Nathalie Baracaldo

Orcid: 0000-0001-9469-045X

According to our database1, Nathalie Baracaldo authored at least 75 papers between 2011 and 2024.

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Bibliography

2024
MAP: Multi-Human-Value Alignment Palette.
CoRR, 2024

WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models.
CoRR, 2024

Mitigating Forgetting in LLM Supervised Fine-Tuning and Preference Learning.
CoRR, 2024

Turning Generative Models Degenerate: The Power of Data Poisoning Attacks.
CoRR, 2024

Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs.
CoRR, 2024

Rethinking Machine Unlearning for Large Language Models.
CoRR, 2024

FedKDD: International Joint Workshop on Federated Learning for Data Mining and Graph Analytics.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Byzantine-Resilient Bilevel Federated Learning.
Proceedings of the 13th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2024

Enhancing In-context Learning via Linear Probe Calibration.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Is Federated Learning Still Alive in the Foundation Model Era?
Proceedings of the AAAI 2024 Spring Symposium Series, 2024

2023
FairSISA: Ensemble Post-Processing to Improve Fairness of Unlearning in LLMs.
CoRR, 2023

Forcing Generative Models to Degenerate Ones: The Power of Data Poisoning Attacks.
CoRR, 2023

Privacy-Preserving Federated Learning over Vertically and Horizontally Partitioned Data for Financial Anomaly Detection.
CoRR, 2023

Benchmarking the Effect of Poisoning Defenses on the Security and Bias of Deep Learning Models.
Proceedings of the 2023 IEEE Security and Privacy Workshops (SPW), 2023

LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning.
Proceedings of the International Conference on Machine Learning, 2023

Single-shot General Hyper-parameter Optimization for Federated Learning.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

HDFL: A Heterogeneity and Client Dropout-Aware Federated Learning Framework.
Proceedings of the 23rd IEEE/ACM International Symposium on Cluster, 2023

2022
Machine Learning Security and Privacy.
IEEE Secur. Priv., 2022

Federated XGBoost on Sample-Wise Non-IID Data.
CoRR, 2022

Federated Unlearning: How to Efficiently Erase a Client in FL?
CoRR, 2022

A Distributed and Elastic Aggregation Service for Scalable Federated Learning Systems.
CoRR, 2022

Towards an Accountable and Reproducible Federated Learning: A FactSheets Approach.
CoRR, 2022

Single-shot Hyper-parameter Optimization for Federated Learning: A General Algorithm & Analysis.
CoRR, 2022

Keynote Talk - Federated Learning: The Hype, State-of-the-Art and Open Challenges.
Proceedings of the SACMAT '22: The 27th ACM Symposium on Access Control Models and Technologies, New York, NY, USA, June 8, 2022

The 1st International Workshop on Federated Learning with Graph Data (FedGraph).
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Heterogeneity-Aware Adaptive Federated Learning Scheduling.
Proceedings of the IEEE International Conference on Big Data, 2022

DeTrust-FL: Privacy-Preserving Federated Learning in Decentralized Trust Setting.
Proceedings of the IEEE 15th International Conference on Cloud Computing, 2022

TIFF: Tokenized Incentive for Federated Learning.
Proceedings of the IEEE 15th International Conference on Cloud Computing, 2022

Privacy-Preserving Vertical Federated Learning.
Proceedings of the Federated Learning, 2022

Federated Learning for Collaborative Financial Crimes Detection.
Proceedings of the Federated Learning, 2022

Tree-Based Models for Federated Learning Systems.
Proceedings of the Federated Learning, 2022

Introduction to Federated Learning.
Proceedings of the Federated Learning, 2022

Protecting Against Data Leakage in Federated Learning: What Approach Should You Choose?
Proceedings of the Federated Learning, 2022

Federated Learning and Fairness.
Proceedings of the Federated Learning, 2022

Dealing with Byzantine Threats to Neural Networks.
Proceedings of the Federated Learning, 2022

2021
FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning.
CoRR, 2021

Privacy-Preserving Machine Learning: Methods, Challenges and Directions.
CoRR, 2021

Conference Tutorial: Can federated learning solve our data privacy problems? State of the art and open challenges.
Proceedings of the 3rd IEEE International Conference on Trust, 2021

The Design and Development of a Game to Study Backdoor Poisoning Attacks: The Backdoor Game.
Proceedings of the IUI '21: 26th International Conference on Intelligent User Interfaces, 2021

Accountable Federated Machine Learning in Government: Engineering and Management Insights.
Proceedings of the Electronic Participation - 13th IFIP WG 8.5 International Conference, 2021

FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data.
Proceedings of the AISec@CCS 2021: Proceedings of the 14th ACM Workshop on Artificial Intelligence and Security, 2021

Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

LEGATO: A LayerwisE Gradient AggregaTiOn Algorithm for Mitigating Byzantine Attacks in Federated Learning.
Proceedings of the 14th IEEE International Conference on Cloud Computing, 2021

2020
Towards Privacy Preservation and Data Protection in Information System Design. An introduction to the special issue.
Enterp. Model. Inf. Syst. Archit. Int. J. Concept. Model., 2020

Adaptive Histogram-Based Gradient Boosted Trees for Federated Learning.
CoRR, 2020

Mitigating Bias in Federated Learning.
CoRR, 2020

IBM Federated Learning: an Enterprise Framework White Paper V0.1.
CoRR, 2020

TiFL: A Tier-based Federated Learning System.
Proceedings of the HPDC '20: The 29th International Symposium on High-Performance Parallel and Distributed Computing, 2020

2019
G-SIR: An Insider Attack Resilient Geo-Social Access Control Framework.
IEEE Trans. Dependable Secur. Comput., 2019

A Hybrid Approach to Privacy-Preserving Federated Learning - (Extended Abstract).
Inform. Spektrum, 2019

User Centered and Privacy-Driven Process Mining System Design - (Extended Abstract).
Inform. Spektrum, 2019

Privacy-preserving Process Mining: Differential - Privacy for Event Logs (Extended Abstract).
Inform. Spektrum, 2019

Privacy-Preserving Process Mining - Differential Privacy for Event Logs.
Bus. Inf. Syst. Eng., 2019

Towards Taming the Resource and Data Heterogeneity in Federated Learning.
Proceedings of the 2019 USENIX Conference on Operational Machine Learning, 2019

Using BPM Technology to Deploy and Manage Distributed Analytics in Collaborative IoT-Driven Business Scenarios.
Proceedings of the 9th International Conference on the Internet of Things, 2019

HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning.
Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security, 2019

A Hybrid Approach to Privacy-Preserving Federated Learning.
Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security, 2019

User-Centered and Privacy-Driven Process Mining System Design for IoT.
Proceedings of the Information Systems Engineering in Responsible Information Systems, 2019

Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering.
Proceedings of the Workshop on Artificial Intelligence Safety 2019 co-located with the Thirty-Third AAAI Conference on Artificial Intelligence 2019 (AAAI-19), 2019

2018
A Hybrid Approach to Privacy-Preserving Federated Learning.
CoRR, 2018

Complex Collaborative Physical Process Management: A Position on the Trinity of BPM, IoT and DA.
Proceedings of the Collaborative Networks of Cognitive Systems, 2018

Detecting Poisoning Attacks on Machine Learning in IoT Environments.
Proceedings of the 2018 IEEE International Congress on Internet of Things, 2018

2017
rSLA: An Approach for Managing Service Level Agreements in Cloud Environments.
Int. J. Cooperative Inf. Syst., 2017

Mitigating Poisoning Attacks on Machine Learning Models: A Data Provenance Based Approach.
Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security, 2017

2016
Managing Service Quality at the Platform and Application Levels with rSLa.
Proceedings of the 25th IEEE International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises, 2016

Data Provenance Model for Internet of Things (IoT) Systems.
Proceedings of the Service-Oriented Computing - ICSOC 2016 Workshops, 2016

Securing Data Provenance in Internet of Things (IoT) Systems.
Proceedings of the Service-Oriented Computing - ICSOC 2016 Workshops, 2016

2014
Geo-Social-RBAC: A Location-Based Socially Aware Access Control Framework.
Proceedings of the Network and System Security - 8th International Conference, 2014

IEEE IRI 2014 invited industry talks (I): Managing shared information in multi-tenant service provider applications.
Proceedings of the 15th IEEE International Conference on Information Reuse and Integration, 2014

Reconciling End-to-End Confidentiality and Data Reduction In Cloud Storage.
Proceedings of the 6th edition of the ACM Workshop on Cloud Computing Security, 2014

2013
An adaptive risk management and access control framework to mitigate insider threats.
Comput. Secur., 2013

Beyond accountability: using obligations to reduce risk exposure and deter insider attacks.
Proceedings of the 18th ACM Symposium on Access Control Models and Technologies, 2013

2012
A trust-and-risk aware RBAC framework: tackling insider threat.
Proceedings of the 17th ACM Symposium on Access Control Models and Technologies, 2012

2011
A secure, constraint-aware role-based access control interoperation framework.
Proceedings of the 5th International Conference on Network and System Security, 2011

Simulating the effect of privacy concerns in online social networks.
Proceedings of the IEEE International Conference on Information Reuse and Integration, 2011


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