3 citations · 3 across the 4 of their papers we have counts for
4 papers
Estimating the Density Ratio between Distributions with High Discrepancy using Multinomial Logistic Regression
Akash Srivastava, Seungwook Han, Kai Xu +2
Functions of the ratio of the densities are widely used in machine learning to quantify the discrepancy between the two distributions and . For high-dimensional distri…
HybridGNN: Learning Hybrid Representation in Multiplex Heterogeneous Networks
Tiankai Gu, Chaokun Wang, Cheng Wu +6
Recently, graph neural networks have shown the superiority of modeling the complex topological structures in heterogeneous network-based recommender systems. Due to the diverse int…
Repairing Systematic Outliers by Learning Clean Subspaces in VAEs
Simao Eduardo, Kai Xu, Alfredo Nazabal +1
Data cleaning often comprises outlier detection and data repair. Systematic errors result from nearly deterministic transformations that occur repeatedly in the data, e.g. specific…
dpart: Differentially Private Autoregressive Tabular, a General Framework for Synthetic Data Generation
Sofiane Mahiou, Kai Xu, Georgi Ganev
We propose a general, flexible, and scalable framework dpart, an open source Python library for differentially private synthetic data generation. Central to the approach is autoreg…