Search Results for author: Xinli Yu

Found 6 papers, 0 papers with code

Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting

no code implementations19 Jun 2023 Xinli Yu, Zheng Chen, Yuan Ling, Shujing Dong, Zongyi Liu, Yanbin Lu

The application of machine learning models to financial time series comes with several challenges, including the difficulty in cross-sequence reasoning and inference, the hurdle of incorporating multi-modal signals from historical news, financial knowledge graphs, etc., and the issue of interpreting and explaining the model results.

Knowledge Graphs Time Series +1

Video Moment Retrieval via Natural Language Queries

no code implementations4 Sep 2020 Xinli Yu, Mohsen Malmir, Cynthia He, Yue Liu, Rex Wu

However, the inference time will not be a problem for our model since our model has a simple architecture which enables efficient training and inference.

Moment Retrieval Natural Language Queries +1

Neural Stochastic Block Model & Scalable Community-Based Graph Learning

no code implementations16 May 2020 Zheng Chen, Xinli Yu, Yuan Ling, Xiaohua Hu

Compared with SBM, our framework is flexible, naturally allows soft labels and digestion of complex node attributes.

Community Detection Graph Attention +3

Large-Scale Joint Topic, Sentiment & User Preference Analysis for Online Reviews

no code implementations14 Jan 2019 Xinli Yu, Zheng Chen, Wei-Shih Yang, Xiaohua Hu, Erjia Yan

This paper presents a non-trivial reconstruction of a previous joint topic-sentiment-preference review model TSPRA with stick-breaking representation under the framework of variational inference (VI) and stochastic variational inference (SVI).

Variational Inference

Fast Botnet Detection From Streaming Logs Using Online Lanczos Method

no code implementations19 Dec 2018 Zheng Chen, Xinli Yu, Chi Zhang, Jin Zhang, Cui Lin, Bo Song, Jianliang Gao, Xiaohua Hu, Wei-Shih Yang, Erjia Yan

Botnet, a group of coordinated bots, is becoming the main platform of malicious Internet activities like DDOS, click fraud, web scraping, spam/rumor distribution, etc.

Correlated Anomaly Detection from Large Streaming Data

no code implementations19 Dec 2018 Zheng Chen, Xinli Yu, Yuan Ling, Bo Song, Wei Quan, Xiaohua Hu, Erjia Yan

Correlated anomaly detection (CAD) from streaming data is a type of group anomaly detection and an essential task in useful real-time data mining applications like botnet detection, financial event detection, industrial process monitor, etc.

Event Detection Group Anomaly Detection

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