2 citations · 6 across the 7 of their papers we have counts for
13 papers
PADDLES: Phase-Amplitude Spectrum Disentangled Early Stopping for Learning with Noisy Labels
Huaxi Huang, Hui Kang, Sheng Liu +4
Convolutional Neural Networks (CNNs) have demonstrated superiority in learning patterns, but are sensitive to label noises and may overfit noisy labels during training. The early s…
Enhancing Utility in the Watchdog Privacy Mechanism
Mohammad Amin Zarrabian, Ni Ding, Parastoo Sadeghi +1
This paper is concerned with enhancing data utility in the privacy watchdog method for attaining information-theoretic privacy. For a specific privacy constraint, the watchdog meth…
Realistic Differentially-Private Transmission Power Flow Data Release
David Smith, Frederik Geth, Elliott Vercoe +5
For the modeling, design and planning of future energy transmission networks, it is vital for stakeholders to access faithful and useful power flow data, while provably maintaining…
On Properties and Optimization of Information-theoretic Privacy Watchdog
Parastoo Sadeghi, Ni Ding, Thierry Rakotoarivelo
We study the problem of privacy preservation in data sharing, where is a sensitive variable to be protected and is a non-sensitive useful variable correlated with . Vari…
Privacy-Utility Tradeoff in a Guessing Framework Inspired by Index Coding
Yucheng Liu, Ni Ding, Parastoo Sadeghi +1
This paper studies the tradeoff in privacy and utility in a single-trial multi-terminal guessing (estimation) framework using a system model that is inspired by index coding. There…
Part II: A Practical Approach for Successive Omniscience
Ni Ding, Parastoo Sadeghi, Thierry Rakotoarivelo
In Part I, we studied the communication for omniscience (CO) problem and proposed a parametric (PAR) algorithm to determine the minimum sum-rate at which a set of users indexed by…