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02/07/2022
Deletion Inference, Reconstruction, and Compliance in Machine (Un)Learning
Privacy attacks on machine learning models aim to identify the data that...
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05/18/2021
Learning and Certification under Instance-targeted Poisoning
In this paper, we study PAC learnability and certification under instanc...
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03/21/2018
Exploring the Naturalness of Buggy Code with Recurrent Neural Networks
Statistical language models are powerful tools which have been used for ...
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01/13/2018
Black-box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers
Although various techniques have been proposed to generate adversarial s...
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02/22/2017
DeepCloak: Masking Deep Neural Network Models for Robustness Against Adversarial Samples
Recent studies have shown that deep neural networks (DNN) are vulnerable...
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02/09/2017
A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models
Estimating multiple sparse Gaussian Graphical Models (sGGMs) jointly for...
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12/01/2016
