Zilong Zhao | DeepAI

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Featured Co-authors

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∙ 02/03/2023

GTV: Generating Tabular Data via Vertical Federated Learning

Generative Adversarial Networks (GANs) have achieved state-of-the-art re...

0 Zilong Zhao, et al. ∙

∙ 11/17/2022

Permutation-Invariant Tabular Data Synthesis

Tabular data synthesis is an emerging approach to circumvent strict regu...

0 Yujin Zhu, et al. ∙

∙ 10/13/2022

Federated Learning for Tabular Data: Exploring Potential Risk to Privacy

Federated Learning (FL) has emerged as a potentially powerful privacy-pr...

0 Han Wu, et al. ∙

∙ 10/12/2022

FCT-GAN: Enhancing Table Synthesis via Fourier Transform

Synthetic tabular data emerges as an alternative for sharing knowledge w...

0 Zilong Zhao, et al. ∙

∙ 10/11/2022

UGformer for Robust Left Atrium and Scar Segmentation Across Scanners

Thanks to the capacity for long-range dependencies and robustness to irr...

0 Tianyi Liu, et al. ∙

∙ 04/01/2022

CTAB-GAN+: Enhancing Tabular Data Synthesis

While data sharing is crucial for knowledge development, privacy concern...

0 Zilong Zhao, et al. ∙

∙ 02/07/2022

Blind leads Blind: A Zero-Knowledge Attack on Federated Learning

Attacks on Federated Learning (FL) can severely reduce the quality of th...

0 Jiyue Huang, et al. ∙

∙ 01/24/2022

Attacks and Defenses for Free-Riders in Multi-Discriminator GAN

Generative Adversarial Networks (GANs) are increasingly adopted by the i...

0 Zilong Zhao, et al. ∙

∙ 09/19/2021

ComicGAN: Text-to-Comic Generative Adversarial Network

Drawing and annotating comic illustrations is a complex and difficult pr...

23 Ben Proven-Bessel, et al. ∙

∙ 08/18/2021

Fed-TGAN: Federated Learning Framework for Synthesizing Tabular Data

Generative Adversarial Networks (GANs) are typically trained to synthesi...

0 Zilong Zhao, et al. ∙

∙ 07/06/2021

DTGAN: Differential Private Training for Tabular GANs

Tabular generative adversarial networks (TGAN) have recently emerged to ...

0 Aditya Kunar, et al. ∙

∙ 03/19/2021

Enhancing Robustness of On-line Learning Models on Highly Noisy Data

Classification algorithms have been widely adopted to detect anomalies f...

14 Zilong Zhao, et al. ∙

∙ 02/16/2021

CTAB-GAN: Effective Table Data Synthesizing

While data sharing is crucial for knowledge development, privacy concern...

0 Zilong Zhao, et al. ∙

∙ 11/13/2020

An Exploratory Analysis on Users' Contributions in Federated Learning

Federated Learning is an emerging distributed collaborative learning par...

0 Jiyue Huang, et al. ∙

∙ 03/20/2020

Event-Based Control for Online Training of Neural Networks

Convolutional Neural Network (CNN) has become the most used method for i...

0 Zilong Zhao, et al. ∙

∙ 01/28/2020

QActor: On-line Active Learning for Noisy Labeled Stream Data

Noisy labeled data is more a norm than a rarity for self-generated conte...

0 Taraneh Younesian, et al. ∙

∙ 11/18/2019

Feedback Control for Online Training of Neural Networks

Convolutional neural networks (CNNs) are commonly used for image classif...

0 Zilong Zhao, et al. ∙

∙ 11/11/2019

RAD: On-line Anomaly Detection for Highly Unreliable Data

Classification algorithms have been widely adopted to detect anomalies f...

0 Zilong Zhao, et al. ∙

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