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Distributed machine learning (ML) systems today use an unsophisticated threat model: data sources must trust a central ML process.
A Newton-Raphson algorithm for maximum likelihood factor analysis
1969
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A Survey of Approaches to Automatic Schema Matching
2001
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Hashcash - A Denial of Service Counter-Measure
2002
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The sybil attack
2002
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Tor: The Second-generation Onion Router
2004
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A Survey of Outlier Detection Methodologies
2004
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Low-Cost Traffic Analysis of Tor
2005
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Exploiting Machine Learning to Subvert Your Spam Filter
2008
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A Practical Congestion Attack on Tor Using Long Paths
2009
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The Quasi-Newton Least Squares Method: A New and Fast Secant Method Analyzed for Linear Systems
2009
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ANTIDOTE: Understanding and Defending Against Poisoning of Anomaly Detectors
2009
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2009
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The Security of Machine Learning
2010
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Large-Scale Machine Learning with Stochastic Gradient Descent
2010
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”You Might Also Like: ” Privacy Risks of Collaborative Filtering
2011
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Adversarial Machine Learning
2011
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Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
2011
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Poisoning Attacks Against Support Vector Machines
2012
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Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud
2012
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Users Get Routed: Traffic Correlation on Tor by Realistic Adversaries
2013
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UCI machine learning repository, 2013
2013
Cited alongside, same era.
Stochastic gradient descent with differentially private updates
Privacy-preserving deep learning
2015
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Vuvuzela: Scalable private messaging resistant to traffic analysis
2015
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TensorFlow: A system for large-scale machine learning
2016
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Oblivious Multi-Party Machine Learning on Trusted Processors
2016
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Stealing Machine Learning Models via Prediction APIs
2016
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Practical secure aggregation for privacy-preserving machine learning
2017
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Secure Sharing of Geospatial Wildlife Data
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2013
Cited alongside, same era.
The Algorithmic Foundations of Differential Privacy
2014
Cited alongside, same era.
Privacy in pharmacogenetics: An end-to-end case study of personalized warfarin dosing
2014
Cited alongside, same era.
Differentially private distributed logistic regression using private and public data
2014
Cited alongside, same era.
Scaling Distributed Machine Learning with the Parameter Server
2014
Cited alongside, same era.
Riposte: An Anonymous Messaging System Handling Millions of Users
2015
Cited alongside, same era.
2017
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Differentially private federated learning: A client level perspective
2017
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Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning
2017
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Gaia: Geo-Distributed Machine Learning Approaching LAN Speeds
2017
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Communication-Efficient Learning of Deep Networks from Decentralized Data
2017
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Federated Learning: Collaborative Machine Learning without Centralized Training Data
2017
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SecureML: A System for Scalable Privacy-Preserving Machine Learning
2017
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A Berkeley View of Systems Challenges for AI
2017
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