KWAN-LIU MA


PUBLICATIONS

(A more complete list can be seen at DBLP.)

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Scalable Training of Sparse Linear SVM

Guo-Xun Yuan and Kwan-Liu Ma

In Proceedings of IEEE ICDM 2012
(Accepted for publication)
December , 2012

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Sparse linear support vector machines have been widely applied to variable selection in many applications. For large data, managing the cost of training a sparse model with good predication performance is an essential topic. In this work, we propose a scalable training algorithm for large-scale data with millions of examples and features. We develop a dual alternating direction method for solving L1-regularized linear SVM ...

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Inferring Human Mobility Patterns from Anonymized Mobile Communication Usage

Yuzuru Tanahashi, James R. Rowland, Stephen North, and Kwan-Liu Ma

In Proceedings of ACM 10th International Conference on Advances in Mobile Computing & Multimedia (MoMM 2012)
December, 2012, pp. 151-160

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Anonymized Call Detail Records (CDRs) contain positional information of large populations and therefore have been extensively analyzed to understand human mobility. Due to the temporally sparse and spatially coarse nature of the data, most of these studies have focused on primitive aspects of movements such as travel distance and speed. Incorporating underlying geographic information in these analyses would allow analysts to put these movements into context and to gain deeper insight into how metropolitan areas function ...

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Visual Cluster Exploration of Web Clickstream Data

Jishang Wei, Zeqian Shen, Neel Sundaresan, and Kwan-Liu Ma

In Proceedings of the Visual Analytics Science and Technology Conference
(Accepted by VisWeek/VAST 2012)
2012

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Web clickstream data are routinely collected to study how users browse the web and use a particular service. It is clear that the ability to extract user behavioral information from such data is very valuable to e-commerce companies. In this paper, we introduce a visual analytics system to facilitate interactive visual cluster exploration of web clickstream data. The system first presents an overview of the clickstreams cluster structure by a Self-Organizing Map with Markov chain models, and then enables visual cluster analysis through an intuitive user interface so that an analyst can either obtain information summarization of a selected group of data or supervise further data cluster generation ...

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Living Liquid: Design and Evaluation of an Exploratory Visualization Tool for Museum Visitors

Joyce Ma, Isaac Liao, Jennifer Frazier, and Kwan-Liu Ma

IEEE Transactions on Visualization and Computer Graphics
(Accepted by VisWeek/InfoVis 2012)
2012

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Interactive visualizations can allow science museum visitors to explore new worlds by seeing and interacting with scientific data. However, designing interactive visualizations for informal learning environments, such as museums, presents several challenges: varying levels of visitor domain knowledge and visualization familiarity, the need to engage visitors on a personal level, and limited visitor time per exhibit. This paper examines these design considerations through the iterative development and evaluation of an interactive visualization exhibit, Living Liquid, which allows visitors to explore the time-varying global distribution of simulated marine microbes by using a touchscreen interface ...

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Visualizing Flow of Uncertainty through Analytical Processes

Yingcai Wu, Guo-Xun Yuan, and Kwan-Liu Ma

IEEE Transactions on Visualization and Computer Graphics
(Accepted by VisWeek/InfoVis 2012)
2012

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Uncertainty can arise in every stage of a visual analytics process, especially in data-intensive applications with a sequence of data transformations. Analysts must be properly informed about the extent of uncertainty to avoid making erroneous decisions. Additionally, throughout the process of multidimensional, multivariate data analysis, uncertainty due to data transformation and integration may split, merge, increase, or decrease. This dynamic characteristic along with other features of uncertainty pose a great challenge to effective uncertainty-aware visualization ...

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Design Considerations for Optimizing Storyline Visualizations

Yuzuru Tanahashi and Kwan-Liu Ma

IEEE Transactions on Visualization and Computer Graphics
(Accepted by VisWeek/InfoVis 2012)
2012

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Storyline visualization is a technique used to depict the temporal dynamics of social interactions. This visualization technique was first introduced as a hand-drawn illustration in XKCD’s “Movie Narrative Charts” [22]. If properly constructed, the visualization can convey both global trends and local interactions in the data. However, previous methods for automating storyline visualizations are overly simple, failing to achieve some of the essential principles practiced by professional illustrators ...

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Fuzzy Volume Rendering

Nathaniel Fout and Kwan-Liu Ma

IEEE Transactions on Visualization and Computer Graphics
(Accepted by VisWeek/Vis 2012)
2012

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In order to assess the reliability of volume rendering, it is necessary to consider the uncertainty associated with the volume data and how it is propagated through the volume rendering algorithm, as well as the contribution to uncertainty from the rendering algorithm itself. In this work, we show how to apply concepts from the field of reliable computing in order to build a framework for management of uncertainty in volume rendering, with the result being a self-validating computational model to compute a posteriori uncertainty bounds ...

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An Adaptive Prediction-based Approach to Lossless Compression of Floating-point Volume Data

Nathaniel Fout and Kwan-Liu Ma

IEEE Transactions on Visualization and Computer Graphics
(Accepted by VisWeek/Vis 2012)
2012

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In this work we address the problem of lossless compression of floating-point scientific and medical data. We propose two prediction-based compression methods that share a common framework, which consists of a switched prediction scheme wherein the best predictor out of a preset group of linear predictors is selected. Such a scheme is able to adapt to different datasets as well as to varying statistics within the data ...

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Flexible Analysis Software for Emerging Architectures

Kenneth Moreland, Brad King, Robert Marynard, and Kwan-Liu Ma

In Proceedings of PDAC-12 Workshop (with SC12)
(accepted for publication)
November, 2012

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We are on the threshold of a transformative change in the basic architecture of high-performance computing. The use of accelerator processors, characterized by large core counts, shared but asymmetrical memory, and heavy thread loading, is quickly becoming the norm in high performance computing. These accelerators represent significant challenges in updating our existing base of software. An intrinsic problem with this transition is a fundamental programming shift from message passing processes to much more fine thread scheduling with memory sharing ...

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ViSizer: A Visualization Resizing Framework

Yingcai Wu, Xiaotong Liu, Shixia Liu and Kwan-Liu Ma

IEEE Transactions on Visualization and Computer Graphics
(Accepted for publication) http://doi.ieeecomputersociety.org/10.1109/TVCG.2012.114
2012

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Visualization resizing is useful for many applications where users may use different display devices. General resizing techniques (e.g., uniform scaling) and image resizing techniques suffer from several drawbacks, as they do not consider the
content of the visualizations. This work introduces ViSizer, a perception-based framework for automatically resizing a visualization to fit any display.We formulate an energy function based on a perception model (feature congestion), which aims to determine the optimal deformation for every local region ...

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Visual Analysis of Massive Web Session Data

Zeqian Shen, Jishang Wei, Neel Sundaresan, and Kwan-Liu Ma

In Proceedings of IEEE Symposium on Large Data Analysis and Visualization (LDAV)
October, 2012

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Tracking and recording users’ browsing behaviors on the web down to individual mouse clicks can create massive web session logs. While such web session data contain valuable information about user behaviors, the ever-increasing data size has placed a big challenge to analyzing and visualizing the data. An efficient data analysis framework requires both powerful computational analysis and interactive visualization. Following the visual analytics mantra “Analyze first, show the important, zoom, filter and analyze further, details on demand”, we introduce a two-tier visual analysis system, TrailExplorer2, to discover knowledge from massive log data ...

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Group Dynamics in Scientific Visualization

Sedat Ozer, Jishang Wei, Deborah Silver, Kwan-Liu Ma, and Pino Martin

In Proceedings of IEEE Symposium on Large Data Analysis and Visualization (LDAV '12)
October, 2012, pp. 97-104

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As the size of simulations increases, the number of features to track also increases. Furthermore, following individual features becomes challenging when there are many features in the data. However, many of these features act in groups, which potentially reduces both the computational and visual tracking load. While feature tracking, which follows the interaction and evolution of individual features, is an ...

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A Job Scheduling Design for Visualization Services using GPU Clusters

Wei-Hsien Hsu, Chun-Fu Wang, Kwan-Liu Ma, Hongfeng Yu, and Jacqueline H. Chen

In Proceedings of IEEE Cluster 2012
(Accepted for publication)
Semptember, 2012

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Modern large-scale heterogeneous computers incorporating
GPUs offer impressive processing capabilities. It is desirable to fully utilize such systems for serving multiple users concurrently to visualize large data at interactive rates. However, as the disparity between data transfer speed and compute speed continues to increase in heterogeneous systems, data locality becomes crucial for performance. We present a new job scheduling design to support multiuser exploration of large data in a heterogeneous computing environment, achieving near optimal data locality and minimizing I/O overhead ...

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Clustering, Visualizing, and Navigating for Large Dynamic Graphs

Arnaud Sallaberry, Chris Muelder, and Kwan-Liu Ma

In Proceedings of Graph Drawing 2012
(Accepted for publication)
Sepetember, 2012

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In this paper, we present a new approach to exploring dynamic graphs. We first propose a new clustering algorithm for dynamic graphs which fi nds an ideal clustering for each time-step and links the clusters together. The resulting time-varying clusters are then used to defi ne two visual representations. The fi rst view is an overview that shows how clusters evolve over time and provides an interface to find and select interesting time-steps . ...

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Ambiguity-Free Edge-Bundling for Interactive Graph Visualization

Sheng-Jie Luo, Chun-Liang Liu, Bing-Yu Chen, and Kwan-Liu Ma

IEEE Transactions on Visualization and Computer Graphics
Volume 18, Number 5, 2012

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Graph visualization has been widely used to understand and present both global structural and local adjacency information in relational datasets (e.g., transportation networks, citation networks, or social networks). Large graphs, however, are difficult to visualize because fast layout and good clarity are not always easily achieved. When the number of edges is large, edge bundling can be used to improve the clarity, but in many cases, the edges could be still too cluttered to permit correct interpretation of the relations between nodes ...

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Restoration of Brick and Stone Relief from Single Rubbing Images

Zhuwen LI, Song Wang, Jinhui Yu, and Kwan-Liu Ma

IEEE Transactions on Visualization and Computer Graphics
Volume 18, Number 2, 2012, pp. 177-187

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We present a two-level approach for height map estimation from single images, aiming at restoring brick and stone relief (BSR) from their rubbing images in a visually plausible manner. In our approach, the base relief of the low frequency component is estimated automatically with a partial differential equation (PDE) based mesh deformation scheme. A few vertices near the central area of the object region are selected and assigned with heights estimated by an erosion based contour map ...

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Visual Reasoning about Social Networks using Centrality Sensitivities

Carlos Correa, Tarik Crnovrsanin and Kwan-Liu Ma

IEEE Transactions on Visualization and Computer Graphics

Volume 18, Number 1, 2012

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In this paper, we study the sensitivity of centrality metrics as a key metric of social networks to support visual reasoning. As centrality represents the prestige or importance of a node in a network, its sensitivity represents the importance of the relationship between this and all other nodes in the network. We have derived an analytical solution that extracts the sensitivity as the derivative of centrality with respect to degree for two centrality metrics based on feedback and random walks ...

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Scientific Storytelling using Visualization

Kwan-Liu Ma, Isaac Liao, Jennifer Frazier, Helwig Hauser, and Helen-Nicole Kostis

IEEE Computer Graphics and Applications
Volume 32, Number 1, 2012, pp. 12-19

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Scientists frequently tell stories using visualizations of scientific data, in the process of disseminating findings to peers and the general public. However, techniques and methods for effective scientific storytelling have received little attention so far. This article explores how literary and theatrical narrative conventions can inform the design and presentation of visualizations, and discusses the challenges of adapting scientific visualizations for broader audiences ...

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Visual Analysis of Particle Behaviors to Understand Combustion Simulations

Jishang Wei,Hongfeng Yu, Ray W. Grout, Jacqueline Chen, and Kwan-Liu Ma

IEEE Computer Graphics and Applications
Volume 32, Number 1, 2012, pp. 22-33

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Simulations of turbulent flames have used particles to capture the dynamic behavior of combustion in next-generation engines. Each particle includes a history of its movement positions and changing thermochemical states. Analyzing such a set of many millions of particles helps scientists understand turbulence. A dual-space method enables effective visual analysis of both the spatial movement and attribute evolution of particles. A cluster-label-classify strategy categorizes particles' attribute evolution curves ...