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2020 – today
- 2024
[j29]Yae Jee Cho, Divyansh Jhunjhunwala, Tian Li, Virginia Smith, Gauri Joshi:
Maximizing Global Model Appeal in Federated Learning. Trans. Mach. Learn. Res. 2024 (2024)- [j28]Jianyu Wang, Rudrajit Das, Gauri Joshi, Satyen Kale, Zheng Xu, Tong Zhang:
On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data. Trans. Mach. Learn. Res. 2024 (2024) - [c53]Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi:
FedFisher: Leveraging Fisher Information for One-Shot Federated Learning. AISTATS 2024: 1612-1620 - [c52]Neharika Jali, Guannan Qu, Weina Wang, Gauri Joshi:
Efficient Reinforcement Learning for Routing Jobs in Heterogeneous Queueing Systems. AISTATS 2024: 4177-4185 - [c51]Yae Jee Cho, Luyang Liu, Zheng Xu, Aldi Fahrezi, Gauri Joshi:
Heterogeneous LoRA for Federated Fine-tuning of On-Device Foundation Models. EMNLP 2024: 12903-12913 - [c50]Pranay Sharma, Jiarui Li, Gauri Joshi:
On Improved Distributed Random Reshuffling over Networks. ICASSP 2024: 13211-13215 - [c49]Jiin Woo, Laixi Shi, Gauri Joshi, Yuejie Chi:
Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices. ICML 2024 - [c48]Divyansh Jhunjhunwala, Neharika Jali, Gauri Joshi, Shiqiang Wang:
Erasure Coded Neural Network Inference via Fisher Averaging. ISIT 2024: 13-18 - [i67]Yae Jee Cho, Luyang Liu, Zheng Xu, Aldi Fahrezi, Gauri Joshi:
Heterogeneous Low-Rank Approximation for Federated Fine-tuning of On-Device Foundation Models. CoRR abs/2401.06432 (2024) - [i66]Neharika Jali, Guannan Qu, Weina Wang, Gauri Joshi:
Efficient Reinforcement Learning for Routing Jobs in Heterogeneous Queueing Systems. CoRR abs/2402.01147 (2024) - [i65]Jiin Woo, Laixi Shi, Gauri Joshi, Yuejie Chi:
Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices. CoRR abs/2402.05876 (2024) - [i64]Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi:
FedFisher: Leveraging Fisher Information for One-Shot Federated Learning. CoRR abs/2403.12329 (2024) - [i63]Baris Askin, Pranay Sharma, Carlee Joe-Wong, Gauri Joshi:
FedAST: Federated Asynchronous Simultaneous Training. CoRR abs/2406.00302 (2024) - [i62]Divyansh Jhunjhunwala, Neharika Jali, Gauri Joshi, Shiqiang Wang:
Erasure Coded Neural Network Inference via Fisher Averaging. CoRR abs/2409.01420 (2024) - [i61]Zhenyu Sun, Ziyang Zhang, Zheng Xu, Gauri Joshi, Pranay Sharma, Ermin Wei:
Debiasing Federated Learning with Correlated Client Participation. CoRR abs/2410.01209 (2024) - [i60]Aayushya Agarwal, Gauri Joshi, Lawrence T. Pileggi:
FedECADO: A Dynamical System Model of Federated Learning. CoRR abs/2410.09933 (2024) - [i59]Aleksandar Armacki, Shuhua Yu, Pranay Sharma, Gauri Joshi, Dragana Bajovic, Dusan Jakovetic, Soummya Kar:
Nonlinear Stochastic Gradient Descent and Heavy-tailed Noise: A Unified Framework and High-probability Guarantees. CoRR abs/2410.13954 (2024) - [i58]Baris Askin, Pranay Sharma, Gauri Joshi, Carlee Joe-Wong:
Federated Communication-Efficient Multi-Objective Optimization. CoRR abs/2410.16398 (2024) - 2023
- [j27]Yae Jee Cho
, Jianyu Wang, Tarun Chirvolu, Gauri Joshi:
Communication-Efficient and Model-Heterogeneous Personalized Federated Learning via Clustered Knowledge Transfer. IEEE J. Sel. Top. Signal Process. 17(1): 234-247 (2023) - [j26]Samarth Gupta, Jinhang Zuo, Carlee Joe-Wong, Gauri Joshi, Osman Yagan:
Correlated Combinatorial Bandits for Online Resource Allocation. SIGMETRICS Perform. Evaluation Rev. 50(4): 20-22 (2023) - [j25]Tuhinangshu Choudhury, Weina Wang, Gauri Joshi:
Tackling Heterogeneous Traffic in Multi-access Systems via Erasure Coded Servers. SIGMETRICS Perform. Evaluation Rev. 50(4): 59-61 (2023) - [j24]Pranay Sharma, Rohan Panda, Gauri Joshi:
Federated Minimax Optimization with Client Heterogeneity. Trans. Mach. Learn. Res. 2023 (2023) - [c47]Ellango Jothimurugesan, Kevin Hsieh, Jianyu Wang, Gauri Joshi, Phillip B. Gibbons:
Federated Learning under Distributed Concept Drift. AISTATS 2023: 5834-5853 - [c46]Yae Jee Cho, Gauri Joshi, Dimitrios Dimitriadis:
Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels. ICCV 2023: 17041-17050 - [c45]Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi:
FedExP: Speeding Up Federated Averaging via Extrapolation. ICLR 2023 - [c44]Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang:
On the Convergence of Federated Averaging with Cyclic Client Participation. ICML 2023: 5677-5721 - [c43]Jiin Woo, Gauri Joshi, Yuejie Chi:
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond. ICML 2023: 37157-37216 - [c42]Shuli Jiang, Pranay Sharma, Gauri Joshi:
Correlation Aware Sparsified Mean Estimation Using Random Projection. NeurIPS 2023 - [i57]Divyansh Jhunjhunwala, Shiqiang Wang, Gauri Joshi:
FedExP: Speeding up Federated Averaging Via Extrapolation. CoRR abs/2301.09604 (2023) - [i56]Yae Jee Cho, Pranay Sharma, Gauri Joshi, Zheng Xu, Satyen Kale, Tong Zhang:
On the Convergence of Federated Averaging with Cyclic Client Participation. CoRR abs/2302.03109 (2023) - [i55]Pranay Sharma, Rohan Panda, Gauri Joshi:
Federated Minimax Optimization with Client Heterogeneity. CoRR abs/2302.04249 (2023) - [i54]Jiin Woo, Gauri Joshi, Yuejie Chi:
The Blessing of Heterogeneity in Federated Q-learning: Linear Speedup and Beyond. CoRR abs/2305.10697 (2023) - [i53]Yae Jee Cho, Gauri Joshi, Dimitrios Dimitriadis:
Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels. CoRR abs/2307.08809 (2023) - [i52]Aleksandar Armacki, Pranay Sharma, Gauri Joshi, Dragana Bajovic, Dusan Jakovetic, Soummya Kar:
High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise. CoRR abs/2310.18784 (2023) - [i51]Shuli Jiang, Pranay Sharma, Gauri Joshi:
Correlation Aware Sparsified Mean Estimation Using Random Projection. CoRR abs/2310.18868 (2023) - 2022
- [j23]Ankur Mallick, Malhar Chaudhari, Utsav Sheth, Ganesh Palanikumar, Gauri Joshi:
Rateless codes for near-perfect load balancing in distributed matrix-vector multiplication. Commun. ACM 65(5): 111-118 (2022) - [j22]Xiaoxi Zhang, Jianyu Wang, Li-Feng Lee, Tom Yang, Akansha Kalra, Gauri Joshi, Carlee Joe-Wong:
Machine Learning on Volatile Instances: Convergence, Runtime, and Cost Tradeoffs. IEEE/ACM Trans. Netw. 30(1): 215-228 (2022) - [j21]Jianyu Wang, Anit Kumar Sahu, Gauri Joshi, Soummya Kar:
Matcha: A Matching-Based Link Scheduling Strategy to Speed up Distributed Optimization. IEEE Trans. Signal Process. 70: 5208-5221 (2022) - [c41]Yae Jee Cho, Jianyu Wang, Gauri Joshi:
Towards Understanding Biased Client Selection in Federated Learning. AISTATS 2022: 10351-10375 - [c40]Sen Lin, Ming Shi, Anish Arora, Raef Bassily, Elisa Bertino, Constantine Caramanis, Kaushik R. Chowdhury, Eylem Ekici, Atilla Eryilmaz, Stratis Ioannidis, Nan Jiang, Gauri Joshi, Jim Kurose, Yingbin Liang, Zhiqiang Lin, Jia Liu, Mingyan Liu, Tommaso Melodia, Aryan Mokhtari, Rob Nowak, Sewoong Oh, Srini Parthasarathy, Chunyi Peng, Hulya Seferoglu, Ness B. Shroff, Sanjay Shakkottai, Kannan Srinivasan, Ameet Talwalkar, Aylin Yener, Lei Ying:
Leveraging Synergies Between AI and Networking to Build Next Generation Edge Networks. CIC 2022: 16-25 - [c39]Zhiyuan Zhao, Gauri Joshi:
A Dynamic Reweighting Strategy For Fair Federated Learning. ICASSP 2022: 8772-8776 - [c38]Sajad Khodadadian, Pranay Sharma, Gauri Joshi, Siva Theja Maguluri:
Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling. ICML 2022: 10997-11057 - [c37]Pranay Sharma, Rohan Panda, Gauri Joshi, Pramod K. Varshney:
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms. ICML 2022: 19683-19730 - [c36]Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, Dimitrios Dimitriadis:
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning. IJCAI 2022: 2881-2887 - [c35]Ankur Mallick, Gauri Joshi:
Rateless Sum-Recovery Codes For Distributed Non-Linear Computations. ITW 2022: 160-165 - [c34]Ankur Mallick, Kevin Hsieh, Behnaz Arzani, Gauri Joshi:
Matchmaker: Data Drift Mitigation in Machine Learning for Large-Scale Systems. MLSys 2022 - [c33]Samarth Gupta, Jinhang Zuo, Carlee Joe-Wong, Gauri Joshi, Osman Yagan:
Correlated combinatorial bandits for online resource allocation. MobiHoc 2022: 91-100 - [c32]Tuhinangshu Choudhury, Weina Wang, Gauri Joshi:
Tackling heterogeneous traffic in multi-access systems via erasure coded servers. MobiHoc 2022: 171-180 - [c31]Divyansh Jhunjhunwala, Pranay Sharma, Aushim Nagarkatti, Gauri Joshi:
Fedvarp: Tackling the variance due to partial client participation in federated learning. UAI 2022: 906-916 - [c30]Neelkamal Bhuyan, Sharayu Moharir, Gauri Joshi:
Multi-Model Federated Learning with Provable Guarantees. VALUETOOLS 2022: 207-222 - [p1]Gauri Joshi, Shiqiang Wang:
Communication-Efficient Distributed Optimization Algorithms. Federated Learning 2022: 125-143 - [i50]Jianyu Wang, Hang Qi, Ankit Singh Rawat, Sashank J. Reddi, Sagar Waghmare, Felix X. Yu, Gauri Joshi:
FedLite: A Scalable Approach for Federated Learning on Resource-constrained Clients. CoRR abs/2201.11865 (2022) - [i49]Pranay Sharma, Rohan Panda, Gauri Joshi, Pramod K. Varshney:
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms. CoRR abs/2203.04850 (2022) - [i48]Yae Jee Cho, Andre Manoel, Gauri Joshi, Robert Sim, Dimitrios Dimitriadis:
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning. CoRR abs/2204.12703 (2022) - [i47]Yae Jee Cho, Divyansh Jhunjhunwala, Tian Li, Virginia Smith, Gauri Joshi:
To Federate or Not To Federate: Incentivizing Client Participation in Federated Learning. CoRR abs/2205.14840 (2022) - [i46]Ellango Jothimurugesan, Kevin Hsieh, Jianyu Wang, Gauri Joshi, Phillip B. Gibbons:
Federated Learning under Distributed Concept Drift. CoRR abs/2206.00799 (2022) - [i45]Jianyu Wang, Rudrajit Das, Gauri Joshi, Satyen Kale, Zheng Xu, Tong Zhang:
On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data. CoRR abs/2206.04723 (2022) - [i44]Sajad Khodadadian, Pranay Sharma, Gauri Joshi, Siva Theja Maguluri:
Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling. CoRR abs/2206.10185 (2022) - [i43]Tuhinangshu Choudhury, Weina Wang, Gauri Joshi:
Tackling Heterogeneous Traffic in Multi-access Systems via Erasure Coded Servers. CoRR abs/2207.03983 (2022) - [i42]Neelkamal Bhuyan, Sharayu Moharir, Gauri Joshi:
Multi-Model Federated Learning with Provable Guarantees. CoRR abs/2207.04330 (2022) - [i41]Divyansh Jhunjhunwala, Pranay Sharma, Aushim Nagarkatti, Gauri Joshi:
FedVARP: Tackling the Variance Due to Partial Client Participation in Federated Learning. CoRR abs/2207.14130 (2022) - 2021
- [j20]Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao:
Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14(1-2): 1-210 (2021) - [j19]Gauri Joshi, Vasundhara Sen:
Residential Consumer Understanding of Electricity Bills: The Case of the Indian Consumer. Int. J. Asian Bus. Inf. Manag. 12(3): 1-16 (2021) - [j18]Jianyu Wang, Gauri Joshi:
Cooperative SGD: A Unified Framework for the Design and Analysis of Local-Update SGD Algorithms. J. Mach. Learn. Res. 22: 213:1-213:50 (2021) - [j17]Samarth Gupta, Gauri Joshi, Osman Yagan:
Best-Arm Identification in Correlated Multi-Armed Bandits. IEEE J. Sel. Areas Inf. Theory 2(2): 549-563 (2021) - [j16]Sanghamitra Dutta, Jianyu Wang, Gauri Joshi:
Slow and Stale Gradients Can Win the Race. IEEE J. Sel. Areas Inf. Theory 2(3): 1012-1024 (2021) - [j15]Samarth Gupta, Shreyas Chaudhari, Gauri Joshi, Osman Yagan:
Multi-Armed Bandits With Correlated Arms. IEEE Trans. Inf. Theory 67(10): 6711-6732 (2021) - [j14]Mehmet S. Aktas, Gauri Joshi, Swanand Kadhe, Fatemeh Kazemi, Emina Soljanin:
Service Rate Region: A New Aspect of Coded Distributed System Design. IEEE Trans. Inf. Theory 67(12): 7940-7963 (2021) - [j13]Gauri Joshi, Dhruva Kaushal:
Synergy via Redundancy: Adaptive Replication Strategies and Fundamental Limits. IEEE/ACM Trans. Netw. 29(2): 737-749 (2021) - [j12]Jianyu Wang, Qinghua Liu, Hao Liang, Gauri Joshi, H. Vincent Poor:
A Novel Framework for the Analysis and Design of Heterogeneous Federated Learning. IEEE Trans. Signal Process. 69: 5234-5249 (2021) - [c29]Divyansh Jhunjhunwala, Advait Gadhikar, Gauri Joshi, Yonina C. Eldar:
Adaptive Quantization of Model Updates for Communication-Efficient Federated Learning. ICASSP 2021: 3110-3114 - [c28]Samarth Gupta, Shreyas Chaudhari, Subhojyoti Mukherjee, Gauri Joshi, Osman Yagan:
A Unified Approach to Translate Classical Bandit Algorithms to Structured Bandits. ICASSP 2021: 3360-3364 - [c27]Ankur Mallick, Sophie Smith, Gauri Joshi:
Rateless Codes for Distributed Non-linear Computations. ISTC 2021: 1-5 - [c26]Tuhinangshu Choudhury, Gauri Joshi, Weina Wang, Sanjay Shakkottai:
Job Dispatching Policies for Queueing Systems with Unknown Service Rates. MobiHoc 2021: 181-190 - [c25]Divyansh Jhunjhunwala, Ankur Mallick, Advait Gadhikar, Swanand Kadhe, Gauri Joshi:
Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation. NeurIPS 2021: 14280-14292 - [c24]Ankur Mallick, Chaitanya Dwivedi, Bhavya Kailkhura, Gauri Joshi, Thomas Yong-Jin Han:
Deep kernels with probabilistic embeddings for small-data learning. UAI 2021: 918-928 - [i40]Divyansh Jhunjhunwala, Advait Gadhikar, Gauri Joshi, Yonina C. Eldar:
Adaptive Quantization of Model Updates for Communication-Efficient Federated Learning. CoRR abs/2102.04487 (2021) - [i39]Jianyu Wang, Zheng Xu, Zachary Garrett, Zachary Charles, Luyang Liu, Gauri Joshi:
Local Adaptivity in Federated Learning: Convergence and Consistency. CoRR abs/2106.02305 (2021) - [i38]Tuhinangshu Choudhury, Gauri Joshi, Weina Wang, Sanjay Shakkottai:
Job Dispatching Policies for Queueing Systems with Unknown Service Rates. CoRR abs/2106.04707 (2021) - [i37]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) - [i36]Samarth Gupta, Gauri Joshi, Osman Yagan:
Best-Arm Identification in Correlated Multi-Armed Bandits. CoRR abs/2109.04941 (2021) - [i35]Yae Jee Cho, Jianyu Wang, Tarun Chiruvolu, Gauri Joshi:
Personalized Federated Learning for Heterogeneous Clients with Clustered Knowledge Transfer. CoRR abs/2109.08119 (2021) - [i34]Divyansh Jhunjhunwala, Ankur Mallick, Advait Gadhikar, Swanand Kadhe, Gauri Joshi:
Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation. CoRR abs/2110.07751 (2021) - 2020
- [j11]Samarth Gupta, Shreyas Chaudhari, Subhojyoti Mukherjee, Gauri Joshi, Osman Yagan:
A Unified Approach to Translate Classical Bandit Algorithms to the Structured Bandit Setting. IEEE J. Sel. Areas Inf. Theory 1(3): 840-853 (2020) - [c23]Jianyu Wang, Anit Kumar Sahu, Gauri Joshi, Soummya Kar:
Exploring the Error-Runtime Trade-off in Decentralized Optimization. ACSSC 2020: 910-914 - [c22]Yae Jee Cho, Samarth Gupta, Gauri Joshi, Osman Yagan:
Bandit-based Communication-Efficient Client Selection Strategies for Federated Learning. ACSSC 2020: 1066-1069 - [c21]Samarth Gupta, Gauri Joshi, Osman Yagan:
Correlated Multi-Armed Bandits with A Latent Random Source. ICASSP 2020: 3572-3576 - [c20]Jianyu Wang, Hao Liang, Gauri Joshi:
Overlap Local-SGD: An Algorithmic Approach to Hide Communication Delays in Distributed SGD. ICASSP 2020: 8871-8875 - [c19]Xiaoxi Zhang, Jianyu Wang, Gauri Joshi, Carlee Joe-Wong:
Machine Learning on Volatile Instances. INFOCOM 2020: 139-148 - [c18]Jianyu Wang, Qinghua Liu, Hao Liang, Gauri Joshi, H. Vincent Poor:
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization. NeurIPS 2020 - [c17]Ankur Mallick, Malhar Chaudhari, Utsav Sheth, Ganesh Palanikumar, Gauri Joshi:
Rateless Codes for Near-Perfect Load Balancing in Distributed Matrix-Vector Multiplication. SIGMETRICS (Abstracts) 2020: 95-96 - [i33]Jianyu Wang, Hao Liang, Gauri Joshi:
Overlap Local-SGD: An Algorithmic Approach to Hide Communication Delays in Distributed SGD. CoRR abs/2002.09539 (2020) - [i32]Xiaoxi Zhang, Jianyu Wang, Gauri Joshi, Carlee Joe-Wong:
Machine Learning on Volatile Instances. CoRR abs/2003.05649 (2020) - [i31]Sanghamitra Dutta, Jianyu Wang, Gauri Joshi:
Slow and Stale Gradients Can Win the Race. CoRR abs/2003.10579 (2020) - [i30]Jianyu Wang, Qinghua Liu, Hao Liang, Gauri Joshi, H. Vincent Poor:
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization. CoRR abs/2007.07481 (2020) - [i29]Ankur Mallick, Chaitanya Dwivedi, Bhavya Kailkhura, Gauri Joshi, Thomas Yong-Jin Han:
Probabilistic Neighbourhood Component Analysis: Sample Efficient Uncertainty Estimation in Deep Learning. CoRR abs/2007.10800 (2020) - [i28]Mehmet S. Aktas, Gauri Joshi, Swanand Kadhe, Fatemeh Kazemi, Emina Soljanin:
Service Rate Region: A New Aspect of Coded Distributed System Design. CoRR abs/2009.01598 (2020) - [i27]Yae Jee Cho, Jianyu Wang, Gauri Joshi:
Client Selection in Federated Learning: Convergence Analysis and Power-of-Choice Selection Strategies. CoRR abs/2010.01243 (2020) - [i26]Yae Jee Cho, Samarth Gupta, Gauri Joshi, Osman Yagan:
Bandit-based Communication-Efficient Client Selection Strategies for Federated Learning. CoRR abs/2012.08009 (2020) - [i25]Gauri Joshi, Dhruva Kaushal:
Synergy via Redundancy: Adaptive Replication Strategies and Fundamental Limits. CoRR abs/2012.13608 (2020)
2010 – 2019
- 2019
- [j10]Gauri Joshi, Pratima Amol Sheorey:
Whose Decision is it Anyways? The Changing Purchasing Patterns of Indian Families. Int. J. Asian Bus. Inf. Manag. 10(4): 21-30 (2019) - [j9]Ankur Mallick, Malhar Chaudhari, Utsav Sheth, Ganesh Palanikumar, Gauri Joshi:
Rateless Codes for Near-Perfect Load Balancing in Distributed Matrix-Vector Multiplication. Proc. ACM Meas. Anal. Comput. Syst. 3(3): 58:1-58:40 (2019) - [j8]Da Wang, Gauri Joshi, Gregory W. Wornell:
Efficient Straggler Replication in Large-Scale Parallel Computing. ACM Trans. Model. Perform. Evaluation Comput. Syst. 4(2): 7:1-7:23 (2019) - [c16]Ankur Mallick, Malhar Chaudhari, Gauri Joshi:
Fast and Efficient Distributed Matrix-vector Multiplication Using Rateless Fountain Codes. ICASSP 2019: 8192-8196 - [c15]Gauri Joshi, Ashish Verma:
Introduction to ScaDL 2019. IPDPS Workshops 2019: 924 - [c14]Ankur Mallick, Gauri Joshi:
Rateless Codes for Distributed Computations with Sparse Compressed Matrices. ISIT 2019: 2793-2797 - [c13]Jianyu Wang, Gauri Joshi:
Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD. SysML 2019 - [i24]Sarah E. Anderson, Ann Johnston, Gauri Joshi, Gretchen L. Matthews, Carolyn Mayer, Emina Soljanin:
Service Rate Region of Content Access from Erasure Coded Storage. CoRR abs/1901.02399 (2019) - [i23]Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin G. Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Randall Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar:
SysML: The New Frontier of Machine Learning Systems. CoRR abs/1904.03257 (2019) - [i22]Jianyu Wang, Anit Kumar Sahu, Zhouyi Yang, Gauri Joshi, Soummya Kar:
MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling. CoRR abs/1905.09435 (2019) - [i21]Angela H. Jiang, Daniel L.-K. Wong, Giulio Zhou, David G. Andersen, Jeffrey Dean, Gregory R. Ganger, Gauri Joshi, Michael Kaminsky, Michael Kozuch, Zachary C. Lipton, Padmanabhan Pillai:
Accelerating Deep Learning by Focusing on the Biggest Losers. CoRR abs/1910.00762 (2019) - [i20]Ankur Mallick, Chaitanya Dwivedi, Bhavya Kailkhura, Gauri Joshi, Thomas Yong-Jin Han:
Deep Probabilistic Kernels for Sample-Efficient Learning. CoRR abs/1910.05858 (2019) - [i19]