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ORCIDSuhas N. Diggavi
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- affiliation: University of California, Los Angeles, USA
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2020 – today
- 2024
[j101]Navjot Singh, Xuanyu Cao, Suhas N. Diggavi, Tamer Basar:
Decentralized multi-task stochastic optimization with compressed communications. Autom. 159: 111363 (2024)- [j100]Antonious M. Girgis
, Suhas N. Diggavi:
Multi-Message Shuffled Privacy in Federated Learning. IEEE J. Sel. Areas Inf. Theory 5: 12-27 (2024) - [j99]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: 135-147 (2024) - [j98]Sundara Rajan Srinivasavaradhan, Pavlos Nikolopoulos, Christina Fragouli, Suhas N. Diggavi:
Improving Group Testing via Gradient Descent. IEEE J. Sel. Areas Inf. Theory 5: 236-245 (2024) - [i107]Kaan Ozkara, Bruce Huang, Ruida Zhou, Suhas N. Diggavi:
Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning. CoRR abs/2402.12537 (2024) - [i106]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 abs/2404.02461 (2024) - 2023
- [j97]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) - [j96]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): 845-850 (2023) - [j95]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): 851-873 (2023) - [j94]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): 721-736 (2023) - [j93]Pavlos Nikolopoulos, Sundara Rajan Srinivasavaradhan, Tao Guo, Christina Fragouli, Suhas N. Diggavi:
Community-Aware Group Testing. IEEE Trans. Inf. Theory 69(7): 4361-4383 (2023) - [j92]Deepesh Data, Suhas N. Diggavi:
Byzantine-Resilient High-Dimensional Federated Learning. IEEE Trans. Inf. Theory 69(10): 6639-6670 (2023) - [j91]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): 5844-5854 (2023) - [c181]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 - [c180]Kaan Ozkara, Bruce Huang, Suhas N. Diggavi:
Personalized PCA for Federated Heterogeneous Data. ISIT 2023: 168-173 - [c179]Osama A. Hanna, Xinlin Li, Suhas N. Diggavi, Christina Fragouli:
Common Information Dimension. ISIT 2023: 406-411 - [c178]Navjot Singh, Suhas N. Diggavi:
Representation Transfer Learning via Multiple Pre-trained models for Linear Regression. ISIT 2023: 561-566 - [c177]Xinlin Li, Osama A. Hanna, Christina Fragouli, Suhas N. Diggavi, Gunjan Verma, Joydeep Bhattacharyya:
Feature Compression for Multimodal Multi-Object Tracking. MILCOM 2023: 139-143 - [c176]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: 144-149 - [c175]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 - [i105]Dhaivat Joshi, Suhas N. Diggavi, Mark J. P. Chaisson, Sreeram Kannan:
HQAlign: Aligning nanopore reads for SV detection using current-level modeling. CoRR abs/2301.03834 (2023) - [i104]Antonious M. Girgis, Suhas N. Diggavi:
Multi-Message Shuffled Privacy in Federated Learning. CoRR abs/2302.11152 (2023) - [i103]Osama A. Hanna, Xinlin Li, Suhas N. Diggavi, Christina Fragouli:
Common Information Dimension. CoRR abs/2305.06469 (2023) - [i102]Navjot Singh, Suhas N. Diggavi:
Representation Transfer Learning via Multiple Pre-trained models for Linear Regression. CoRR abs/2305.16440 (2023) - [i101]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 abs/2310.20071 (2023) - 2022
- [j90]Joyson Sebastian, Suhas N. Diggavi:
On the Generalized Degrees of Freedom of the Noncoherent Interference Channel. IEEE Trans. Wirel. Commun. 21(9): 7011-7025 (2022) - [c174]Yanwen Mao, Deepesh Data, Suhas N. Diggavi, Paulo Tabuada:
Decentralized Learning Robust to Data Poisoning Attacks. CDC 2022: 6788-6793 - [c173]Mohamad Rida Rammal, Suhas N. Diggavi, Ashutosh Sabharwal:
3D Orientation Estimation With Configurable Backscatter Arrays. ISIT 2022: 1832-1837 - [c172]Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi:
Distributed User-Level Private Mean Estimation. ISIT 2022: 2196-2201 - [c171]Sundara Rajan Srinivasavaradhan, Pavlos Nikolopoulos, Christina Fragouli, Suhas N. Diggavi:
Improving Group Testing via Gradient Descent. ISIT 2022: 2243-2248 - [c170]Sundara Rajan Srinivasavaradhan, Pavlos Nikolopoulos, Christina Fragouli, Suhas N. Diggavi:
Dynamic group testing to control and monitor disease progression in a population. ISIT 2022: 2255-2260 - [c169]Osama A. Hanna, Xinlin Li, Christina Fragouli, Suhas N. Diggavi:
Can we break the dependency in distributed detection? ISIT 2022: 2720-2725 - [c168]Mohamad Rida Rammal, Alessandro Achille, Aditya Golatkar, Suhas N. Diggavi, Stefano Soatto:
On Leave-One-Out Conditional Mutual Information For Generalization. NeurIPS 2022 - [i100]Sundara Rajan Srinivasavaradhan, Pavlos Nikolopoulos, Christina Fragouli, Suhas N. Diggavi:
Improving Group Testing via Gradient Descent. CoRR abs/2201.12325 (2022) - [i99]Mohamad Rida Rammal, Alessandro Achille, Aditya Golatkar, Suhas N. Diggavi, Stefano Soatto:
On Leave-One-Out Conditional Mutual Information For Generalization. CoRR abs/2207.00581 (2022) - [i98]Kaan Ozkara, Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi:
A Generative Framework for Personalized Learning and Estimation: Theory, Algorithms, and Privacy. CoRR abs/2207.01771 (2022) - [i97]Osama A. Hanna, Antonious M. Girgis, Christina Fragouli, Suhas N. Diggavi:
Differentially Private Stochastic Linear Bandits: (Almost) for Free. CoRR abs/2207.03445 (2022) - 2021
- [j89]Dhaivat Joshi, Shunfu Mao, Sreeram Kannan, Suhas N. Diggavi:
QAlign: aligning nanopore reads accurately using current-level modeling. Bioinform. 37(5): 625-633 (2021) - [j88]Yanwen Mao, Suhas N. Diggavi, Christina Fragouli, Paulo Tabuada:
Secure State-Reconstruction Over Networks Subject to Attacks. IEEE Control. Syst. Lett. 5(1): 157-162 (2021) - [j87]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): 464-478 (2021) - [j86]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): 954-969 (2021) - [j85]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): 987-1001 (2021) - [j84]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): 1588-1601 (2021) - [j83]Deepesh Data, Linqi Song, Suhas N. Diggavi:
Data Encoding for Byzantine-Resilient Distributed Optimization. IEEE Trans. Inf. Theory 67(2): 1117-1140 (2021) - [j82]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): 3389-3410 (2021) - [c167]Pavlos Nikolopoulos, Sundara Rajan Srinivasavaradhan, Tao Guo, Christina Fragouli, Suhas N. Diggavi:
Group testing for connected communities. AISTATS 2021: 2341-2349 - [c166]Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Peter Kairouz, Ananda Theertha Suresh:
Shuffled Model of Differential Privacy in Federated Learning. AISTATS 2021: 2521-2529 - [c165]Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Ananda Theertha Suresh, Peter Kairouz:
On the Rényi Differential Privacy of the Shuffle Model. CCS 2021: 2321-2341 - [c164]Pavlos Nikolopoulos, Sundara Rajan Srinivasavaradhan, Tao Guo, Christina Fragouli, Suhas N. Diggavi:
Group testing for overlapping communities. ICC 2021: 1-7 - [c163]Deepesh Data, Suhas N. Diggavi:
Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data. ICML 2021: 2478-2488 - [c162]Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi:
Differentially Private Federated Learning with Shuffling and Client Self-Sampling. ISIT 2021: 338-343 - [c161]Sundara Rajan Srinivasavaradhan, Pavlos Nikolopoulos, Christina Fragouli, Suhas N. Diggavi:
An entropy reduction approach to continual testing. ISIT 2021: 611-616 - [c160]Navjot Singh, Deepesh Data, Jemin George, Suhas N. Diggavi:
SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized Optimization. ISIT 2021: 1212-1217 - [c159]Deepesh Data, Suhas N. Diggavi:
Byzantine-Resilient SGD in High Dimensions on Heterogeneous Data. ISIT 2021: 2310-2315 - [c158]Kaan Ozkara, Navjot Singh, Deepesh Data, Suhas N. Diggavi:
QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning. NeurIPS 2021: 3622-3634 - [c157]Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi:
Renyi Differential Privacy of The Subsampled Shuffle Model In Distributed Learning. NeurIPS 2021: 29181-29192 - [i96]Kaan Ozkara, Navjot Singh, Deepesh Data, Suhas N. Diggavi:
QuPeL: Quantized Personalization with Applications to Federated Learning. CoRR abs/2102.11786 (2021) - [i95]Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi, Ananda Theertha Suresh, Peter Kairouz:
On the Renyi Differential Privacy of the Shuffle Model. CoRR abs/2105.05180 (2021) - [i94]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 Horváth, 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 abs/2107.06917 (2021) - [i93]Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi:
Renyi Differential Privacy of the Subsampled Shuffle Model in Distributed Learning. CoRR abs/2107.08763 (2021) - [i92]Kaan Ozkara, Navjot Singh, Deepesh Data, Suhas N. Diggavi:
QuPeD: Quantized Personalization via Distillation with Applications to Federated Learning. CoRR abs/2107.13892 (2021) - [i91]Navjot Singh, Xuanyu Cao, Suhas N. Diggavi, Tamer Basar:
Decentralized Multi-Task Stochastic Optimization With Compressed Communications. CoRR abs/2112.12373 (2021) - 2020
- [j81]Mehrdad Showkatbakhsh, Yasser Shoukry, Suhas N. Diggavi, Paulo Tabuada:
Securing state reconstruction under sensor and actuator attacks: Theory and design. Autom. 116: 108920 (2020) - [j80]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): 217-226 (2020) - [j79]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): 237-249 (2020) - [j78]Antonious M. Girgis, Deepesh Data, Kamalika Chaudhuri, Christina Fragouli, Suhas N. Diggavi:
Successive Refinement of Privacy. IEEE J. Sel. Areas Inf. Theory 1(3): 745-759 (2020) - [j77]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: 276-285 (2020) - [j76]Joyson Sebastian, Suhas N. Diggavi:
Generalized Degrees Freedom of Noncoherent MIMO Channels With Asymmetric Link Strengths. IEEE Trans. Inf. Theory 66(7): 4431-4448 (2020) - [j75]Joyson Sebastian, Suhas N. Diggavi:
Generalized Degrees of Freedom of Noncoherent Diamond Networks. IEEE Trans. Inf. Theory 66(8): 5228-5260 (2020) - [c156]Navjot Singh, Deepesh Data, Jemin George, Suhas N. Diggavi:
SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized Optimization. CDC 2020: 3449-3456 - [c155]Sundara Rajan Srinivasavaradhan, Suhas N. Diggavi, Christina Fragouli:
Equivalence of ML decoding to a continuous optimization problem. ISIT 2020: 343-348 - [c154]Antonious M. Girgis, Deepesh Data, Suhas N. Diggavi:
Hiding Identities: Estimation Under Local Differential Privacy. ISIT 2020: 914-919 - [c153]Kenneth Chang, Nathaniel Raymondi, Ashutosh Sabharwal, Suhas N. Diggavi:
"Wireless Paint": Code Design for 3D Orientation Estimation with Backscatter Arrays. ISIT 2020: 1224-1229 - [c152]Deepesh Data, Suhas N. Diggavi:
On Byzantine-Resilient High-Dimensional Stochastic Gradient Descent. ISIT 2020: 2628-2633 - [i90]Navjot Singh, Deepesh Data, Jemin George, Suhas N. Diggavi:
SQuARM-SGD: Communication-Efficient Momentum SGD for Decentralized Optimization. CoRR abs/2005.07041 (2020) - [i89]Deepesh Data, Suhas N. Diggavi:
Byzantine-Resilient SGD in High Dimensions on Heterogeneous Data. CoRR abs/2005.07866 (2020) - [i88]Antonious M. Girgis, Deepesh Data, Kamalika Chaudhuri, Christina Fragouli, Suhas N. Diggavi:
Successive Refinement of Privacy. CoRR abs/2005.11651 (2020) - [i87]Sundara Rajan Srinivasavaradhan, Michelle Du, Suhas N. Diggavi, Christina Fragouli:
Algorithms for reconstruction over single and multiple deletion channels. CoRR abs/2005.14388 (2020) - [i86]Jad Hachem, Nikhil Karamchandani, Suhas N. Diggavi, Sharayu Moharir:
Coded Caching for Heterogeneous Wireless Networks. CoRR abs/2006.01025 (2020) - [i85]Deepesh Data, Suhas N. Diggavi:
Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data. CoRR abs/2006.13041 (2020) - [i84]Gaurav Kumar Agarwal, Mohammed Karmoose, Suhas N. Diggavi, Christina Fragouli, Paulo Tabuada:
Distortion based Light-weight Security for Cyber-Physical Systems. CoRR abs/2006.15998 (2020) - [i83]Pavlos Nikolopoulos, Tao Guo, Christina Fragouli, Suhas N. Diggavi:
Community aware group testing. CoRR abs/2007.08111 (2020) - [i82]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 abs/2008.07180 (2020) - [i81]Pavlos Nikolopoulos, Sundara Rajan Srinivasavaradhan, Tao Guo, Christina Fragouli, Suhas N. Diggavi:
Group testing for overlapping communities. CoRR abs/2012.02804 (2020) - [i80]Osama A. Hanna, Yahya H. Ezzeldin, Christina Fragouli, Suhas N. Diggavi:
Quantizing data for distributed learning. CoRR abs/2012.07913 (2020)
2010 – 2019
- 2019
- [j74]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): 1077-1080 (2019) - [j73]Can Karakus, Yifan Sun, Suhas N. Diggavi, Wotao Yin:
Redundancy Techniques for Straggler Mitigation in Distributed Optimization and Learning. J. Mach. Learn. Res. 20: 72:1-72:47 (2019) - [c151]Abhin Shah, Nikhil Karamchandani, Suhas N. Diggavi:
Coded Caching: Global vs Local Content Popularity. CWIT 2019: 1-6 - [c150]Sundara Rajan Srinivasavaradhan, Michelle Du, Suhas N. Diggavi, Christina Fragouli:
Symbolwise MAP for Multiple Deletion Channels. ISIT 2019: 181-185 - [c149]Yahya H. Ezzeldin, Christina Fragouli, Suhas N. Diggavi:
Quantizing Signals for Linear Classification. ISIT 2019: 912-916 - [c148]Deepesh Data, Linqi Song, Suhas N. Diggavi:
Data Encoding Methods for Byzantine-Resilient Distributed Optimization. ISIT 2019: 2719-2723 - [c147]Deepesh Data, Suhas N. Diggavi:
Byzantine-Tolerant Distributed Coordinate Descent. ISIT 2019: 2724-2728 - [c146]Debraj Basu, Deepesh Data, Can Karakus, Suhas N. Diggavi:
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification and Local Computations. NeurIPS 2019: 14668-14679 - [i79]Mehrdad Showkatbakhsh, Can Karakus, Suhas N. Diggavi:
Privacy-Utility Trade-off of Linear Regression under Random Projections and Additive Noise. CoRR abs/1902.04688 (2019) - [i78]Mehrdad Showkatbakhsh, Can Karakus, Suhas N. Diggavi:
Differentially Private Consensus-Based Distributed Optimization. CoRR abs/1903.07792 (2019) - [i77]Mehrdad Showkatbakhsh, Yasser Shoukry, Suhas N. Diggavi, Paulo Tabuada:
Securing State Estimation Under Sensor and Actuator Attacks: Theory and Design. CoRR abs/1904.01869 (2019) - [i76]Debraj Basu, Deepesh Data, Can Karakus, Suhas N. Diggavi:
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification, and Local Computations. CoRR abs/1906.02367 (2019) - [i75]Deepesh Data, Linqi Song, Suhas N. Diggavi:
Data Encoding for Byzantine-Resilient Distributed Optimization. CoRR abs/1907.02664 (2019) - [i74]Navjot Singh, Deepesh Data, Jemin George, Suhas N. Diggavi:
SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized Stochastic Optimization. CoRR abs/1910.14280 (2019) - [i73]Osama A. Hanna, Yahya H. Ezzeldin, Tara Sadjadpour, Christina Fragouli, Suhas N. Diggavi:
On Distributed Quantization for Classification. CoRR abs/1911.00216 (2019) - 2018
- [j72]Tarek F. Abdelzaher, Nora Ayanian, Tamer Basar, Suhas N. Diggavi, Jana Diesner, Deepak Ganesan, Ramesh Govindan, Susmit Jha, Tancrède Lepoint, Benjamin M. Marlin, Klara Nahrstedt, David M. Nicol, Raj Rajkumar, Stephen Russell, Sanjit A. Seshia, Fei Sha, Prashant J. Shenoy, Mani B. Srivastava, Gaurav S. Sukhatme, Ananthram Swami, Paulo Tabuada, Don Towsley, Nitin H. Vaidya, Venugopal V. Veeravalli:
Toward an Internet of Battlefield Things: A Resilience Perspective. Computer 51(11): 24-36 (2018) - [j71]Jad Hachem, Urs Niesen, Suhas N. Diggavi:
Energy-Efficiency Gains of Caching for Interference Channels. IEEE Commun. Lett. 22(7): 1434-1437 (2018) - [j70]Jad Hachem, Nikhil Karamchandani, Sharayu Moharir, Suhas N. Diggavi:
Caching With Partial Adaptive Matching. IEEE J. Sel. Areas Commun. 36(8): 1831-1842 (2018) - [j69]Joyson Sebastian, Can Karakus, Suhas N. Diggavi:
Approximate Capacity of Fast Fading Interference Channels With no Instantaneous CSIT. IEEE Trans. Commun. 66(12): 6015-6027 (2018) - [j68]Wei-Che Wang, Yair Yona, Suhas N. Diggavi, Puneet Gupta:
Design and Analysis of Stability-Guaranteed PUFs. IEEE Trans. Inf. Forensics Secur. 13(4): 978-992 (2018) - [j67]Wei Mao, Suhas N. Diggavi, Sreeram Kannan:
Models and Information-Theoretic Bounds for Nanopore Sequencing. IEEE Trans. Inf. Theory 64(4): 3216-3236 (2018) - [j66]Jad Hachem, Urs Niesen, Suhas N. Diggavi:
Degrees of Freedom of Cache-Aided Wireless Interference Networks. IEEE Trans. Inf. Theory 64(7): 5359-5380 (2018) - [c145]Deepesh Data, Linqi Song, Suhas N. Diggavi:
Data Encoding for Byzantine-Resilient Distributed Gradient Descent. Allerton 2018: 863-870 - [c144]Gaurav Kumar Agarwal, Mohammed Karmoose, Suhas N. Diggavi, Christina Fragouli, Paulo Tabuada:
Distorting an Adversary's View in Cyber-Physical Systems. CDC 2018: 1476-1481 - [c143]Alimzhan Sultangazin, Suhas N. Diggavi, Paulo Tabuada:
Protecting the Privacy of Networked Multi-Agent Systems Controlled over the Cloud. ICCCN 2018: 1-7 - [c142]Yasser Shoukry, Shaunak Mishra, Zutian Luo, Suhas N. Diggavi:
Sybil attack resilient traffic networks: a physics-based trust propagation approach. ICCPS 2018: 43-54 - [c141]Tarek F. Abdelzaher, Nora Ayanian, Tamer Basar, Suhas N. Diggavi, Jana Diesner, Deepak Ganesan, Ramesh Govindan, Susmit Jha, Tancrède Lepoint, Benjamin M. Marlin, Klara Nahrstedt, David M. Nicol, Raj Rajkumar, Stephen Russell, Sanjit A. Seshia, Fei Sha, Prashant J. Shenoy, Mani B. Srivastava, Gaurav S. Sukhatme, Ananthram Swami, Paulo Tabuada, Don Towsley, Nitin H. Vaidya, Venugopal V. Veeravalli:
Will Distributed Computing Revolutionize Peace? The Emergence of Battlefield IoT. ICDCS 2018: 1129-1138 - [c140]Mehrdad Showkatbakhsh, Can Karakus, Suhas N. Diggavi:
Privacy-Utility Trade-off of Linear Regression under Random Projections and Additive Noise. ISIT 2018: 186-190 - [c139]Sundara Rajan Srinivasavaradhan, Michelle Du, Suhas N. Diggavi, Christina Fragouli:
On Maximum Likelihood Reconstruction over Multiple Deletion Channels. ISIT 2018: 436-440 - [i72]