Nirupam Gupta - RankMe

74 papers A* 12A 1B 1C 6Misc 1Journal 44Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Mosaic Learning: A Framework for Decentralized Learning with Model Fragmentation. CoRR Sayan Biswas, Davide Frey, Romaric Gaudel, Nirupam Gupta, Anne-Marie Kermarrec, Dimitri Lerévérend, Rafael Pires, Rishi Sharma, François Taïani, Martijn de Vos
2025	A*	`conf`	Adaptive Gradient Clipping for Robust Federated Learning. ICLR Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Ahmed Jellouli, Geovani Rizk, John Stephan
2025	J	`jnl`	Generalization under Byzantine & Poisoning Attacks: Tight Stability Bounds in Robust Distributed Learning. CoRR Thomas Boudou, Batiste Le Bars, Nirupam Gupta, Aurélien Bellet
2025	J	`jnl`	Reconciling Communication Compression and Byzantine-Robustness in Distributed Learning. CoRR Diksha Gupta, Nirupam Gupta, Chuan Xu, Giovanni Neglia
2025	J	`jnl`	Robust Federated Inference. CoRR Akash Balasaheb Dhasade, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Maxime Jacovella, Anne-Marie Kermarrec, Rafael Pinot
2024	J	`jnl`	Boosting Robustness by Clipping Gradients in Distributed Learning. CoRR Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Ahmed Jellouli, Geovani Rizk, John Stephan
2024	A*	`conf`	Brief Announcement: A Case for Byzantine Machine Learning. PODC Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
2024	J	`jnl`	Byzantine Machine Learning: A Primer. ACM Comput. Surv. Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
2024	A*	`conf`	Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates. ICML Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Geovani Rizk, Sasha Voitovych
2024	A*	`conf`	Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients. NeurIPS Youssef Allouah, Abdellah El Mrini, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
2024	J	`jnl`	Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients. CoRR Youssef Allouah, Abdellah El Mrini, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
2024	—	`ed.`	Networked Systems - 12th International Conference, NETYS 2024, Rabat, Morocco, May 29-31, 2024, Proceedings NETYS Armando Castañeda, Constantin Enea, Nirupam Gupta
2024	J	`jnl`	On the Relevance of Byzantine Robust Optimization Against Data Poisoning. CoRR Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
2024	A*	`conf`	Revisiting Ensembling in One-Shot Federated Learning. NeurIPS Youssef Allouah, Akash Balasaheb Dhasade, Rachid Guerraoui, Nirupam Gupta, Anne-Marie Kermarrec, Rafael Pinot, Rafael Pires, Rishi Sharma
2024	J	`jnl`	Revisiting Ensembling in One-Shot Federated Learning. CoRR Youssef Allouah, Akash Balasaheb Dhasade, Rachid Guerraoui, Nirupam Gupta, Anne-Marie Kermarrec, Rafael Pinot, Rafael Pires, Rishi Sharma
2024	—	`book`	Robust Machine Learning - Distributed Methods for Safe AI Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
2024	J	`jnl`	Tackling Byzantine Clients in Federated Learning. CoRR Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Geovani Rizk, Sasha Voitovych
2023	J	`jnl`	Byzantine Fault-Tolerance in Federated Local SGD Under $2f$-Redundancy. IEEE Trans. Control. Netw. Syst. Nirupam Gupta, Thinh T. Doan, Nitin H. Vaidya
2023	J	`jnl`	Distributed Learning with Curious and Adversarial Machines. CoRR Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
2023	A	`conf`	Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity. AISTATS Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
2023	J	`jnl`	Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity. CoRR Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
2023	Misc	`conf`	Impact of Redundancy on Resilience in Distributed Optimization and Learning. ICDCN Shuo Liu, Nirupam Gupta, Nitin H. Vaidya
2023	A*	`conf`	On the Privacy-Robustness-Utility Trilemma in Distributed Learning. ICML Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
2023	A*	`conf`	Robust Collaborative Learning with Linear Gradient Overhead. ICML Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Lê-Nguyên Hoang, Rafael Pinot, John Stephan
2023	A*	`conf`	Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity. NeurIPS Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Geovani Rizk
2023	J	`jnl`	Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity. CoRR Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Rafaël Pinot, Geovani Rizk
2022	A*	`conf`	Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums. ICML Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
2022	J	`jnl`	Byzantine Machine Learning Made Easy by Resilient Averaging of Momentums. CoRR Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
2022	B	`conf`	Democratizing Machine Learning: Resilient Distributed Learning with Heterogeneous Participants. SRDS Karim Boubouh, Amine Boussetta, Nirupam Gupta, Alexandre Maurer, Rafaël Pinot
2022	J	`jnl`	Impact of Redundancy on Resilience in Distributed Optimization and Learning. CoRR Shuo Liu, Nirupam Gupta, Nitin H. Vaidya
2022	J	`jnl`	Iterative pre-conditioning for expediting the distributed gradient-descent method: The case of linear least-squares problem. Autom. Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
2022	J	`jnl`	Making Byzantine Decentralized Learning Efficient. CoRR Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Lê Nguyên Hoang, Rafael Pinot, John Stephan
2022	J	`jnl`	On Preconditioning of Decentralized Gradient-Descent When Solving a System of Linear Equations. IEEE Trans. Control. Netw. Syst. Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
2022	J	`jnl`	On the Impossible Safety of Large AI Models. CoRR El-Mahdi El-Mhamdi, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Lê-Nguyên Hoang, Rafael Pinot, John Stephan
2021	—	`conf`	Accelerating Distributed SGD for Linear Regression using Iterative Pre-Conditioning. L4DC Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
2021	A*	`conf`	Approximate Byzantine Fault-Tolerance in Distributed Optimization. PODC Shuo Liu, Nirupam Gupta, Nitin H. Vaidya
2021	J	`jnl`	Approximate Byzantine Fault-Tolerance in Distributed Optimization. CoRR Shuo Liu, Nirupam Gupta, Nitin H. Vaidya
2021	J	`jnl`	Asynchronous Distributed Optimization with Redundancy in Cost Functions. CoRR Shuo Liu, Nirupam Gupta, Nitin H. Vaidya
2021	C	`conf`	Byzantine Fault-Tolerance in Decentralized Optimization under 2f-Redundancy. ACC Nirupam Gupta, Thinh T. Doan, Nitin H. Vaidya
2021	J	`jnl`	Byzantine Fault-Tolerance in Federated Local SGD under 2f-Redundancy. CoRR Nirupam Gupta, Thinh T. Doan, Nitin H. Vaidya
2021	J	`jnl`	Byzantine Fault-Tolerance in Peer-to-Peer Distributed Gradient-Descent. CoRR Nirupam Gupta, Nitin H. Vaidya
2021	—	`conf`	Byzantine Fault-Tolerant Distributed Machine Learning with Norm-Based Comparative Gradient Elimination. DSN Workshops Nirupam Gupta, Shuo Liu, Nitin H. Vaidya
2021	J	`jnl`	Combining Differential Privacy and Byzantine Resilience in Distributed SGD. CoRR Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Sébastien Rouault, John Stephan
2021	A*	`conf`	Differential Privacy and Byzantine Resilience in SGD: Do They Add Up? PODC Rachid Guerraoui, Nirupam Gupta, Rafaël Pinot, Sébastien Rouault, John Stephan
2021	J	`jnl`	Differential Privacy and Byzantine Resilience in SGD: Do They Add Up? CoRR Rachid Guerraoui, Nirupam Gupta, Rafaël Pinot, Sébastien Rouault, John Stephan
2021	J	`jnl`	On Accelerating Distributed Convex Optimizations. CoRR Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
2021	J	`jnl`	Preserving Statistical Privacy in Distributed Optimization. IEEE Control. Syst. Lett. Nirupam Gupta, Shripad Gade, Nikhil Chopra, Nitin H. Vaidya
2021	—	`conf`	Redundancy in cost functions for Byzantine fault-tolerant federated learning. ResilientFL Shuo Liu, Nirupam Gupta, Nitin H. Vaidya
2021	C	`conf`	Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: The Case of Distributed Linear Regression Problem. ACC Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
2021	J	`jnl`	Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: The Case of Distributed Linear Regression Problem. CoRR Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
2021	J	`jnl`	Robustness of Iteratively Pre-Conditioned Gradient-Descent Method: The Case of Distributed Linear Regression Problem. IEEE Control. Syst. Lett. Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
2021	J	`jnl`	Utilizing Redundancy in Cost Functions for Resilience in Distributed Optimization and Learning. CoRR Shuo Liu, Nirupam Gupta, Nitin H. Vaidya
2020	J	`jnl`	Accelerating Distributed SGD for Linear Linear Regression using Iterative Pre-Conditioning. CoRR Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
2020	J	`jnl`	Byzantine Fault-Tolerance in Decentralized Optimization under Minimal Redundancy. CoRR Nirupam Gupta, Thinh T. Doan, Nitin H. Vaidya
2020	J	`jnl`	Byzantine Fault-Tolerant Distributed Machine Learning Using Stochastic Gradient Descent (SGD) and Norm-Based Comparative Gradient Elimination (CGE). CoRR Nirupam Gupta, Shuo Liu, Nitin H. Vaidya
2020	J	`jnl`	False Data Injection Attacks in Bilateral Teleoperation Systems. IEEE Trans. Control. Syst. Technol. Yimeng Dong, Nirupam Gupta, Nikhil Chopra
2020	A*	`conf`	Fault-Tolerance in Distributed Optimization: The Case of Redundancy. PODC Nirupam Gupta, Nitin H. Vaidya
2020	J	`jnl`	Iterative Pre-Conditioning for Expediting the Gradient-Descent Method: The Distributed Linear Least-Squares Problem. CoRR Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
2020	C	`conf`	Iterative Pre-Conditioning to Expedite the Gradient-Descent Method. ACC Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
2020	J	`jnl`	Iterative Pre-Conditioning to Expedite the Gradient-Descent Method. CoRR Kushal Chakrabarti, Nirupam Gupta, Nikhil Chopra
2020	J	`jnl`	Preserving Statistical Privacy in Distributed Optimization. CoRR Nirupam Gupta, Shripad Gade, Nikhil Chopra, Nitin H. Vaidya
2020	J	`jnl`	Resilience in Collaborative Optimization: Redundant and Independent Cost Functions. CoRR Nirupam Gupta, Nitin H. Vaidya
2019	J	`jnl`	Byzantine Fault Tolerant Distributed Linear Regression. CoRR Nirupam Gupta, Nitin H. Vaidya
2019	—	`conf`	Byzantine Fault-Tolerant Parallelized Stochastic Gradient Descent for Linear Regression. Allerton Nirupam Gupta, Nitin H. Vaidya
2019	J	`jnl`	Privacy of Agents' Costs in Peer-to-Peer Distributed Optimization. CoRR Nirupam Gupta, Nikhil Chopra
2019	J	`jnl`	Randomized Reactive Redundancy for Byzantine Fault-Tolerance in Parallelized Learning. CoRR Nirupam Gupta, Nitin H. Vaidya
2019	C	`conf`	Statistical Privacy in Distributed Average Consensus on Bounded Real Inputs. ACC Nirupam Gupta, Jonathan Katz, Nikhil Chopra
2019	J	`jnl`	Statistical Privacy in Distributed Average Consensus on Bounded Real Inputs. CoRR Nirupam Gupta, Jonathan Katz, Nikhil Chopra
2018	J	`jnl`	Information-Theoretic Privacy in Distributed Average Consensus. CoRR Nirupam Gupta, Jonathan Katz, Nikhil Chopra
2018	—	`conf`	Model-Based Encryption: Privacy of States in Networked Control Systems. Allerton Nirupam Gupta, Nikhil Chopra
2018	—	`—`	Privacy in Distributed Multi-Agent Collaboration: consensus and Optimization. Nirupam Gupta
2017	C	`conf`	Robustness of distributive double-integrator consensus to loss of graph connectivity. ACC Nirupam Gupta, Yimeng Dong, Nikhil Chopra
2016	—	`conf`	Confidentiality in distributed average information consensus. CDC Nirupam Gupta, Nikhil Chopra
2016	C	`conf`	On content modification attacks in bilateral teleoperation systems. ACC Yimeng Dong, Nirupam Gupta, Nikhil Chopra