Ziqi Liu

Feature Propagation on Graph: A New Perspective to Graph Representation Learning

2018 · arXiv (Cornell University)

We study feature propagation on graph, an inference process involved in graph representation learning tasks. It's to spread the features over the whole graph to the $t$-th orders, thus to expand the end's features. The …

Distributed Deep Forest and its Application to Automatic Detection of Cash-out Fraud

2018 · arXiv (Cornell University)

Internet companies are facing the need for handling large-scale machine learning applications on a daily basis and distributed implementation of machine learning algorithms which can handle extra-large scale tasks with great performance is widely needed. …

Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing

2019

Mobile payment such as Alipay has been widely used in our daily lives. To further promote the mobile payment activities, it is important to run marketing campaigns under a limited budget by providing incentives such …

Graph Representation Learning for Merchant Incentive Optimization in Mobile Payment Marketing

2020 · arXiv (Cornell University)

Mobile payment such as Alipay has been widely used in our daily lives. To further promote the mobile payment activities, it is important to run marketing campaigns under a limited budget by providing incentives such …

Can Small Language Models be Good Reasoners for Sequential Recommendation?

2024 · arXiv (Cornell University)

Large language models (LLMs) open up new horizons for sequential recommendations, owing to their remarkable language comprehension and generation capabilities. However, there are still numerous challenges that should be addressed to successfully implement sequential recommendations …

Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts

2024 · arXiv (Cornell University)

In recent years, large language models (LLMs) have made remarkable achievements in various domains. However, the untimeliness and cost of knowledge updates coupled with hallucination issues of LLMs have curtailed their applications in knowledge intensive …

Ultra-Short-Term Power Forecasting for Distributed PV based on Multi-Source Remote Sensing Information and Adaptive Feature Extraction

2024

The lack of meteorological data for distributed photovoltaic (DPV) makes it impossible to incorporate meteorological information sources highly related to PV output into power forecasting model, which limits the further improvement of forecasting accuracy. Therefore, …

Privacy Preserving Point-of-Interest Recommendation Using Decentralized Matrix Factorization

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

Points of interest (POI) recommendation has been drawn much attention recently due to the increasing popularity of location-based networks, e.g., Foursquare and Yelp. Among the existing approaches to POI recommendation, Matrix Factorization (MF) based techniques …