Privacy preserving probabilistic inference with Hidden Markov Models

By Manas A. Pathak, Shantanu D. Rane, Wei Sun, Bhiksha Raj. 2011

50 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Probabilistic & Bayesian Methods, Privacy & Security

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Reza Shokri
2. Vitaly Shmatikov
3. Prateek Mittal
4. Congzheng Song
5. Liwei Song
6. Lingjuan Lyu
7. Yang Zhang
8. Nicolas Papernot

In Probabilistic & Bayesian Methods

1. Vitaly Shmatikov
2. Reza Shokri

In Privacy & Security

1. Reza Shokri
2. Vitaly Shmatikov
3. Arjun Narayan
4. Aleksandra Korolova
5. Manas A. Pathak

Citations in the corpus

• Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (2016, neutral): “Attempts to provide differential privacy for machine learning models led to a series of efforts on shallow machine learning models, including work by Bassily et al. (2014); Chaudhuri & Monteleoni (2009); Pathak et al. (2011); Song et al. (2013), and Wainwright et al. (2012).”
• Privacy-preserving deep learning (2015, background): “Techniques that protect privacy of the model include privacypreserving probabilistic inference [38], privacy-preserving speaker identification [36], and computing on encrypted data [3, 6, 55].”