activity
20172020
most citedCampus3D: A Photogrammetry Point Cloud Benchmark for Hierarchical Understanding of Outdoor Scene

57 citations · 74 across the 3 of their papers we have counts for

collaborators

6 papers

cs.LG2020

An Exponential Factorization Machine with Percentage Error Minimization to Retail Sales Forecasting

Chongshou Li, Brenda Cheang, Zhixing Luo +1

This paper proposes a new approach to sales forecasting for new products with long lead time but short product life cycle. These SKUs are usually sold for one season only, without…

cs.CV202057 cited

Campus3D: A Photogrammetry Point Cloud Benchmark for Hierarchical Understanding of Outdoor Scene

Xinke Li, Chongshou Li, Zekun Tong +5

Learning on 3D scene-based point cloud has received extensive attention as its promising application in many fields, and well-annotated and multisource datasets can catalyze the de…

cs.DS2020

Revisiting Modified Greedy Algorithm for Monotone Submodular Maximization with a Knapsack Constraint

Jing Tang, Xueyan Tang, Andrew Lim +3

Monotone submodular maximization with a knapsack constraint is NP-hard. Various approximation algorithms have been devised to address this optimization problem. In this paper, we r…

stat.AP2019

Deep Pattern of Time Series and Its Applications in Estimation, Forecasting, Fault Diagnosis and Target Tracking

Shixiong Wang, Chongshou Li, Andrew Lim

The information contained in a time series is more than what the values themselves are. In this paper, the Time-variant Local Autocorrelated Polynomial model with Kalman filter is…

stat.AP2019

Why Are the ARIMA and SARIMA not Sufficient

Shixiong Wang, Chongshou Li, Andrew Lim

The autoregressive moving average (ARMA) model takes the significant position in time series analysis for a wide-sense stationary time series. The difference operator and seasonal…

cs.CV201717 cited

WeText: Scene Text Detection under Weak Supervision

Shangxuan Tian, Shijian Lu, Chongshou Li

The requiring of large amounts of annotated training data has become a common constraint on various deep learning systems. In this paper, we propose a weakly supervised scene text…