activity
20172020
most citedDeepTrend: A Deep Hierarchical Neural Network for Traffic Flow Prediction

45 citations · 50 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG20204 cited

Improving Federated Relational Data Modeling via Basis Alignment and Weight Penalty

Yilun Lin, Chaochao Chen, Cen Chen +1

Federated learning (FL) has attracted increasing attention in recent years. As a privacy-preserving collaborative learning paradigm, it enables a broader range of applications, esp…

cs.RO20201 cited

GPO: Global Plane Optimization for Fast and Accurate Monocular SLAM Initialization

Sicong Du, Hengkai Guo, Yao Chen +4

Initialization is essential to monocular Simultaneous Localization and Mapping (SLAM) problems. This paper focuses on a novel initialization method for monocular SLAM based on plan…

cs.HC2019

Not at Home on the Range: Peer Production and the Urban/Rural Divide

Isaac Johnson, Allen Yilun Lin, Toby Jia-Jun Li +4

Wikipedia articles about places, OpenStreetMap features, and other forms of peer-produced content have become critical sources of geographic knowledge for humans and intelligent te…

cs.AI2018

An Efficient Deep Reinforcement Learning Model for Urban Traffic Control

Yilun Lin, Xingyuan Dai, Li Li +1

Urban Traffic Control (UTC) plays an essential role in Intelligent Transportation System (ITS) but remains difficult. Since model-based UTC methods may not accurately describe the…

cs.LG201745 cited

DeepTrend: A Deep Hierarchical Neural Network for Traffic Flow Prediction

Xingyuan Dai, Rui Fu, Yilun Lin +2

In this paper, we consider the temporal pattern in traffic flow time series, and implement a deep learning model for traffic flow prediction. Detrending based methods decompose ori…