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Workshop
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Position: Challenges and Opportunities for Differential Privacy in the U.S. Federal Government
Amol Khanna · Adam Mccormick · Andre Nguyen · Christopher Aguirre · Edward Raff
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Poster
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Wed 16:30
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Differentially Private Optimization with Sparse Gradients
Badih Ghazi · Cristóbal Guzmán · Pritish Kamath · Ravi Kumar · Pasin Manurangsi
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Poster
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Thu 16:30
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Attack-Aware Noise Calibration for Differential Privacy
Bogdan Kulynych · Juan Gomez · Georgios Kaissis · Flavio Calmon · Carmela Troncoso
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Poster
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Wed 16:30
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A Huber Loss Minimization Approach to Mean Estimation under User-level Differential Privacy
Puning Zhao · Lifeng LAI · Li Shen · Qingming Li · Jiafei Wu · Zhe Liu
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Workshop
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Decreasing Inconsistencies in Differentially Private Language Models through Self-Distillation
Kieleh Ngong Ivoline Clarisse · Joseph Near · Niloofar Mireshghallah
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Workshop
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A Cautionary Tale on the Evaluation of Differentially Private In-Context Learning
Anjun Hu · Jiyang Guan · Philip Torr · Francesco Pinto
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Poster
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Thu 11:00
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Noise-Aware Differentially Private Regression via Meta-Learning
Ossi Räisä · Stratis Markou · Matthew Ashman · Wessel Bruinsma · Marlon Tobaben · Antti Honkela · Richard Turner
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Poster
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Wed 16:30
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Differential Privacy in Scalable General Kernel Learning via K-means Nystr{\"o}m Random Features
Bonwoo Lee · Jeongyoun Ahn · Cheolwoo Park
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Poster
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Wed 16:30
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Exactly Minimax-Optimal Locally Differentially Private Sampling
Hyun-Young Park · Shahab Asoodeh · Si-Hyeon Lee
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Affinity Event
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Towards Privacy-Preserving Medical Imaging: Federated Learning with Differential Privacy and Secure Aggregation Using a Modified ResNet Architecture
Mohamad Haj Fares · Ahmed Mohamed Saad Emam Saad
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Workshop
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Sat 15:45
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Privately Learning from Graphs with Applications in Fine-tuning Large Pretrained Models
Haoteng YIN · Rongzhe Wei · Eli Chien · Pan Li
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