7 papers
An Expectation-Maximization Relaxed Method for Privacy Funnel
Lingyi Chen, Jiachuan Ye, Shitong Wu +3
The privacy funnel (PF) gives a framework of privacy-preserving data release, where the goal is to release useful data while also limiting the exposure of associated sensitive info…
A Double Maximization Approach for Optimizing the LM Rate of Mismatched Decoding
Lingyi Chen, Shitong Wu, Xinwei Li +3
An approach is established for maximizing the Lower bound on the Mismatch capacity (hereafter abbreviated as LM rate), a key performance bound in mismatched decoding, by optimizing…
On Convergence of Discrete Schemes for Computing the Rate-Distortion Function of Continuous Source
Lingyi Chen, Shitong Wu, Wenyi Zhang +2
Computing the rate-distortion function for continuous sources is commonly regarded as a standard continuous optimization problem. When numerically addressing this problem, a typica…
Efficient and Provably Convergent Computation of Information Bottleneck: A Semi-Relaxed Approach
Lingyi Chen, Shitong Wu, Jiachuan Ye +3
Information Bottleneck (IB) is a technique to extract information about one target random variable through another relevant random variable. This technique has garnered significant…
Information Bottleneck Revisited: Posterior Probability Perspective with Optimal Transport
Lingyi Chen, Shitong Wu, Wenhao Ye +5
Information bottleneck (IB) is a paradigm to extract information in one target random variable from another relevant random variable, which has aroused great interest due to its po…
Computation of Rate-Distortion-Perception Functions With Wasserstein Barycenter
Chunhui Chen, Xueyan Niu, Wenhao Ye +4
The nascent field of Rate-Distortion-Perception (RDP) theory is seeing a surge of research interest due to the application of machine learning techniques in the area of lossy compr…