16 citations · 38 across the 12 of their papers we have counts for
4 papers · 1 filter
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…
DropIT: Dropping Intermediate Tensors for Memory-Efficient DNN Training
Joya Chen, Kai Xu, Yuhui Wang +2
A standard hardware bottleneck when training deep neural networks is GPU memory. The bulk of memory is occupied by caching intermediate tensors for gradient computation in the back…
Decoupling Makes Weakly Supervised Local Feature Better
Kunhong Li, Longguang Wang, Li Liu +3
Weakly supervised learning can help local feature methods to overcome the obstacle of acquiring a large-scale dataset with densely labeled correspondences. However, since weak supe…