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Workshop
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Client-Private Secure Aggregation for Privacy-Preserving Federated Learning
Parker Newton · Olivia Choudhury · Bill Horne · Vidya Ravipati · Divya Bhargavi · Ujjwal Ratan
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Workshop
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Fri 14:20
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Invited Talk #5, Privacy-Preserving Data Synthesis for General Purposes, Bo Li
Bo Li
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Poster
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Tue 14:00
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DReS-FL: Dropout-Resilient Secure Federated Learning for Non-IID Clients via Secret Data Sharing
Jiawei Shao · Yuchang Sun · Songze Li · Jun Zhang
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Workshop
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Publicly Available Privacy-preserving Benchmarks for Polygenic Prediction
Menno Witteveen · Menno Witteveen
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Workshop
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Privacy-Preserving Data Filtering in Federated Learning Using Influence Approximation
Ljubomir Rokvic · Panayiotis Danassis · Boi Faltings
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Affinity Workshop
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Mon 7:10
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Oral Presentation 3: Privacy-Preserving Machine Learning for Collaborative Data Sharing via Auto-encoder Latent Space Embeddings
Ana María Quintero-Ossa
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Poster
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[Re] Privacy-preserving collaborative learning with automatic transformation search
Alfonso Taboada Warmerdam · Lodewijk Loerakker · Lucas Meijer · Ole Nissen
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Poster
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Tue 9:00
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Dataset Distillation using Neural Feature Regression
Yongchao Zhou · Ehsan Nezhadarya · Jimmy Ba
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Workshop
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Privacy-Preserving Group Fairness in Cross-Device Federated Learning
Sikha Pentyala · Nicola Neophytou · Anderson Nascimento · Martine De Cock · Golnoosh Farnadi
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Affinity Workshop
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Privacy-Preserving Machine Learning for Collaborative Data Sharing via Auto-encoder Latent Space Embeddings
Ana María Quintero-Ossa · Jesus Solano · Hernan Garcia · David Zarruk · Alejandro Bahnsen · Carlos Valencia
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Affinity Workshop
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Privacy-Preserving Online Mirror Descent With Single-Sided Trust for Federated Learning
Olusola Odeyomi · Gergely Zaruba
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Poster
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Wed 14:00
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Differentially Private Covariance Revisited
Wei Dong · Yuting Liang · Ke Yi
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