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08/29/2023
The Relative Gaussian Mechanism and its Application to Private Gradient Descent
The Gaussian Mechanism (GM), which consists in adding Gaussian noise to ...
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06/05/2023
Improved Stability and Generalization Analysis of the Decentralized SGD Algorithm
This paper presents a new generalization error analysis for the Decentra...
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05/25/2023
DP-SGD Without Clipping: The Lipschitz Neural Network Way
State-of-the-art approaches for training Differentially Private (DP) Dee...
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05/21/2023
How to Capture Intersectional Fairness
In this work, we tackle the problem of intersectional group fairness in ...
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02/24/2023
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning
We study differentially private (DP) machine learning algorithms as inst...
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02/13/2023
One-Shot Federated Conformal Prediction
In this paper, we introduce a conformal prediction method to construct p...
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10/28/2022
Fairness Certificates for Differentially Private Classification
In this work, we theoretically study the impact of differential privacy ...
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08/24/2022
Collaborative Algorithms for Online Personalized Mean Estimation
We consider an online estimation problem involving a set of agents. Each...
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08/09/2022
PEPPER: Empowering User-Centric Recommender Systems over Gossip Learning
Recommender systems are proving to be an invaluable tool for extracting ...
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07/04/2022
High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent
In this paper, we study differentially private empirical risk minimizati...
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06/10/2022
Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging
Decentralized optimization is increasingly popular in machine learning f...
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05/12/2022
Fair NLP Models with Differentially Private Text Encoders
Encoded text representations often capture sensitive attributes about in...
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03/02/2022
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation
Graph Neural Networks (GNNs) are powerful models designed for graph data...
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02/23/2022
Differentially Private Speaker Anonymization
Sharing real-world speech utterances is key to the training and deployme...
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12/23/2021
Mitigating Leakage from Data Dependent Communications in Decentralized Computing using Differential Privacy
Imagine a group of citizens willing to collectively contribute their per...
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11/17/2021
Differentially Private Federated Learning on Heterogeneous Data
Federated Learning (FL) is a paradigm for large-scale distributed learni...
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10/22/2021
Differentially Private Coordinate Descent for Composite Empirical Risk Minimization
Machine learning models can leak information about the data used to trai...
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08/23/2021
Federated Multi-Task Learning under a Mixture of Distributions
The increasing size of data generated by smartphones and IoT devices mot...
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04/15/2021
D-Cliques: Compensating NonIIDness in Decentralized Federated Learning with Topology
The convergence speed of machine learning models trained with Federated ...
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12/09/2020
Privacy Amplification by Decentralization
Analyzing data owned by several parties while achieving a good trade-off...
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06/12/2020
Distributed Differentially Private Averaging with Improved Utility and Robustness to Malicious Parties
Learning from data owned by several parties, as in federated learning, r...
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05/18/2020
Design Choices for X-vector Based Speaker Anonymization
The recently proposed x-vector based anonymization scheme converts any i...
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02/19/2020
Learning Fair Scoring Functions: Fairness Definitions, Algorithms and Generalization Bounds for Bipartite Ranking
Many applications of artificial intelligence, ranging from credit lendin...
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12/10/2019
Advances and Open Problems in Federated Learning
Federated learning (FL) is a machine learning setting where many clients...
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11/12/2019
Privacy-Preserving Adversarial Representation Learning in ASR: Reality or Illusion?
Automatic speech recognition (ASR) is a key technology in many services ...
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11/10/2019
Evaluating Voice Conversion-based Privacy Protection against Informed Attackers
Speech signals are a rich source of speaker-related information includin...
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10/09/2019
Private Protocols for U-Statistics in the Local Model and Beyond
In this paper, we study the problem of computing U-statistics of degree ...
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08/13/2019
metric-learn: Metric Learning Algorithms in Python
metric-learn is an open source Python package implementing supervised an...
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06/21/2019
Trade-offs in Large-Scale Distributed Tuplewise Estimation and Learning
The development of cluster computing frameworks has allowed practitioner...
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02/19/2019
Who started this rumor? Quantifying the natural differential privacy guarantees of gossip protocols
Gossip protocols, also called rumor spreading or epidemic protocols, are...
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01/24/2019
Communication-Efficient and Decentralized Multi-Task Boosting while Learning the Collaboration Graph
We study the decentralized machine learning scenario where many users co...
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07/20/2018
Escaping the Curse of Dimensionality in Similarity Learning: Efficient Frank-Wolfe Algorithm and Generalization Bounds
Similarity and metric learning provides a principled approach to constru...
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07/18/2018
A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization
The performance of many machine learning techniques depends on the choic...
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03/27/2018
Hiding in the Crowd: A Massively Distributed Algorithm for Private Averaging with Malicious Adversaries
The amount of personal data collected in our everyday interactions with ...
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12/20/2017
A Distributed Frank-Wolfe Framework for Learning Low-Rank Matrices with the Trace Norm
We consider the problem of learning a high-dimensional but low-rank matr...
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05/23/2017
Fast and Differentially Private Algorithms for Decentralized Collaborative Machine Learning
Consider a set of agents in a peer-to-peer communication network, where ...
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01/13/2017
Kernel Approximation Methods for Speech Recognition
We study large-scale kernel methods for acoustic modeling in speech reco...
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10/17/2016
Decentralized Collaborative Learning of Personalized Models over Networks
We consider a set of learning agents in a collaborative peer-to-peer net...
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06/08/2016
Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions
In decentralized networks (of sensors, connected objects, etc.), there i...
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03/18/2016
A Comparison between Deep Neural Nets and Kernel Acoustic Models for Speech Recognition
We study large-scale kernel methods for acoustic modeling and compare to...
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11/17/2015
Extending Gossip Algorithms to Distributed Estimation of U-Statistics
Efficient and robust algorithms for decentralized estimation in networks...
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01/12/2015
Scaling-up Empirical Risk Minimization: Optimization of Incomplete U-statistics
In a wide range of statistical learning problems such as ranking, cluste...
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11/14/2014
How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets
The computational complexity of kernel methods has often been a major ba...
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11/10/2014
Similarity Learning for High-Dimensional Sparse Data
A good measure of similarity between data points is crucial to many task...
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04/15/2014
Sparse Compositional Metric Learning
We propose a new approach for metric learning by framing it as learning ...
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04/09/2014
A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning
Learning sparse combinations is a frequent theme in machine learning. In...
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07/17/2013
Supervised Metric Learning with Generalization Guarantees
The crucial importance of metrics in machine learning algorithms has led...
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06/28/2013
A Survey on Metric Learning for Feature Vectors and Structured Data
The need for appropriate ways to measure the distance or similarity betw...
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09/05/2012
Robustness and Generalization for Metric Learning
Metric learning has attracted a lot of interest over the last decade, bu...
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06/27/2012
