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ORCIDNathalie Baracaldo
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2020 – today
- 2024
[c39]Nathalie Baracaldo:
Is Federated Learning Still Alive in the Foundation Model Era? AAAI Spring Symposia 2024: 293- [c38]Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen:
Enhancing In-context Learning via Linear Probe Calibration. AISTATS 2024: 307-315 - [c37]Momin Abbas, Yi Zhou, Nathalie Baracaldo, Horst Samulowitz, Parikshit Ram, Theodoros Salonidis:
Byzantine-Resilient Bilevel Federated Learning. SAM 2024: 1-5 - [c36]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: 6718-6719 - [i29]Momin Abbas, Yi Zhou, Parikshit Ram, Nathalie Baracaldo, Horst Samulowitz, Theodoros Salonidis, Tianyi Chen:
Enhancing In-context Learning via Linear Probe Calibration. CoRR abs/2401.12406 (2024) - [i28]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 abs/2402.08787 (2024) - [i27]Swanand Ravindra Kadhe, Farhan Ahmed, Dennis Wei, Nathalie Baracaldo, Inkit Padhi:
Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs. CoRR abs/2406.11780 (2024) - [i26]Shuli Jiang, Swanand Ravindra Kadhe, Yi Zhou, Farhan Ahmed, Ling Cai, Nathalie Baracaldo:
Turning Generative Models Degenerate: The Power of Data Poisoning Attacks. CoRR abs/2407.12281 (2024) - [i25]Heshan Devaka Fernando, Han Shen, Parikshit Ram, Yi Zhou, Horst Samulowitz, Nathalie Baracaldo, Tianyi Chen:
Mitigating Forgetting in LLM Supervised Fine-Tuning and Preference Learning. CoRR abs/2410.15483 (2024) - [i24]Jinghan Jia, Jiancheng Liu, Yihua Zhang, Parikshit Ram, Nathalie Baracaldo, Sijia Liu:
WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models. CoRR abs/2410.17509 (2024) - [i23]Xinran Wang, Qi Le, Ammar Ahmed, Enmao Diao, Yi Zhou, Nathalie Baracaldo, Jie Ding, Ali Anwar:
MAP: Multi-Human-Value Alignment Palette. CoRR abs/2410.19198 (2024) - 2023
- [c35]Syed Zawad, Ali Anwar, Yi Zhou, Nathalie Baracaldo, Feng Yan:
HDFL: A Heterogeneity and Client Dropout-Aware Federated Learning Framework. CCGrid 2023: 311-321 - [c34]Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig:
Single-shot General Hyper-parameter Optimization for Federated Learning. ICLR 2023 - [c33]Timothy Castiglia, Yi Zhou, Shiqiang Wang, Swanand Kadhe, Nathalie Baracaldo, Stacy Patterson:
LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning. ICML 2023: 3757-3781 - [c32]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: 45-56 - [e2]Stefanos Laskaridis, Alexey Tumanov, Nathalie Baracaldo, Dimitrios Vytiniotis:
Proceedings of the 4th International Workshop on Distributed Machine Learning, DistributedML 2023, Paris, France, 8 December 2023. ACM 2023 [contents] - [i22]Timothy Castiglia, Yi Zhou, Shiqiang Wang, Swanand Kadhe, Nathalie Baracaldo, Stacy Patterson:
LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning. CoRR abs/2305.02219 (2023) - [i21]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 abs/2310.19304 (2023) - [i20]Shuli Jiang, Swanand Ravindra Kadhe, Yi Zhou, Ling Cai, Nathalie Baracaldo:
Forcing Generative Models to Degenerate Ones: The Power of Data Poisoning Attacks. CoRR abs/2312.04748 (2023) - [i19]Swanand Ravindra Kadhe, Anisa Halimi, Ambrish Rawat, Nathalie Baracaldo:
FairSISA: Ensemble Post-Processing to Improve Fairness of Unlearning in LLMs. CoRR abs/2312.07420 (2023) - 2022
- [j9]Nathalie Baracaldo, Alina Oprea:
Machine Learning Security and Privacy. IEEE Secur. Priv. 20(5): 11-13 (2022) - [c31]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: 407-416 - [c30]Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, Swanand Kadhe, Heiko Ludwig:
DeTrust-FL: Privacy-Preserving Federated Learning in Decentralized Trust Setting. CLOUD 2022: 417-426 - [c29]Jingoo Han, Ahmad Faraz Khan, Syed Zawad, Ali Anwar, Nathalie Baracaldo, Yi Zhou, Feng Yan, Ali Raza Butt:
Heterogeneity-Aware Adaptive Federated Learning Scheduling. IEEE Big Data 2022: 911-920 - [c28]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: 5179-5180 - [c27]Nathalie Baracaldo:
Keynote Talk - Federated Learning: The Hype, State-of-the-Art and Open Challenges. SACMAT 2022: 3-4 - [p7]Heiko Ludwig, Nathalie Baracaldo:
Introduction to Federated Learning. Federated Learning 2022: 1-23 - [p6]Yuya Jeremy Ong, Nathalie Baracaldo, Yi Zhou:
Tree-Based Models for Federated Learning Systems. Federated Learning 2022: 27-52 - [p5]Annie Abay, Yi Zhou, Nathalie Baracaldo, Heiko Ludwig:
Federated Learning and Fairness. Federated Learning 2022: 177-191 - [p4]Nathalie Baracaldo, Runhua Xu:
Protecting Against Data Leakage in Federated Learning: What Approach Should You Choose? Federated Learning 2022: 281-312 - [p3]Yi Zhou, Nathalie Baracaldo, Ali Anwar, Kamala Varma:
Dealing with Byzantine Threats to Neural Networks. Federated Learning 2022: 391-414 - [p2]Runhua Xu, Nathalie Baracaldo, Yi Zhou, Annie Abay, Ali Anwar:
Privacy-Preserving Vertical Federated Learning. Federated Learning 2022: 417-438 - [p1]Toyotaro Suzumura, Yi Zhou, Ryo Kawahara, Nathalie Baracaldo, Heiko Ludwig:
Federated Learning for Collaborative Financial Crimes Detection. Federated Learning 2022: 455-466 - [e1]Heiko Ludwig, Nathalie Baracaldo:
Federated Learning - A Comprehensive Overview of Methods and Applications. Springer 2022, ISBN 978-3-030-96895-3 [contents] - [i18]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 abs/2202.08338 (2022) - [i17]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 abs/2202.12443 (2022) - [i16]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 abs/2204.07767 (2022) - [i15]Anisa Halimi, Swanand Kadhe, Ambrish Rawat, Nathalie Baracaldo:
Federated Unlearning: How to Efficiently Erase a Client in FL? CoRR abs/2207.05521 (2022) - [i14]Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, Swanand Kadhe, Heiko Ludwig:
DeTrust-FL: Privacy-Preserving Federated Learning in Decentralized Trust Setting. CoRR abs/2207.07779 (2022) - [i13]Katelinh Jones, Yuya Jeremy Ong, Yi Zhou, Nathalie Baracaldo:
Federated XGBoost on Sample-Wise Non-IID Data. CoRR abs/2209.01340 (2022) - 2021
- [c26]Kamala Varma, Yi Zhou, Nathalie Baracaldo, Ali Anwar:
LEGATO: A LayerwisE Gradient AggregaTiOn Algorithm for Mitigating Byzantine Attacks in Federated Learning. CLOUD 2021: 272-277 - [c25]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: 10807-10814 - [c24]Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, James Joshi, Heiko Ludwig:
FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data. AISec@CCS 2021: 181-192 - [c23]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: 125-138 - [c22]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: 423-433 - [c21]Nathalie Baracaldo:
Conference Tutorial: Can federated learning solve our data privacy problems? State of the art and open challenges. TPS-ISA 2021: xxv - [i12]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 abs/2102.00655 (2021) - [i11]Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, James Joshi, Heiko Ludwig:
FedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data. CoRR abs/2103.03918 (2021) - [i10]Kamala Varma, Yi Zhou, Nathalie Baracaldo, Ali Anwar:
LEGATO: A LayerwisE Gradient AggregaTiOn Algorithm for Mitigating Byzantine Attacks in Federated Learning. CoRR abs/2107.12490 (2021) - [i9]Runhua Xu, Nathalie Baracaldo, James Joshi:
Privacy-Preserving Machine Learning: Methods, Challenges and Directions. CoRR abs/2108.04417 (2021) - [i8]Yi Zhou, Parikshit Ram, Theodoros Salonidis, Nathalie Baracaldo, Horst Samulowitz, Heiko Ludwig:
FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning. CoRR abs/2112.08524 (2021) - 2020
- [j8]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: 7:1-7:2 (2020) - [c20]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: 125-136 - [i7]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 abs/2001.09249 (2020) - [i6]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 abs/2007.10987 (2020) - [i5]Annie Abay, Yi Zhou, Nathalie Baracaldo, Shashank Rajamoni, Ebube Chuba, Heiko Ludwig:
Mitigating Bias in Federated Learning. CoRR abs/2012.02447 (2020) - [i4]Yuya Jeremy Ong, Yi Zhou, Nathalie Baracaldo, Heiko Ludwig:
Adaptive Histogram-Based Gradient Boosted Trees for Federated Learning. CoRR abs/2012.06670 (2020)
2010 – 2019
- 2019
- [j7]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): 595-614 (2019) - [j6]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): 347-348 (2019) - [j5]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): 349-351 (2019) - [j4]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): 356-357 (2019) - [j3]Nathalie Baracaldo, Balaji Palanisamy, James Joshi:
G-SIR: An Insider Attack Resilient Geo-Social Access Control Framework. IEEE Trans. Dependable Secur. Comput. 16(1): 84-98 (2019) - [c19]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 - [c18]Judith Michael, Agnes Koschmider, Felix Mannhardt, Nathalie Baracaldo, Bernhard Rumpe:
User-Centered and Privacy-Driven Process Mining System Design for IoT. CAiSE Forum 2019: 194-206 - [c17]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: 1-11 - [c16]Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, Heiko Ludwig:
HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning. AISec@CCS 2019: 13-23 - [c15]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: 19:1-19:8 - [c14]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: 19-21 - [i3]Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, Heiko Ludwig:
HybridAlpha: An Efficient Approach for Privacy-Preserving Federated Learning. CoRR abs/1912.05897 (2019) - 2018
- [c13]Nathalie Baracaldo, Bryant Chen, Heiko Ludwig, Jaehoon Amir Safavi, Rui Zhang:
Detecting Poisoning Attacks on Machine Learning in IoT Environments. ICIOT 2018: 57-64 - [c12]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: 244-253 - [i2]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 abs/1811.03728 (2018) - [i1]Stacey Truex, Nathalie Baracaldo, Ali Anwar, Thomas Steinke, Heiko Ludwig, Rui Zhang:
A Hybrid Approach to Privacy-Preserving Federated Learning. CoRR abs/1812.03224 (2018) - 2017
- [j2]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): 1742003:1-1742003:29 (2017) - [c11]Nathalie Baracaldo, Bryant Chen, Heiko Ludwig, Jaehoon Amir Safavi:
Mitigating Poisoning Attacks on Machine Learning Models: A Data Provenance Based Approach. AISec@CCS 2017: 103-110 - 2016
- [c10]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: 85-91 - [c9]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: 92-98 - [c8]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: 265-266 - 2014
- [c7]Nathalie Baracaldo, Elli Androulaki, Joseph S. Glider, Alessandro Sorniotti:
Reconciling End-to-End Confidentiality and Data Reduction In Cloud Storage. CCSW 2014: 21-32 - [c6]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: xxxii-xxxv - [c5]Nathalie Baracaldo, Balaji Palanisamy, James B. D. Joshi:
Geo-Social-RBAC: A Location-Based Socially Aware Access Control Framework. NSS 2014: 501-509 - 2013
- [j1]Nathalie Baracaldo, James Joshi:
An adaptive risk management and access control framework to mitigate insider threats. Comput. Secur. 39: 237-254 (2013) - [c4]Nathalie Baracaldo, James Joshi:
Beyond accountability: using obligations to reduce risk exposure and deter insider attacks. SACMAT 2013: 213-224 - 2012
- [c3]Nathalie Baracaldo, James Joshi:
A trust-and-risk aware RBAC framework: tackling insider threat. SACMAT 2012: 167-176 - 2011
- [c2]Nathalie Baracaldo, Claudia A. López, Mohd Anwar, Michael Lewis:
Simulating the effect of privacy concerns in online social networks. IRI 2011: 519-524 - [c1]Nathalie Baracaldo, Amirreza Masoumzadeh, James Joshi:
A secure, constraint-aware role-based access control interoperation framework. NSS 2011: 200-207
Coauthor Index
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