Yue Zhao
Санкт-Петербургский государственный университет
- Anomaly Detection Techniques and Applications
- Network Security and Intrusion Detection
- Advanced Malware Detection Techniques
- Privacy-Preserving Technologies in Data
- Adversarial Robustness in Machine Learning
Чем занимается
Ключевые темы по публикациям: Anomaly Detection Techniques and Applications; Network Security and Intrusion Detection; Advanced Malware Detection Techniques; Privacy-Preserving Technologies in Data; Adversarial Robustness in Machine Learning.
Последние работы
Все 92 в OpenAlexFederated Learning with Non-IID Data2018 · аннотациясвернуть
Federated learning enables resource-constrained edge compute devices, such as mobile phones and IoT devices, to learn a shared model for prediction, while keeping the training data local. This decentralized approach to…
Federated Learning Based on Dynamic Regularization2021 · аннотациясвернуть
We propose a novel federated learning method for distributively training neural network models, where the server orchestrates cooperation between a subset of randomly chosen devices in each round. We view Federated…
- In vivo detection of microstructural correlates of brain pathology in preclinical and early Alzheimer Disease with magnetic resonance imaging2016
A Simple Recurrent Unit Model Based Intrusion Detection System With DCGAN2019 · аннотациясвернуть
Due to the complex and time-varying network environments, traditional methods are difficult to extract accurate features of intrusion behavior from the high-dimensional data samples and process the high-volume of these…
- Entropy-Weight-Method-Based Integrated Models for Short-Term Intersection Traffic Flow Prediction2022
- A branch selective kernel network based on slow features with interpretability for fault detection and diagnosis in chemical processes2025
- Language Strategies and Language Preferences in the Russian Tertiary Sector, the International Trade and the Impact of the One Belt One Road Initiative2025
- A panel quantile model via correlated random effects approach for testing pecking order theory2025
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Шаблон письма
Здравствуйте, Yue Zhao! Я студент(ка) [курс, факультет, вуз]. Мне интересна тема [опишите интересы своими словами]. Прочитал(а) вашу работу «Federated Learning with Non-IID Data» (2018) — она близка к тому, чем я хочу заниматься. Хочу обсудить возможность выполнить научную работу под вашим руководством. Буду благодарен(на) за ответ — готов(а) рассказать о себе подробнее и прислать резюме. С уважением, [Имя Фамилия]
На этапе теста письмо отправляешь сам из своей почты. Отправка из сервиса и статусы заявок — скоро.