Virginia Smith

According to our database1, Virginia Smith authored at least 43 papers between 2012 and 2021.

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Bibliography

2021
Progressive Compressed Records: Taking a Byte out of Deep Learning Data.
Proc. VLDB Endow., 2021

On Tilted Losses in Machine Learning: Theory and Applications.
CoRR, 2021

Private Multi-Task Learning: Formulation and Applications to Federated Learning.
CoRR, 2021

A Field Guide to Federated Optimization.
CoRR, 2021

On Large-Cohort Training for Federated Learning.
CoRR, 2021

Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing.
CoRR, 2021

Lessons from Chasing Few-Shot Learning Benchmarks: Rethinking the Evaluation of Meta-Learning Methods.
CoRR, 2021

Label Leakage and Protection in Two-party Split Learning.
CoRR, 2021

Heterogeneity for the Win: One-Shot Federated Clustering.
Proceedings of the 38th International Conference on Machine Learning, 2021

Ditto: Fair and Robust Federated Learning Through Personalization.
Proceedings of the 38th International Conference on Machine Learning, 2021

Tilted Empirical Risk Minimization.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Federated Learning: Challenges, Methods, and Future Directions.
IEEE Signal Process. Mag., 2020

Federated Multi-Task Learning for Competing Constraints.
CoRR, 2020

Is Support Set Diversity Necessary for Meta-Learning?
CoRR, 2020

Federated Optimization in Heterogeneous Networks.
Proceedings of Machine Learning and Systems 2020, 2020

Learning Context-Aware Policies from Multiple Smart Homes via Federated Multi-Task Learning.
Proceedings of the Fifth IEEE/ACM International Conference on Internet-of-Things Design and Implementation, 2020

Fair Resource Allocation in Federated Learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Enhancing the Privacy of Federated Learning with Sketching.
CoRR, 2019

Privacy for Free: Communication-Efficient Learning with Differential Privacy Using Sketches.
CoRR, 2019

Fair Resource Allocation in Federated Learning.
CoRR, 2019

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

One-Shot Federated Learning.
CoRR, 2019

A Kernel Theory of Modern Data Augmentation.
Proceedings of the 36th International Conference on Machine Learning, 2019

Efficient Augmentation via Data Subsampling.
Proceedings of the 7th International Conference on Learning Representations, 2019

FedDANE: A Federated Newton-Type Method.
Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, 2019

2018
On the Convergence of Federated Optimization in Heterogeneous Networks.
CoRR, 2018

LEAF: A Benchmark for Federated Settings.
CoRR, 2018

2017
System-Aware Optimization for Machine Learning at Scale.
PhD thesis, 2017

Distributed optimization with arbitrary local solvers.
Optim. Methods Softw., 2017

CoCoA: A General Framework for Communication-Efficient Distributed Optimization.
J. Mach. Learn. Res., 2017

Federated Multi-Task Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
A Static Change Impact Analysis Approach based on Metrics and Visualizations to Support the Evolution of Workflow Repositories.
Int. J. Web Serv. Res., 2016

2015
L1-Regularized Distributed Optimization: A Communication-Efficient Primal-Dual Framework.
CoRR, 2015

Going In-Depth: Finding Longform on the Web.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Adding vs. Averaging in Distributed Primal-Dual Optimization.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Communication-Efficient Distributed Dual Coordinate Ascent.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013
A comparative study of high renewables penetration electricity grids.
Proceedings of the IEEE Fourth International Conference on Smart Grid Communications, 2013

A Change Impact Analysis Approach for Workflow Repository Management.
Proceedings of the 2013 IEEE 20th International Conference on Web Services, Santa Clara, CA, USA, June 28, 2013

MLI: An API for Distributed Machine Learning.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

Classification of sidewalks in street view images.
Proceedings of the International Green Computing Conference, 2013

2012
Modeling building thermal response to HVAC zoning.
SIGBED Rev., 2012

Identifying models of HVAC systems using semiparametric regression.
Proceedings of the American Control Conference, 2012

Representing USDL for Humans and Tools.
Proceedings of the Handbook of Service Description - USDL and Its Methods, 2012


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