53 citations · 78 across the 11 of their papers we have counts for
10 papers · 1 filter
A Geometry-Aware Algorithm to Learn Hierarchical Embeddings in Hyperbolic Space
Zhangyu Wang, Lantian Xu, Zhifeng Kong +3
Hyperbolic embeddings are a class of representation learning methods that offer competitive performances when data can be abstracted as a tree-like graph. However, in practice, lea…
Data Redaction from Conditional Generative Models
Zhifeng Kong, Kamalika Chaudhuri
Deep generative models are known to produce undesirable samples such as harmful content. Traditional mitigation methods include re-training from scratch, filtering, or editing; how…
Can Membership Inferencing be Refuted?
Zhifeng Kong, Amrita Roy Chowdhury, Kamalika Chaudhuri
Membership inference (MI) attack is currently the most popular test for measuring privacy leakage in machine learning models. Given a machine learning model, a data point and some…
Approximate Data Deletion in Generative Models
Zhifeng Kong, Scott Alfeld
Users have the right to have their data deleted by third-party learned systems, as codified by recent legislation such as the General Data Protection Regulation (GDPR) and the Cali…
Data Redaction from Pre-trained GANs
Zhifeng Kong, Kamalika Chaudhuri
Large pre-trained generative models are known to occasionally output undesirable samples, which undermines their trustworthiness. The common way to mitigate this is to re-train the…
On Fast Sampling of Diffusion Probabilistic Models
Zhifeng Kong, Wei Ping
In this work, we propose FastDPM, a unified framework for fast sampling in diffusion probabilistic models. FastDPM generalizes previous methods and gives rise to new algorithms wit…