Xiaolong Li

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. …

Analysis of Intensive Utilization Potential of Industrial Land at Enterprise Scale

2018

Industrial land is an important part of urban resources, and extensive development can seriously hinder the process of urbanization. In order to meet the demand for larger-scale and higher-quality urban economic growth using limited land …

A Hybrid Deep Learning and Handcrafted Features based Approach for Thyroid Nodule Classification in Ultrasound Images

2020 · Journal of Physics Conference Series

Abstract With the increasing incidence rate of thyroid cancer, the diagnosis of thyroid nodules has become an important task. In this paper, we designed a deep neural network (DNN) to classify whether a thyroid nodule …

ToolExpNet: Optimizing Multi-Tool Selection in LLMs with Similarity and Dependency-Aware Experience Networks

2025

Tool learning enhances Large Language Models' (LLMs) dynamic interaction with external tools, improving their ability to solve complex problems.However, current empirical methods, which primarily focus on isolated tools learning, still struggle with accurate multi-tool selection …

cw2vec: Learning Chinese Word Embeddings with Stroke n-gram Information

2018 · Proceedings of the AAAI Conference on Artificial Intelligence

We propose cw2vec, a novel method for learning Chinese word embeddings. It is based on our observation that exploiting stroke-level information is crucial for improving the learning of Chinese word embeddings. Specifically, we design a …

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 …