Suhas N. Diggavi

ORCID

Publication Activity (10 Years)

Years Active: 1995-2024
Publications (10 Years): 162

Top Venues

CoRR

ISIT

IEEE Trans. Inf. Theory

IEEE J. Sel. Areas Inf. Theory

Publications

Tomoyoshi Kimura, Jinyang Li, Tianshi Wang, Denizhan Kara, Yizhuo Chen, Yigong Hu, Ruijie Wang, Maggie B. Wigness, Shengzhong Liu, Mani B. Srivastava, Suhas N. Diggavi, Tarek F. Abdelzaher
On the Efficiency and Robustness of Vibration-based Foundation Models for IoT Sensing: A Case Study. CoRR (2024)
Antonious M. Girgis, Suhas N. Diggavi
Multi-Message Shuffled Privacy in Federated Learning. IEEE J. Sel. Areas Inf. Theory 5 (2024)
Osama A. Hanna, Antonious M. Girgis, Christina Fragouli, Suhas N. Diggavi
Differentially Private Stochastic Linear Bandits: (Almost) for Free. IEEE J. Sel. Areas Inf. Theory 5 (2024)
Kaan Ozkara, Bruce Huang, Ruida Zhou, Suhas N. Diggavi
Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning. CoRR (2024)
Navjot Singh, Xuanyu Cao, Suhas N. Diggavi, Tamer Basar
Decentralized multi-task stochastic optimization with compressed communications. Autom. 159 (2024)
Sundara Rajan Srinivasavaradhan, Pavlos Nikolopoulos, Christina Fragouli, Suhas N. Diggavi
Improving Group Testing via Gradient Descent. IEEE J. Sel. Areas Inf. Theory 5 (2024)
Kaan Ozkara, Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi
A Statistical Framework for Personalized Federated Learning and Estimation: Theory, Algorithms, and Privacy. ICLR (2023)
Navjot Singh, Suhas N. Diggavi
Representation Transfer Learning via Multiple Pre-trained models for Linear Regression. ISIT (2023)
Mohamad Rida Rammal, Suhas N. Diggavi, Ashutosh Sabharwal
Coded Estimation: Design of Backscatter Array Codes for 3D Orientation Estimation. IEEE Trans. Wirel. Commun. 22 (9) (2023)
Dhaivat Joshi, Suhas N. Diggavi, Mark J. P. Chaisson, Sreeram Kannan
HQAlign: Aligning nanopore reads for SV detection using current-level modeling. CoRR (2023)
Dhaivat Joshi, Suhas N. Diggavi, Mark J. P. Chaisson, Sreeram Kannan
HQAlign: aligning nanopore reads for SV detection using current-level modeling. Bioinform. 39 (10) (2023)
Xuanyu Cao, Tamer Basar, Suhas N. Diggavi, Yonina C. Eldar, Khaled B. Letaief, H. Vincent Poor, Junshan Zhang
Guest Editorial Communication-Efficient Distributed Learning Over Networks. IEEE J. Sel. Areas Commun. 41 (4) (2023)
Kaan Ozkara, Bruce Huang, Suhas N. Diggavi
Personalized PCA for Federated Heterogeneous Data. ISIT (2023)
Xuanyu Cao, Tamer Basar, Suhas N. Diggavi, Yonina C. Eldar, Khaled B. Letaief, H. Vincent Poor, Junshan Zhang
Communication-Efficient Distributed Learning: An Overview. IEEE J. Sel. Areas Commun. 41 (4) (2023)
Shengzhong Liu, Tomoyoshi Kimura, Dongxin Liu, Ruijie Wang, Jinyang Li, Suhas N. Diggavi, Mani B. Srivastava, Tarek F. Abdelzaher
FOCAL: Contrastive Learning for Multimodal Time-Series Sensing Signals in Factorized Orthogonal Latent Space. NeurIPS (2023)
Deepesh Data, Suhas N. Diggavi
Byzantine-Resilient High-Dimensional Federated Learning. IEEE Trans. Inf. Theory 69 (10) (2023)
Pavlos Nikolopoulos, Sundara Rajan Srinivasavaradhan, Tao Guo, Christina Fragouli, Suhas N. Diggavi
Community-Aware Group Testing. IEEE Trans. Inf. Theory 69 (7) (2023)
Navjot Singh, Suhas N. Diggavi
Representation Transfer Learning via Multiple Pre-trained models for Linear Regression. CoRR (2023)
Xinlin Li, Osama A. Hanna, Christina Fragouli, Suhas N. Diggavi, Gunjan Verma, Joydeep Bhattacharyya
Feature Compression for Multimodal Multi-Object Tracking. MILCOM (2023)
Osama A. Hanna, Xinlin Li, Suhas N. Diggavi, Christina Fragouli
Common Information Dimension. ISIT (2023)
Osama A. Hanna, Xinlin Li, Suhas N. Diggavi, Christina Fragouli
Common Information Dimension. CoRR (2023)
Walid A. Hanafy, Li Wu, Tarek F. Abdelzaher, Suhas N. Diggavi, Prashant J. Shenoy
Failure-Resilient ML Inference at the Edge through Graceful Service Degradation. MILCOM (2023)
Shengzhong Liu, Tomoyoshi Kimura, Dongxin Liu, Ruijie Wang, Jinyang Li, Suhas N. Diggavi, Mani B. Srivastava, Tarek F. Abdelzaher
FOCAL: Contrastive Learning for Multimodal Time-Series Sensing Signals in Factorized Orthogonal Latent Space. CoRR (2023)
Antonious M. Girgis, Suhas N. Diggavi
Multi-Message Shuffled Privacy in Federated Learning. CoRR (2023)
Navjot Singh, Deepesh Data, Jemin George, Suhas N. Diggavi
SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized Optimization. IEEE Trans. Autom. Control. 68 (2) (2023)
Sundara Rajan Srinivasavaradhan, Pavlos Nikolopoulos, Christina Fragouli, Suhas N. Diggavi
Dynamic group testing to control and monitor disease progression in a population. ISIT (2022)
Sundara Rajan Srinivasavaradhan, Pavlos Nikolopoulos, Christina Fragouli, Suhas N. Diggavi
Improving Group Testing via Gradient Descent. ISIT (2022)
Kaan Ozkara, Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi
A Generative Framework for Personalized Learning and Estimation: Theory, Algorithms, and Privacy. CoRR (2022)
Joyson Sebastian, Suhas N. Diggavi
On the Generalized Degrees of Freedom of the Noncoherent Interference Channel. IEEE Trans. Wirel. Commun. 21 (9) (2022)
Yanwen Mao, Deepesh Data, Suhas N. Diggavi, Paulo Tabuada
Decentralized Learning Robust to Data Poisoning Attacks. CDC (2022)
Mohamad Rida Rammal, Alessandro Achille, Aditya Golatkar, Suhas N. Diggavi, Stefano Soatto
On Leave-One-Out Conditional Mutual Information For Generalization. CoRR (2022)
Osama A. Hanna, Antonious M. Girgis, Christina Fragouli, Suhas N. Diggavi
Differentially Private Stochastic Linear Bandits: (Almost) for Free. CoRR (2022)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi
Distributed User-Level Private Mean Estimation. ISIT (2022)
Sundara Rajan Srinivasavaradhan, Pavlos Nikolopoulos, Christina Fragouli, Suhas N. Diggavi
Improving Group Testing via Gradient Descent. CoRR (2022)
Mohamad Rida Rammal, Suhas N. Diggavi, Ashutosh Sabharwal
3D Orientation Estimation With Configurable Backscatter Arrays. ISIT (2022)
Mohamad Rida Rammal, Alessandro Achille, Aditya Golatkar, Suhas N. Diggavi, Stefano Soatto
On Leave-One-Out Conditional Mutual Information For Generalization. NeurIPS (2022)
Osama A. Hanna, Xinlin Li, Christina Fragouli, Suhas N. Diggavi
Can we break the dependency in distributed detection? ISIT (2022)
Deepesh Data, Suhas N. Diggavi
Byzantine-Resilient SGD in High Dimensions on Heterogeneous Data. ISIT (2021)
Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horvath, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu
A Field Guide to Federated Optimization. CoRR (2021)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi
Differentially Private Federated Learning with Shuffling and Client Self-Sampling. ISIT (2021)
Deepesh Data, Linqi Song, Suhas N. Diggavi
Data Encoding for Byzantine-Resilient Distributed Optimization. IEEE Trans. Inf. Theory 67 (2) (2021)
Navjot Singh, Xuanyu Cao, Suhas N. Diggavi, Tamer Basar
Decentralized Multi-Task Stochastic Optimization With Compressed Communications. CoRR (2021)
Osama A. Hanna, Yahya H. Ezzeldin, Christina Fragouli, Suhas N. Diggavi
Quantization of Distributed Data for Learning. IEEE J. Sel. Areas Inf. Theory 2 (3) (2021)
Kaan Ozkara, Navjot Singh, Deepesh Data, Suhas N. Diggavi
QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning. NeurIPS (2021)
Kaan Ozkara, Navjot Singh, Deepesh Data, Suhas N. Diggavi
QuPeL: Quantized Personalization with Applications to Federated Learning. CoRR (2021)
Pavlos Nikolopoulos, Sundara Rajan Srinivasavaradhan, Tao Guo, Christina Fragouli, Suhas N. Diggavi
Group testing for overlapping communities. ICC (2021)
Sundara Rajan Srinivasavaradhan, Pavlos Nikolopoulos, Christina Fragouli, Suhas N. Diggavi
An entropy reduction approach to continual testing. ISIT (2021)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Ananda Theertha Suresh, Peter Kairouz
On the Renyi Differential Privacy of the Shuffle Model. CoRR (2021)
Navjot Singh, Deepesh Data, Jemin George, Suhas N. Diggavi
SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized Optimization. ISIT (2021)
Pavlos Nikolopoulos, Sundara Rajan Srinivasavaradhan, Tao Guo, Christina Fragouli, Suhas N. Diggavi
Group testing for connected communities. AISTATS (2021)
Sundara Rajan Srinivasavaradhan, Michelle Du, Suhas N. Diggavi, Christina Fragouli
Algorithms for Reconstruction Over Single and Multiple Deletion Channels. IEEE Trans. Inf. Theory 67 (6) (2021)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi
Renyi Differential Privacy of The Subsampled Shuffle Model In Distributed Learning. NeurIPS (2021)
Kaan Ozkara, Navjot Singh, Deepesh Data, Suhas N. Diggavi
QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning. CoRR (2021)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh
Shuffled Model of Federated Learning: Privacy, Accuracy and Communication Trade-Offs. IEEE J. Sel. Areas Inf. Theory 2 (1) (2021)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh
Shuffled Model of Differential Privacy in Federated Learning. AISTATS (2021)
Dhaivat Joshi, Shunfu Mao, Sreeram Kannan, Suhas N. Diggavi
QAlign: aligning nanopore reads accurately using current-level modeling. Bioinform. 37 (5) (2021)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Ananda Theertha Suresh, Peter Kairouz
On the Rényi Differential Privacy of the Shuffle Model. CCS (2021)
Yanwen Mao, Suhas N. Diggavi, Christina Fragouli, Paulo Tabuada
Secure State-Reconstruction Over Networks Subject to Attacks. IEEE Control. Syst. Lett. 5 (1) (2021)
Navjot Singh, Deepesh Data, Jemin George, Suhas N. Diggavi
SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized Optimization. IEEE J. Sel. Areas Inf. Theory 2 (3) (2021)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi
Renyi Differential Privacy of the Subsampled Shuffle Model in Distributed Learning. CoRR (2021)
Deepesh Data, Suhas N. Diggavi
Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data. ICML (2021)
Gaurav Kumar Agarwal, Mohammed Karmoose, Suhas N. Diggavi, Christina Fragouli, Paulo Tabuada
Distortion-Based Lightweight Security for Cyber-Physical Systems. IEEE Trans. Autom. Control. 66 (4) (2021)
Mehrdad Showkatbakhsh, Yasser Shoukry, Suhas N. Diggavi, Paulo Tabuada
Securing state reconstruction under sensor and actuator attacks: Theory and design. Autom. 116 (2020)
Deepesh Data, Suhas N. Diggavi
On Byzantine-Resilient High-Dimensional Stochastic Gradient Descent. ISIT (2020)
Joyson Sebastian, Suhas N. Diggavi
Generalized Degrees Freedom of Noncoherent MIMO Channels With Asymmetric Link Strengths. IEEE Trans. Inf. Theory 66 (7) (2020)
Wei-Che Wang, Yair Yona, Yizhang Wu, Suhas N. Diggavi, Puneet Gupta
SLATE: A Secure Lightweight Entity Authentication Hardware Primitive. IEEE Trans. Inf. Forensics Secur. 15 (2020)
Deepesh Data, Suhas N. Diggavi
Byzantine-Resilient SGD in High Dimensions on Heterogeneous Data. CoRR (2020)
Pavlos Nikolopoulos, Sundara Rajan Srinivasavaradhan, Tao Guo, Christina Fragouli, Suhas N. Diggavi
Group testing for overlapping communities. CoRR (2020)
Sundara Rajan Srinivasavaradhan, Michelle Du, Suhas N. Diggavi, Christina Fragouli
Algorithms for reconstruction over single and multiple deletion channels. CoRR (2020)
Antonious M. Girgis, Deepesh Data, Kamalika Chaudhuri, Christina Fragouli, Suhas N. Diggavi
Successive Refinement of Privacy. CoRR (2020)
Antonious M. Girgis, Deepesh Data, Kamalika Chaudhuri, Christina Fragouli, Suhas N. Diggavi
Successive Refinement of Privacy. IEEE J. Sel. Areas Inf. Theory 1 (3) (2020)
Navjot Singh, Deepesh Data, Jemin George, Suhas N. Diggavi
SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized Optimization. CoRR (2020)
Osama A. Hanna, Yahya H. Ezzeldin, Christina Fragouli, Suhas N. Diggavi
Quantizing data for distributed learning. CoRR (2020)
Kenneth Chang, Nathaniel Raymondi, Ashutosh Sabharwal, Suhas N. Diggavi
"Wireless Paint": Code Design for 3D Orientation Estimation with Backscatter Arrays. ISIT (2020)
Deepesh Data, Suhas N. Diggavi
Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data. CoRR (2020)
Joyson Sebastian, Suhas N. Diggavi
Generalized Degrees of Freedom of Noncoherent Diamond Networks. IEEE Trans. Inf. Theory 66 (8) (2020)
Debraj Basu, Deepesh Data, Can Karakus, Suhas N. Diggavi
Qsparse-Local-SGD: Distributed SGD With Quantization, Sparsification, and Local Computations. IEEE J. Sel. Areas Inf. Theory 1 (1) (2020)
Osama A. Hanna, Yahya H. Ezzeldin, Tara Sadjadpour, Christina Fragouli, Suhas N. Diggavi
On Distributed Quantization for Classification. IEEE J. Sel. Areas Inf. Theory 1 (1) (2020)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi
Hiding Identities: Estimation Under Local Differential Privacy. ISIT (2020)
Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh
Shuffled Model of Federated Learning: Privacy, Communication and Accuracy Trade-offs. CoRR (2020)
Sundara Rajan Srinivasavaradhan, Suhas N. Diggavi, Christina Fragouli
Equivalence of ML decoding to a continuous optimization problem. ISIT (2020)
Jad Hachem, Nikhil Karamchandani, Suhas N. Diggavi, Sharayu Moharir
Coded Caching for Heterogeneous Wireless Networks. CoRR (2020)
Navjot Singh, Deepesh Data, Jemin George, Suhas N. Diggavi
SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized Optimization. CDC (2020)
Gaurav Kumar Agarwal, Mohammed Karmoose, Suhas N. Diggavi, Christina Fragouli, Paulo Tabuada
Distortion based Light-weight Security for Cyber-Physical Systems. CoRR (2020)
Pavlos Nikolopoulos, Tao Guo, Christina Fragouli, Suhas N. Diggavi
Community aware group testing. CoRR (2020)
Deepesh Data, Suhas N. Diggavi
Byzantine-Tolerant Distributed Coordinate Descent. ISIT (2019)
Yahya H. Ezzeldin, Christina Fragouli, Suhas N. Diggavi
Quantizing Signals for Linear Classification. ISIT (2019)
Debraj Basu, Deepesh Data, Can Karakus, Suhas N. Diggavi
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification, and Local Computations. CoRR (2019)
Osama A. Hanna, Yahya H. Ezzeldin, Tara Sadjadpour, Christina Fragouli, Suhas N. Diggavi
On Distributed Quantization for Classification. CoRR (2019)
Deepesh Data, Linqi Song, Suhas N. Diggavi
Data Encoding for Byzantine-Resilient Distributed Optimization. CoRR (2019)
Navjot Singh, Deepesh Data, Jemin George, Suhas N. Diggavi
SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized Stochastic Optimization. CoRR (2019)
Abhin Shah, Nikhil Karamchandani, Suhas N. Diggavi
Coded Caching: Global vs Local Content Popularity. CWIT (2019)
Deepesh Data, Linqi Song, Suhas N. Diggavi
Data Encoding Methods for Byzantine-Resilient Distributed Optimization. ISIT (2019)
Mohammed Karmoose, Christina Fragouli, Suhas N. Diggavi, Rafael Misoczki, Lily L. Yang, Zhenliang Zhang
Using mm-Waves for Secret Key Establishment. IEEE Commun. Lett. 23 (6) (2019)
Mehrdad Showkatbakhsh, Can Karakus, Suhas N. Diggavi
Privacy-Utility Trade-off of Linear Regression under Random Projections and Additive Noise. CoRR (2019)
Can Karakus, Yifan Sun, Suhas N. Diggavi, Wotao Yin
Redundancy Techniques for Straggler Mitigation in Distributed Optimization and Learning. J. Mach. Learn. Res. 20 (2019)
Sundara Rajan Srinivasavaradhan, Michelle Du, Suhas N. Diggavi, Christina Fragouli
Symbolwise MAP for Multiple Deletion Channels. ISIT (2019)
Mehrdad Showkatbakhsh, Can Karakus, Suhas N. Diggavi
Differentially Private Consensus-Based Distributed Optimization. CoRR (2019)
Debraj Basu, Deepesh Data, Can Karakus, Suhas N. Diggavi
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification and Local Computations. NeurIPS (2019)
Mehrdad Showkatbakhsh, Yasser Shoukry, Suhas N. Diggavi, Paulo Tabuada
Securing State Estimation Under Sensor and Actuator Attacks: Theory and Design. CoRR (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Suhas N. Diggavi