42 citations · 59 across the 12 of their papers we have counts for
7 papers · 1 filter
StraightDP: Geometry-Aware Differential Privacy for Rectified-Flow Transformers
Xujun Che, Depeng Xu, Xintao Wu
Differentially private (DP) training of text-conditioned generative models suffers a utility cliff at strong privacy. We revisit this problem through the geometry of rectified flow…
Unlocking High-Fidelity Molecular Generation from Mass Spectra via Dual-Stream Line Graph Diffusion
Xujun Che, Xiuxia Du, Depeng Xu
De novo molecular generation from tandem mass spectra is a challenging inverse problem whose core difficulty lies in the circular dependency between atom-level and bond-level reaso…
Fine-grained Anomaly Detection in Sequential Data via Counterfactual Explanations
He Cheng, Depeng Xu, Shuhan Yuan +1
Anomaly detection in sequential data has been studied for a long time because of its potential in various applications, such as detecting abnormal system behaviors from log data. A…
Fairness-aware Agnostic Federated Learning
Wei Du, Depeng Xu, Xintao Wu +1
Federated learning is an emerging framework that builds centralized machine learning models with training data distributed across multiple devices. Most of the previous works about…
Removing Disparate Impact of Differentially Private Stochastic Gradient Descent on Model Accuracy
Depeng Xu, Wei Du, Xintao Wu
When we enforce differential privacy in machine learning, the utility-privacy trade-off is different w.r.t. each group. Gradient clipping and random noise addition disproportionate…
Achieving Differential Privacy in Vertically Partitioned Multiparty Learning
Depeng Xu, Shuhan Yuan, Xintao Wu
Preserving differential privacy has been well studied under centralized setting. However, it's very challenging to preserve differential privacy under multiparty setting, especiall…
FairGAN: Fairness-aware Generative Adversarial Networks
Depeng Xu, Shuhan Yuan, Lu Zhang +1
Fairness-aware learning is increasingly important in data mining. Discrimination prevention aims to prevent discrimination in the training data before it is used to conduct predict…