Yang Cao
12 papers in the PaperMetrix corpus
Papers by this author
-
A Sensitive Words Filtering Model Based on Web Text Features
2018 · Proceedings of the 2018 2nd International Conference on Computer Science and Artificial Intelligence
The false advertising of food and drag on the Internet is mainly based on the content of the product website promotion pages. When people browse a website, they get the most parts of the information …
-
Understanding the Interplay between Privacy and Robustness in Federated Learning
2021 · arXiv (Cornell University)
Federated Learning (FL) is emerging as a promising paradigm of privacy-preserving machine learning, which trains an algorithm across multiple clients without exchanging their data samples. Recent works highlighted several privacy and robustness weaknesses in FL …
-
An abnormal user login behavior detection method of industrial control system based on multi-dimensional probability analysis
2022 · Journal of Physics Conference Series
Abstract Aiming at the poor detection performance of user abnormal login behavior in the complex environment of industrial control system, a new method based on multi-dimensional probability analysis is proposed. First of all, login time, …
-
Locally Private Streaming Data Release with Shuffling and Subsampling
2023
Longitudinal data collection is an important task for real-time data analysts in this Big Data Era. However, the continual observation of raw data may leak user’s sensitive information. Local differential privacy is a rigorous privacy-preserving …
-
A Generalized Shuffle Framework for Privacy Amplification: Strengthening Privacy Guarantees and Enhancing Utility
2023 · arXiv (Cornell University)
The shuffle model of local differential privacy is an advanced method of privacy amplification designed to enhance privacy protection with high utility. It achieves this by randomly shuffling sensitive data, making linking individual data points …
-
Phantom in the opera: adversarial music attack for robot dialogue system
2024 · Frontiers in Computer Science
This study explores the vulnerability of robot dialogue systems' automatic speech recognition (ASR) module to adversarial music attacks. Specifically, we explore music as a natural camouflage for such attacks. We propose a novel method to …
-
Differentially Private Federated Learning: A Systematic Review
2024 · arXiv (Cornell University)
In recent years, privacy and security concerns in machine learning have promoted trusted federated learning to the forefront of research. Differential privacy has emerged as the de facto standard for privacy protection in federated learning …
-
MMAR: Towards Lossless Multi-Modal Auto-Regressive Probabilistic Modeling
2024 · arXiv (Cornell University)
Recent advancements in multi-modal large language models have propelled the development of joint probabilistic models capable of both image understanding and generation. However, we have identified that recent methods suffer from loss of image information …
-
Smart Grid Data Security Sharing Based on Cloud-Edge Collaboration
2025
In recent years, the rapid advancement of smart terminals and wireless networks has led to exponential growth in the number of powers of IoT devices and the volume of data. These data resources have become …
-
xMTF: A Formula-Free Model for Reinforcement-Learning-Based Multi-Task Fusion in Recommender Systems
2025 · arXiv (Cornell University)
Recommender systems need to optimize various types of user feedback, e.g., clicks, likes, and shares. A typical recommender system handling multiple types of feedback has two components: a multi-task learning (MTL) module, predicting feedback such …
-
IdeFN: Identifying Unclicked Space False Negatives via Relaxed Partial Optimal Transport for Conversion Rate Prediction
2026 · Proceedings of the AAAI Conference on Artificial Intelligence
Accurate conversion rate (CVR) prediction is critical for recommender systems to capture user conversion intent and increase platform revenues. Traditional CVR models commonly suffer from sample selection bias (SSB) and data sparsity (DS), which has …
-
Personalized Recommendation System Based on Collaborative Filtering for IoT Scenarios
2020 · IEEE Transactions on Services Computing
Recommendation technology is an important part of the Internet of Things (IoT) services, which can provide better service for users and help users get information anytime, anywhere. However, the traditional recommendation algorithms cannot meet user's …