activity
20172023
most citedA Survey on ML4VIS: Applying Machine Learning Advances to Data Visualization

120 citations · 1.5k across the 58 of their papers we have counts for

collaborators
Showing 2020Show all

19 papers · 1 filter

cs.HC2020★ 120 cited

A Survey on ML4VIS: Applying Machine Learning Advances to Data Visualization

Qianwen Wang, Zhutian Chen, Yong Wang +1

Inspired by the great success of machine learning (ML), researchers have applied ML techniques to visualizations to achieve a better design, development, and evaluation of visualiz…

cs.HC2020★ 6 cited

GNNLens: A Visual Analytics Approach for Prediction Error Diagnosis of Graph Neural Networks

Zhihua Jin, Yong Wang, Qianwen Wang +3

Graph Neural Networks (GNNs) aim to extend deep learning techniques to graph data and have achieved significant progress in graph analysis tasks (e.g., node classification) in rece…

cs.HC2020★ 2 cited

QLens: Visual Analytics of Multi-step Problem-solving Behaviors for Improving Question Design

Meng Xia, Reshika Palaniyappan Velumani, Yong Wang +2

With the rapid development of online education in recent years, there has been an increasing number of learning platforms that provide students with multi-step questions to cultiva…

cs.HC2020★ 4 cited

Improving Engagement of Animated Visualization with Visual Foreshadowing

Wenchao Li, Yun Wang, Haidong Zhang +1

Animated visualization is becoming increasingly popular as a compelling way to illustrate changes in time series data. However, maintaining the viewer's focus throughout the entire…

cs.HC2020★ 1 cited

What Makes a Data-GIF Understandable?

Xinhuan Shu, Aoyu Wu, Junxiu Tang +3

GIFs are enjoying increasing popularity on social media as a format for data-driven storytelling with visualization; simple visual messages are embedded in short animations that us…

cs.HC2020★ 2 cited

TaxThemis: Interactive Mining and Exploration of Suspicious Tax Evasion Group

Yating Lin, Kamkwai Wong, Yong Wang +4

Tax evasion is a serious economic problem for many countries, as it can undermine the government' s tax system and lead to an unfair business competition environment. Recent resear…

cs.HC2020★ 1 cited

TradAO: A Visual Analytics System for Trading Algorithm Optimization

Ka Wing Tsang, Haotian Li, Fuk Ming Lam +3

With the wide applications of algorithmic trading, it has become critical for traders to build a winning trading algorithm to beat the market. However, due to the lack of efficient…

cs.LG2020★ 11 cited

DECE: Decision Explorer with Counterfactual Explanations for Machine Learning Models

Furui Cheng, Yao Ming, Huamin Qu

With machine learning models being increasingly applied to various decision-making scenarios, people have spent growing efforts to make machine learning models more transparent and…

cs.HC2020★ 3 cited

MobileVisFixer: Tailoring Web Visualizations for Mobile Phones Leveraging an Explainable Reinforcement Learning Framework

Aoyu Wu, Wai Tong, Tim Dwyer +3

We contribute MobileVisFixer, a new method to make visualizations more mobile-friendly. Although mobile devices have become the primary means of accessing information on the web, m…

cs.LG2020★ 32 cited

Peer-inspired Student Performance Prediction in Interactive Online Question Pools with Graph Neural Network

Haotian Li, Huan Wei, Yong Wang +2

Student performance prediction is critical to online education. It can benefit many downstream tasks on online learning platforms, such as estimating dropout rates, facilitating st…

cs.HC2020★ 49 cited

Topology Density Map for Urban Data Visualization and Analysis

Zezheng Feng, Haotian Li, Wei Zeng +2

Density map is an effective visualization technique for depicting the scalar field distribution in 2D space. Conventional methods for constructing density maps are mainly based on…

cs.HC2020★ 56 cited

Visual Analysis of Discrimination in Machine Learning

Qianwen Wang, Zhenhua Xu, Zhutian Chen +3

The growing use of automated decision-making in critical applications, such as crime prediction and college admission, has raised questions about fairness in machine learning. How…

cs.HC2020★ 1 cited

ICE: Identify and Compare Event Sequence Sets through Multi-Scale Matrix and Unit Visualizations

Siwei Fu, Jian Zhao, Linping Yuan +3

Comparative analysis of event sequence data is essential in many application domains, such as website design and medical care. However, analysts often face two challenges: they may…

cs.HC2020★ 25 cited

DFSeer: A Visual Analytics Approach to Facilitate Model Selection for Demand Forecasting

Dong Sun, Zezheng Feng, Yuanzhe Chen +5

Selecting an appropriate model to forecast product demand is critical to the manufacturing industry. However, due to the data complexity, market uncertainty and users' demanding re…

cs.HC2020

RankBooster: Visual Analysis of Ranking Predictions

Abishek Puri, Bon Kyung Ku, Yong Wang +1

Ranking is a natural and ubiquitous way to facilitate decision-making in various applications. However, different rankings are often used for the same set of entities, with each ra…

cs.HC2020★ 4 cited

HypoML: Visual Analysis for Hypothesis-based Evaluation of Machine Learning Models

Qianwen Wang, William Alexander, Jack Pegg +2

In this paper, we present a visual analytics tool for enabling hypothesis-based evaluation of machine learning (ML) models. We describe a novel ML-testing framework that combines t…

cs.HC2020★ 33 cited

VoiceCoach: Interactive Evidence-based Training for Voice Modulation Skills in Public Speaking

Xingbo Wang, Haipeng Zeng, Yong Wang +4

The modulation of voice properties, such as pitch, volume, and speed, is crucial for delivering a successful public speech. However, it is challenging to master different voice mod…

cs.HC2020★ 4 cited

Predicting Student Performance in Interactive Online Question Pools Using Mouse Interaction Features

Huan Wei, Haotian Li, Meng Xia +2

Modeling student learning and further predicting the performance is a well-established task in online learning and is crucial to personalized education by recommending different le…

cs.HC2020★ 4 cited

SirenLess: reveal the intention behind news

Xumeng Chen, Leo Yu-Ho Lo, Huamin Qu

News articles tend to be increasingly misleading nowadays, preventing readers from making subjective judgments towards certain events. While some machine learning approaches have b…