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Thompson Sampling for Robust Transfer in Multi-Task Bandits



Zhi Wang , Chicheng Zhang , Kamalika Chaudhuri

* To appear in Proceedings of the 39th International Conference on Machine Learning (ICML-2022) 

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A Learning-Theoretic Framework for Certified Auditing of Machine Learning Models



Chhavi Yadav , Michal Moshkovitz , Kamalika Chaudhuri


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Throwing Away Data Improves Worst-Class Error in Imbalanced Classification



Martin Arjovsky , Kamalika Chaudhuri , David Lopez-Paz


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Sentence-level Privacy for Document Embeddings



Casey Meehan , Khalil Mrini , Kamalika Chaudhuri

* Presented at ACL 2022 main conference 

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Privacy-Aware Compression for Federated Data Analysis



Kamalika Chaudhuri , Chuan Guo , Mike Rabbat


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Understanding Rare Spurious Correlations in Neural Networks



Yao-Yuan Yang , Kamalika Chaudhuri


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Bounding Training Data Reconstruction in Private (Deep) Learning



Chuan Guo , Brian Karrer , Kamalika Chaudhuri , Laurens van der Maaten


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Privacy Amplification by Subsampling in Time Domain



Tatsuki Koga , Casey Meehan , Kamalika Chaudhuri


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Privacy Amplification via Shuffling for Linear Contextual Bandits



Evrard Garcelon , Kamalika Chaudhuri , Vianney Perchet , Matteo Pirotta


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Behavior of k-NN as an Instance-Based Explanation Method



Chhavi Yadav , Kamalika Chaudhuri


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