Yuan Yang

Convergence Analysis of Two-layer Neural Networks with ReLU Activation

2017 · arXiv (Cornell University)

In recent years, stochastic gradient descent (SGD) based techniques has become the standard tools for training neural networks. However, formal theoretical understanding of why SGD can train neural networks in practice is largely missing. In …

Secure Data Sharing With Flow Model

2020 · arXiv (Cornell University)

In the classical multi-party computation setting, multiple parties jointly compute a function without revealing their own input data. We consider a variant of this problem, where the input data can be shared for machine learning …

Research on Object Detection Method of Four-Electric Equipment in Rail Transit Based on Yolo

2022 · 2022 International Conference on Image Processing, Computer Vision and Machine Learning (ICICML)

Rail transit is a complex system, there will always be a variety of errors in the actual project to bring unnecessary losses. This research aims to increase users’ understanding of equipment by detecting the types …

Weakly supervised deep learning-based classification for histopathology of gliomas: a single center experience

2025 · Scientific Reports

Multiple artificial intelligence systems have been created to facilitate accurate and prompt histopathological diagnosis of tumors using hematoxylin-eosin-stained slides. We aimed to investigate whether weakly supervised deep learning can aid in glioma diagnosis. We analyzed …

Distributed Nesterov Gradient for Differentially Private Optimization with Exact Convergence

2024

Differentially-private distributed optimization algorithms can preserve the private gradient but bring unavoidable trade-off between privacy and optimality. Some methods have been studied to address this based on diminishing stepsize with only sublinear convergence. To improve …