Gauri Joshi

Orcid: 0000-0002-6372-9697

According to our database1, Gauri Joshi authored at least 95 papers between 2012 and 2024.

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Bibliography

2024
FedFisher: Leveraging Fisher Information for One-Shot Federated Learning.
CoRR, 2024

Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices.
CoRR, 2024

Efficient Reinforcement Learning for Routing Jobs in Heterogeneous Queueing Systems.
CoRR, 2024

Heterogeneous Low-Rank Approximation for Federated Fine-tuning of On-Device Foundation Models.
CoRR, 2024

2023
Correlated Combinatorial Bandits for Online Resource Allocation.
SIGMETRICS Perform. Evaluation Rev., April, 2023

Tackling Heterogeneous Traffic in Multi-access Systems via Erasure Coded Servers.
SIGMETRICS Perform. Evaluation Rev., April, 2023

Communication-Efficient and Model-Heterogeneous Personalized Federated Learning via Clustered Knowledge Transfer.
IEEE J. Sel. Top. Signal Process., January, 2023

High-probability Convergence Bounds for Nonlinear Stochastic Gradient Descent Under Heavy-tailed Noise.
CoRR, 2023

Federated Minimax Optimization with Client Heterogeneity.
CoRR, 2023

Correlation Aware Sparsified Mean Estimation Using Random Projection.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond.
Proceedings of the International Conference on Machine Learning, 2023

On the Convergence of Federated Averaging with Cyclic Client Participation.
Proceedings of the International Conference on Machine Learning, 2023

FedExP: Speeding Up Federated Averaging via Extrapolation.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Federated Learning under Distributed Concept Drift.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Matcha: A Matching-Based Link Scheduling Strategy to Speed up Distributed Optimization.
IEEE Trans. Signal Process., 2022

Machine Learning on Volatile Instances: Convergence, Runtime, and Cost Tradeoffs.
IEEE/ACM Trans. Netw., 2022

On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data.
CoRR, 2022

To Federate or Not To Federate: Incentivizing Client Participation in Federated Learning.
CoRR, 2022

FedLite: A Scalable Approach for Federated Learning on Resource-constrained Clients.
CoRR, 2022

Multi-Model Federated Learning with Provable Guarantees.
Proceedings of the Performance Evaluation Methodologies and Tools, 2022

Fedvarp: Tackling the variance due to partial client participation in federated learning.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Matchmaker: Data Drift Mitigation in Machine Learning for Large-Scale Systems.
Proceedings of Machine Learning and Systems 2022, 2022

Rateless Sum-Recovery Codes For Distributed Non-Linear Computations.
Proceedings of the IEEE Information Theory Workshop, 2022

Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Federated Minimax Optimization: Improved Convergence Analyses and Algorithms.
Proceedings of the International Conference on Machine Learning, 2022

Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling.
Proceedings of the International Conference on Machine Learning, 2022

A Dynamic Reweighting Strategy For Fair Federated Learning.
Proceedings of the IEEE International Conference on Acoustics, 2022


Towards Understanding Biased Client Selection in Federated Learning.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Communication-Efficient Distributed Optimization Algorithms.
Proceedings of the Federated Learning, 2022

2021
A Novel Framework for the Analysis and Design of Heterogeneous Federated Learning.
IEEE Trans. Signal Process., 2021

Synergy via Redundancy: Adaptive Replication Strategies and Fundamental Limits.
IEEE/ACM Trans. Netw., 2021

Multi-Armed Bandits With Correlated Arms.
IEEE Trans. Inf. Theory, 2021

Service Rate Region: A New Aspect of Coded Distributed System Design.
IEEE Trans. Inf. Theory, 2021

Best-Arm Identification in Correlated Multi-Armed Bandits.
IEEE J. Sel. Areas Inf. Theory, 2021

Slow and Stale Gradients Can Win the Race.
IEEE J. Sel. Areas Inf. Theory, 2021

Cooperative SGD: A Unified Framework for the Design and Analysis of Local-Update SGD Algorithms.
J. Mach. Learn. Res., 2021

Residential Consumer Understanding of Electricity Bills: The Case of the Indian Consumer.
Int. J. Asian Bus. Inf. Manag., 2021

Advances and Open Problems in Federated Learning.
Found. Trends Mach. Learn., 2021

Personalized Federated Learning for Heterogeneous Clients with Clustered Knowledge Transfer.
CoRR, 2021

A Field Guide to Federated Optimization.
CoRR, 2021

Local Adaptivity in Federated Learning: Convergence and Consistency.
CoRR, 2021

Deep kernels with probabilistic embeddings for small-data learning.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Job Dispatching Policies for Queueing Systems with Unknown Service Rates.
Proceedings of the MobiHoc '21: The Twenty-second International Symposium on Theory, 2021

Rateless Codes for Distributed Non-linear Computations.
Proceedings of the 11th International Symposium on Topics in Coding, 2021

Adaptive Quantization of Model Updates for Communication-Efficient Federated Learning.
Proceedings of the IEEE International Conference on Acoustics, 2021

A Unified Approach to Translate Classical Bandit Algorithms to Structured Bandits.
Proceedings of the IEEE International Conference on Acoustics, 2021

2020
A Unified Approach to Translate Classical Bandit Algorithms to the Structured Bandit Setting.
IEEE J. Sel. Areas Inf. Theory, 2020

Client Selection in Federated Learning: Convergence Analysis and Power-of-Choice Selection Strategies.
CoRR, 2020

Probabilistic Neighbourhood Component Analysis: Sample Efficient Uncertainty Estimation in Deep Learning.
CoRR, 2020

Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Machine Learning on Volatile Instances.
Proceedings of the 39th IEEE Conference on Computer Communications, 2020

Overlap Local-SGD: An Algorithmic Approach to Hide Communication Delays in Distributed SGD.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Correlated Multi-Armed Bandits with A Latent Random Source.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Exploring the Error-Runtime Trade-off in Decentralized Optimization.
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

Bandit-based Communication-Efficient Client Selection Strategies for Federated Learning.
Proceedings of the 54th Asilomar Conference on Signals, Systems, and Computers, 2020

2019
Efficient Straggler Replication in Large-Scale Parallel Computing.
ACM Trans. Model. Perform. Evaluation Comput. Syst., 2019

Rateless Codes for Near-Perfect Load Balancing in Distributed Matrix-Vector Multiplication.
Proc. ACM Meas. Anal. Comput. Syst., 2019

Whose Decision is it Anyways? The Changing Purchasing Patterns of Indian Families.
Int. J. Asian Bus. Inf. Manag., 2019

Advances and Open Problems in Federated Learning.
CoRR, 2019

Deep Probabilistic Kernels for Sample-Efficient Learning.
CoRR, 2019

Accelerating Deep Learning by Focusing on the Biggest Losers.
CoRR, 2019

MATCHA: Speeding Up Decentralized SGD via Matching Decomposition Sampling.
CoRR, 2019

SysML: The New Frontier of Machine Learning Systems.
CoRR, 2019

Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD.
Proceedings of Machine Learning and Systems 2019, 2019

Rateless Codes for Distributed Computations with Sparse Compressed Matrices.
Proceedings of the IEEE International Symposium on Information Theory, 2019

Introduction to ScaDL 2019.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium Workshops, 2019

Fast and Efficient Distributed Matrix-vector Multiplication Using Rateless Fountain Codes.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
Exploiting Correlation in Finite-Armed Structured Bandits.
CoRR, 2018

Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms.
CoRR, 2018

Rateless Codes for Near-Perfect Load Balancing in Distributed Matrix-Vector Multiplication.
CoRR, 2018

Service Rate Region of Content Access from Erasure Coded Storage.
Proceedings of the IEEE Information Theory Workshop, 2018

Active Distribution Learning from Indirect Samples.
Proceedings of the 56th Annual Allerton Conference on Communication, 2018

Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Efficient Redundancy Techniques for Latency Reduction in Cloud Systems.
ACM Trans. Model. Perform. Evaluation Comput. Syst., 2017

Synergy via Redundancy: Boosting Service Capacity with Adaptive Replication.
SIGMETRICS Perform. Evaluation Rev., 2017

Boosting Service Capacity via Adaptive Task Replication.
SIGMETRICS Perform. Evaluation Rev., 2017

On the service capacity region of accessing erasure coded content.
Proceedings of the 55th Annual Allerton Conference on Communication, 2017

2016
Efficient redundancy techniques to reduce delay in Cloud systems.
PhD thesis, 2016

Looking Good and Thinking Green-Can Green Personal Care Products Be Promoted?
Int. J. Asian Bus. Inf. Manag., 2016

2015
Using Straggler Replication to Reduce Latency in Large-scale Parallel Computing.
SIGMETRICS Perform. Evaluation Rev., 2015

Queues with Redundancy: Latency-Cost Analysis.
SIGMETRICS Perform. Evaluation Rev., 2015

Using Straggler Replication to Reduce Latency in Large-scale Parallel Computing (Extended Version).
CoRR, 2015

On Throughput-Smoothness Trade-offs in Streaming Communication.
CoRR, 2015

Playback delay in on-demand streaming communication with feedback.
Proceedings of the IEEE International Symposium on Information Theory, 2015

Efficient replication of queued tasks for latency reduction in cloud systems.
Proceedings of the 53rd Annual Allerton Conference on Communication, 2015

2014
On the Delay-Storage Trade-Off in Content Download from Coded Distributed Storage Systems.
IEEE J. Sel. Areas Commun., 2014

Efficient task replication for fast response times in parallel computation.
Proceedings of the ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, 2014

Throughput-smoothness trade-offs in multicasting of an ordered packet stream.
Proceedings of the International Symposium on Network Coding, 2014

The effect of block-wise feedback on the throughput-delay trade-off in streaming.
Proceedings of the 2014 Proceedings IEEE INFOCOM Workshops, Toronto, ON, Canada, April 27, 2014

2013
Round-robin overlapping generations coding for fast content download.
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

2012
On playback delay in streaming communication.
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012

Coding for fast content download.
Proceedings of the 50th Annual Allerton Conference on Communication, 2012


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