentum-Based Variance Reduction. CoRR abs/2005.00224 (2020)
2010 – 2019
- 2019
- [j4]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): 4027-4042 (2019) - [j3]Prashant Khanduri, Lakshmi Narasimhan Theagarajan, Pramod K. Varshney:
Online Design of Optimal Precoders for High Dimensional Signal Detection. IEEE Trans. Signal Process. 67(15): 4122-4135 (2019) - [j2]Prashant Khanduri, Dominique Pastor, Vinod Sharma, Pramod K. Varshney:
Sequential Random Distortion Testing of Non-Stationary Processes. IEEE Trans. Signal Process. 67(21): 5450-5462 (2019) - [c8]Shan Zhang, Prashant Khanduri, Pramod K. Varshney:
Distributed Sequential Hypothesis Testing with Dependent Sensor Observations. ACSSC 2019: 1862-1866 - [c7]Prashant Khanduri, Lakshmi Narasimhan Theagarajan, Pramod K. Varshney:
Online Linear Compression with Side Information for Distributed Detection of High Dimensional Signals. SPAWC 2019: 1-5 - [i4]Prashant Khanduri, Saikiran Bulusu, Pranay Sharma, Pramod K. Varshney:
Byzantine Resilient Non-Convex SVRG with Distributed Batch Gradient Computations. CoRR abs/1912.04531 (2019) - [i3]Pranay Sharma, Prashant Khanduri, Saikiran Bulusu, Ketan Rajawat, Pramod K. Varshney:
Parallel Restarted SPIDER - Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity. CoRR abs/1912.06036 (2019) - 2018
- [c6]Prashant Khanduri, Dominique Pastor, Vinod Sharma, Pramod K. Varshney:
On Random Distortion Testing Based Sequential Non-Parametric Hypothesis Testing*. Allerton 2018: 328-334 - [c5]Prashant Khanduri, Lakshmi Narasimhan Theagarajan, Pramod K. Varshney:
Online Design of Precoders for High Dimensional Signal Detection in Wireless Sensor Networks. FUSION 2018: 2368-2375 - [c4]Prashant Khanduri, Dominique Pastor, Vinod Sharma, Pramod K. Varshney:
On Sequential Random Distortion Testing of Non-Stationary Processes. ICASSP 2018: 3944-3948 - [i2]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 abs/1806.09710 (2018) - 2017
- [c3]Prashant Khanduri, Aditya Vempaty, Pramod K. Varshney:
A unified diversity measure for distributed inference. ICASSP 2017: 3934-3938 - 2016
- [j1]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): 1484-1488 (2016) - [c2]Prashant Khanduri, Vinod Sharma, Pramod K. Varshney:
Detection diversity of spatio-temporal data using Pitman's efficiency for low SNR regimes. GlobalSIP 2016: 143-147 - [i1]Prashant Khanduri, Bhavya Kailkhura, Jayaraman J. Thiagarajan, Pramod K. Varshney:
Universal Collaboration Strategies for Signal Detection: A Sparse Learning Approach. CoRR abs/1601.06201 (2016) - 2014
- [c1]Prashant Khanduri, Bettagere Nagaraja Bharath, Chandra R. Murthy:
Coverage analysis and training optimization for uplink cellular networks with practical channel estimation. GLOBECOM 2014: 205-210
Coauthor Index
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