Nathalie Baracaldo

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 65

Top Topics

Data Provenance

Machine Learning

Top Venues

Inform. Spektrum

Publications

Swanand Ravindra Kadhe, Farhan Ahmed, Dennis Wei, Nathalie Baracaldo, Inkit Padhi
Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs. CoRR (2024)
Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen
Enhancing In-context Learning via Linear Probe Calibration. AISTATS (2024)
Nathalie Baracaldo
Is Federated Learning Still Alive in the Foundation Model Era? AAAI Spring Symposia (2024)
Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen
Enhancing In-context Learning via Linear Probe Calibration. CoRR (2024)
Junyuan Hong, Carl Yang, Zhuangdi Zhu, Zheng Xu, Nathalie Baracaldo, Neil Shah, Salman Avestimehr, Jiayu Zhou
FedKDD: International Joint Workshop on Federated Learning for Data Mining and Graph Analytics. KDD (2024)
Shuli Jiang, Swanand Ravindra Kadhe, Yi Zhou, Farhan Ahmed, Ling Cai, Nathalie Baracaldo
Turning Generative Models Degenerate: The Power of Data Poisoning Attacks. CoRR (2024)
Sijia Liu, Yuanshun Yao, Jinghan Jia, Stephen Casper, Nathalie Baracaldo, Peter Hase, Xiaojun Xu, Yuguang Yao, Hang Li, Kush R. Varshney, Mohit Bansal, Sanmi Koyejo, Yang Liu
Rethinking Machine Unlearning for Large Language Models. CoRR (2024)
Timothy Castiglia, Yi Zhou, Shiqiang Wang, Swanand Kadhe, Nathalie Baracaldo, Stacy Patterson
LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning. CoRR (2023)
Syed Zawad, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Feng Yan
HDFL: A Heterogeneity and Client Dropout-Aware Federated Learning Framework. CCGrid (2023)
Nathalie Baracaldo, Farhan Ahmed, Kevin Eykholt, Yi Zhou, Shriti Priya, Taesung Lee, Swanand Kadhe, Mike Tan, Sridevi Polavaram, Sterling Suggs, Yuyang Gao, David Slater
Benchmarking the Effect of Poisoning Defenses on the Security and Bias of Deep Learning Models. SP Workshops (2023)
Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig
Single-shot General Hyper-parameter Optimization for Federated Learning. ICLR (2023)
Timothy Castiglia, Yi Zhou, Shiqiang Wang, Swanand Kadhe, Nathalie Baracaldo, Stacy Patterson
LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning. ICML (2023)
Swanand Ravindra Kadhe, Heiko Ludwig, Nathalie Baracaldo, Alan King, Yi Zhou, Keith Houck, Ambrish Rawat, Mark Purcell, Naoise Holohan, Mikio Takeuchi, Ryo Kawahara, Nir Drucker, Hayim Shaul, Eyal Kushnir, Omri Soceanu
Privacy-Preserving Federated Learning over Vertically and Horizontally Partitioned Data for Financial Anomaly Detection. CoRR (2023)
Swanand Ravindra Kadhe, Anisa Halimi, Ambrish Rawat, Nathalie Baracaldo
FairSISA: Ensemble Post-Processing to Improve Fairness of Unlearning in LLMs. CoRR (2023)
Shuli Jiang, Swanand Ravindra Kadhe, Yi Zhou, Ling Cai, Nathalie Baracaldo
Forcing Generative Models to Degenerate Ones: The Power of Data Poisoning Attacks. CoRR (2023)
Jingoo Han, Ahmad Faraz Khan, Syed Zawad, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Feng Yan, Ali Raza Butt
Heterogeneity-Aware Adaptive Federated Learning Scheduling. Big Data (2022)
Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, Swanand Kadhe, Heiko Ludwig
DeTrust-FL: Privacy-Preserving Federated Learning in Decentralized Trust Setting. CoRR (2022)
Carl Yang, Xiaoxiao Li, Nathalie Baracaldo, Neil Shah, Chaoyang He, Lingjuan Lyu, Lichao Sun, Salman Avestimehr
The 1st International Workshop on Federated Learning with Graph Data (FedGraph). CIKM (2022)
Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, Swanand Kadhe, Heiko Ludwig
DeTrust-FL: Privacy-Preserving Federated Learning in Decentralized Trust Setting. CLOUD (2022)
Jingoo Han, Ahmad Faraz Khan, Syed Zawad, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Feng Yan, Ali Raza Butt
TIFF: Tokenized Incentive for Federated Learning. CLOUD (2022)
Katelinh Jones, Yuya Jeremy Ong, Yi Zhou, Nathalie Baracaldo
Federated XGBoost on Sample-Wise Non-IID Data. CoRR (2022)
Nathalie Baracaldo, Alina Oprea
Machine Learning Security and Privacy. IEEE Secur. Priv. 20 (5) (2022)
Nathalie Baracaldo
Keynote Talk - Federated Learning: The Hype, State-of-the-Art and Open Challenges. SACMAT (2022)
Nathalie Baracaldo, Ali Anwar, Mark Purcell, Ambrish Rawat, Mathieu Sinn, Bashar Altakrouri, Dian Balta, Mahdi Sellami, Peter Kuhn, Ulrich Schöpp, Matthias Buchinger
Towards an Accountable and Reproducible Federated Learning: A FactSheets Approach. CoRR (2022)
Anisa Halimi, Swanand Kadhe, Ambrish Rawat, Nathalie Baracaldo
Federated Unlearning: How to Efficiently Erase a Client in FL? CoRR (2022)
Ahmad Khan, Yuze Li, Ali Anwar, Yue Cheng, Thang Hoang, Nathalie Baracaldo, Ali Raza Butt
A Distributed and Elastic Aggregation Service for Scalable Federated Learning Systems. CoRR (2022)
Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig
Single-shot Hyper-parameter Optimization for Federated Learning: A General Algorithm & Analysis. CoRR (2022)
Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, James Joshi, Heiko Ludwig
FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data. AISec@CCS (2021)
Zahra Ashktorab, Casey Dugan, James Johnson, Aabhas Sharma, Dustin Ramsey Torres, Ingrid Lange, Benjamin Hoover, Heiko Ludwig, Bryant Chen, Nathalie Baracaldo, Werner Geyer, Qian Pan
The Design and Development of a Game to Study Backdoor Poisoning Attacks: The Backdoor Game. IUI (2021)
Kamala Varma, Yi Zhou, Nathalie Baracaldo, Ali Anwar
LEGATO: A LayerwisE Gradient AggregaTiOn Algorithm for Mitigating Byzantine Attacks in Federated Learning. CLOUD (2021)
Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig
FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning. CoRR (2021)
Runhua Xu, Nathalie Baracaldo, James Joshi
Privacy-Preserving Machine Learning: Methods, Challenges and Directions. CoRR (2021)
Syed Zawad, Ahsan Ali, Pin-Yu Chen, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Yuan Tian, Feng Yan
Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning. AAAI (2021)
Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, James Joshi, Heiko Ludwig
FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data. CoRR (2021)
Dian Balta, Mahdi Sellami, Peter Kuhn, Ulrich Schöpp, Matthias Buchinger, Nathalie Baracaldo, Ali Anwar, Heiko Ludwig, Mathieu Sinn, Mark Purcell, Bashar Altakrouri
Accountable Federated Machine Learning in Government: Engineering and Management Insights. ePart (2021)
Syed Zawad, Ahsan Ali, Pin-Yu Chen, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Yuan Tian, Feng Yan
Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning. CoRR (2021)
Kamala Varma, Yi Zhou, Nathalie Baracaldo, Ali Anwar
LEGATO: A LayerwisE Gradient AggregaTiOn Algorithm for Mitigating Byzantine Attacks in Federated Learning. CoRR (2021)
Nathalie Baracaldo
Conference Tutorial: Can federated learning solve our data privacy problems? State of the art and open challenges. TPS-ISA (2021)
Heiko Ludwig, Nathalie Baracaldo, Gegi Thomas, Yi Zhou, Ali Anwar, Shashank Rajamoni, Yuya Jeremy Ong, Jayaram Radhakrishnan, Ashish Verma, Mathieu Sinn, Mark Purcell, Ambrish Rawat, Tran Ngoc Minh, Naoise Holohan, Supriyo Chakraborty, Shalisha Witherspoon, Dean Steuer, Laura Wynter, Hifaz Hassan, Sean Laguna, Mikhail Yurochkin, Mayank Agarwal, Ebube Chuba, Annie Abay
IBM Federated Learning: an Enterprise Framework White Paper V0.1. CoRR (2020)
Zheng Chai, Ahsan Ali, Syed Zawad, Stacey Truex, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Heiko Ludwig, Feng Yan, Yue Cheng
TiFL: A Tier-based Federated Learning System. HPDC (2020)
Agnes Koschmider, Judith Michael, Nathalie Baracaldo
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. 15 (2020)
Zheng Chai, Ahsan Ali, Syed Zawad, Stacey Truex, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Heiko Ludwig, Feng Yan, Yue Cheng
TiFL: A Tier-based Federated Learning System. CoRR (2020)
Yuya Jeremy Ong, Yi Zhou, Nathalie Baracaldo, Heiko Ludwig
Adaptive Histogram-Based Gradient Boosted Trees for Federated Learning. CoRR (2020)
Annie Abay, Yi Zhou, Nathalie Baracaldo, Shashank Rajamoni, Ebube Chuba, Heiko Ludwig
Mitigating Bias in Federated Learning. CoRR (2020)
Judith Michael, Agnes Koschmider, Felix Mannhardt, Nathalie Baracaldo, Bernhard Rumpe
User Centered and Privacy-Driven Process Mining System Design - (Extended Abstract). Inform. Spektrum 42 (5) (2019)
Judith Michael, Agnes Koschmider, Felix Mannhardt, Nathalie Baracaldo, Bernhard Rumpe
User-Centered and Privacy-Driven Process Mining System Design for IoT. CAiSE Forum (2019)
Stacey Truex, Nathalie Baracaldo, Ali Anwar, Thomas Steinke, Heiko Ludwig, Rui Zhang, Yi Zhou
A Hybrid Approach to Privacy-Preserving Federated Learning - (Extended Abstract). Inform. Spektrum 42 (5) (2019)
Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, Heiko Ludwig
HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning. AISec@CCS (2019)
Stacey Truex, Nathalie Baracaldo, Ali Anwar, Thomas Steinke, Heiko Ludwig, Rui Zhang, Yi Zhou
A Hybrid Approach to Privacy-Preserving Federated Learning. AISec@CCS (2019)
Felix Mannhardt, Agnes Koschmider, Nathalie Baracaldo, Matthias Weidlich, Judith Michael
Privacy-Preserving Process Mining - Differential Privacy for Event Logs. Bus. Inf. Syst. Eng. 61 (5) (2019)
Felix Mannhardt, Agnes Koschmider, Nathalie Baracaldo, Matthias Weidlich, Judith Michael
Privacy-preserving Process Mining: Differential - Privacy for Event Logs (Extended Abstract). Inform. Spektrum 42 (5) (2019)
Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, Heiko Ludwig
HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning. CoRR (2019)
Nathalie Baracaldo, Balaji Palanisamy, James Joshi
G-SIR: An Insider Attack Resilient Geo-Social Access Control Framework. IEEE Trans. Dependable Secur. Comput. 16 (1) (2019)
Bryant Chen, Wilka Carvalho, Nathalie Baracaldo, Heiko Ludwig, Benjamin Edwards, Taesung Lee, Ian M. Molloy, Biplav Srivastava
Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering. SafeAI@AAAI (2019)
Tim D'Hondt, Anna Wilbik, Paul Grefen, Heiko Ludwig, Nathalie Baracaldo, Ali Anwar
Using BPM Technology to Deploy and Manage Distributed Analytics in Collaborative IoT-Driven Business Scenarios. IOT (2019)
Zheng Chai, Hannan Fayyaz, Zeshan Fayyaz, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Heiko Ludwig, Yue Cheng
Towards Taming the Resource and Data Heterogeneity in Federated Learning. OpML (2019)
Nathalie Baracaldo, Bryant Chen, Heiko Ludwig, Jaehoon Amir Safavi, Rui Zhang
Detecting Poisoning Attacks on Machine Learning in IoT Environments. ICIOT (2018)
Stacey Truex, Nathalie Baracaldo, Ali Anwar, Thomas Steinke, Heiko Ludwig, Rui Zhang
A Hybrid Approach to Privacy-Preserving Federated Learning. CoRR (2018)
Paul Grefen, Heiko Ludwig, Samir Tata, Remco M. Dijkman, Nathalie Baracaldo, Anna Wilbik, Tim D'Hondt
Complex Collaborative Physical Process Management: A Position on the Trinity of BPM, IoT and DA. PRO-VE (2018)
Bryant Chen, Wilka Carvalho, Nathalie Baracaldo, Heiko Ludwig, Benjamin Edwards, Taesung Lee, Ian M. Molloy, Biplav Srivastava
Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering. CoRR (2018)
Mohamed Mohamed, Obinna Anya, Samir Tata, NagaPramod Mandagere, Nathalie Baracaldo, Heiko Ludwig
rSLA: An Approach for Managing Service Level Agreements in Cloud Environments. Int. J. Cooperative Inf. Syst. 26 (2) (2017)
Nathalie Baracaldo, Bryant Chen, Heiko Ludwig, Jaehoon Amir Safavi
Mitigating Poisoning Attacks on Machine Learning Models: A Data Provenance Based Approach. AISec@CCS (2017)
Nathalie Baracaldo, Luis Angel D. Bathen, Roqeeb O. Ozugha, Robert Engel, Samir Tata, Heiko Ludwig
Securing Data Provenance in Internet of Things (IoT) Systems. ICSOC Workshops (2016)
Habeeb Olufowobi, Robert Engel, Nathalie Baracaldo, Luis Angel D. Bathen, Samir Tata, Heiko Ludwig
Data Provenance Model for Internet of Things (IoT) Systems. ICSOC Workshops (2016)
Samir Tata, Mohamed Mohamed, Obinna Anya, Takashi Sakairi, NagaPramod Mandagere, Heiko Ludwig, Nathalie Baracaldo
Managing Service Quality at the Platform and Application Levels with rSLa. WETICE (2016)
Heiko Ludwig, Nathalie Baracaldo, Nish Parikh, Tanvir Ahmed, Rajesh Subramanyan
IEEE IRI 2014 invited industry talks (I): Managing shared information in multi-tenant service provider applications. IRI (2014)
Nathalie Baracaldo, Balaji Palanisamy, James B. D. Joshi
Geo-Social-RBAC: A Location-Based Socially Aware Access Control Framework. NSS (2014)
Nathalie Baracaldo, Elli Androulaki, Joseph S. Glider, Alessandro Sorniotti
Reconciling End-to-End Confidentiality and Data Reduction In Cloud Storage. CCSW (2014)
Nathalie Baracaldo, James Joshi
Beyond accountability: using obligations to reduce risk exposure and deter insider attacks. SACMAT (2013)
Nathalie Baracaldo, James Joshi
An adaptive risk management and access control framework to mitigate insider threats. Comput. Secur. 39 (2013)
Nathalie Baracaldo, James Joshi
A trust-and-risk aware RBAC framework: tackling insider threat. SACMAT (2012)
Nathalie Baracaldo, Claudia A. López, Mohd Anwar, Michael Lewis
Simulating the effect of privacy concerns in online social networks. IRI (2011)
Nathalie Baracaldo, Amirreza Masoumzadeh, James Joshi
A secure, constraint-aware role-based access control interoperation framework. NSS (2011)