Sai Wu

A Comparative Study of in-Database Inference Approaches

2022 · 2022 IEEE 38th International Conference on Data Engineering (ICDE)

In Alibaba's IoT platform, we face the challenge of processing analytical queries involving both structured and unstructured data. Normally, collaborative queries need deep learning (DL) models and relational algebras to work intertwined to produce sophisticated …

Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting

2023 · arXiv (Cornell University)

Federated learning has exhibited vulnerabilities to Byzantine attacks, where the Byzantine attackers can send arbitrary gradients to a central server to destroy the convergence and performance of the global model. A wealth of robust AGgregation …

Assessing Hidden Risks of LLMs: An Empirical Study on Robustness, Consistency, and Credibility

2023 · arXiv (Cornell University)

The recent popularity of large language models (LLMs) has brought a significant impact to boundless fields, particularly through their open-ended ecosystem such as the APIs, open-sourced models, and plugins. However, with their widespread deployment, there …

Personal recommendation using deep recurrent neural networks in NetEase

2016

Each user session in an e-commerce system can be modeled as a sequence of web pages, indicating how the user interacts with the system and makes his/her purchase. A typical recommendation approach, e.g., Collaborative Filtering, …