Zhiwei Xu

Machine Learning Computers With Fractal von Neumann Architecture

2020 · IEEE Transactions on Computers

Machine learning techniques are pervasive tools for emerging commercial applications and many dedicated machine learning computers on different scales have been deployed in embedded devices, servers, and data centers. Currently, most machine learning computer architectures …

Self-supervised Image Clustering from Multiple Incomplete Views via Constrastive Complementary Generation

2022 · arXiv (Cornell University)

Incomplete Multi-View Clustering aims to enhance clustering performance by using data from multiple modalities. Despite the fact that several approaches for studying this issue have been proposed, the following drawbacks still persist: 1) It's difficult …

Adversarial Purification with the Manifold Hypothesis

2024 · Proceedings of the AAAI Conference on Artificial Intelligence

In this work, we formulate a novel framework for adversarial robustness using the manifold hypothesis. This framework provides sufficient conditions for defending against adversarial examples. We develop an adversarial purification method with this framework. Our …

Consensus-Based Decentralized Federated Learning for Model Training Services in IoV

2025

With the rapid development of the Internet of Vehicles (IoV), massive amounts of distributed data are continuously generated, raising critical challenges in ensuring service reliability and security. Federated Learning (FL) has emerged as a promising …

Graph of Verification: Structured Verification of LLM Reasoning with Directed Acyclic Graphs

2025 · arXiv (Cornell University)

Verifying the complex and multi-step reasoning of Large Language Models (LLMs) is a critical challenge, as holistic methods often overlook localized flaws. Step-by-step validation is a promising alternative, yet existing methods are often rigid. They …