Dr. Ole J. Mengshoel is a Senior Systems Scientist with CMU Silicon Valley at the
NASA Ames Research Center. His current research focuses on reasoning, diagnosis, decision
support, reasoning, and machine learning under uncertainty - often using Bayesian
networks – with aerospace applications of interest to NASA. 

Additional research interests include resource allocation and scheduling in real-time
systems, intelligent user interfaces, information assurance, evolutionary algorithms,
knowledge acquisition, and knowledge engineering. Dr. Mengshoel has managed and provided
hands-on leadership in a wide range of research and development projects. Working with
companies such as Boeing, Rockwell Automation, and Rockwell Collins, he has successfully
developed new technologies and software that have or are being matured and transitioned
into the aerospace, defense, finance, education, electronic commerce, and manufacturing
sectors. Dr. Mengshoel has published over 50 articles and papers in journals and
conferences, and holds 4 U.S. patents. He has a Ph.D. in Computer Science from the
University of Illinois, Urbana-Champaign. His undergraduate degree is in Computer Science
from the Norwegian Institute of Technology, Norway (now NTNU). Prior to his work with
NASA, he was a research scientist in the Knowledge-Based Systems at SINTEF
(Scandinavia's largest independent research organization) and in Decision Sciences
Group at Rockwell Scientific (now Teledyne Scientific and Imaging). 

Bayesian Networks

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Adaptive Generalized Crowding for Genetic Algorithms (with Severinio Galan and Antonio de Dios), Information Science (2013)

The genetic algorithm technique known as crowding preserves population diversity by pairing each offspring with...

 

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Towards Real-time, On-board, Hardware-supported Sensor and Software Health Management for Unmanned Aerial Systems (with Johann Schumann, Kristin Y. Rozier, Thomas Reinbacher, Timmy Mbaya, and Corey Ippolito), Annual Conference of the Prognostics and Health Management Society (2013)

Unmanned aerial systems (UASs) can only be deployed if they can effectively complete their missions...

 

PDF

Optimizing Parallel Belief Propagation in Junction Trees using Regression (with Lu Zheng), The 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2013)

The junction tree approach, with applications in artificial intelligence, computer vision, machine learning, and statistics,...

 

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Exploring Multiple Dimensions of Parallelism in Junction Tree Message Passing (with Lu Zheng), Models for Spatial, Temporal and Network Data -- A UAI Application Workshop (2013)

Belief propagation over junction trees is known to be computationally challenging in the general case....

 

PDF

Latent Topic Analysis for Predicting Group Purchasing Behavior on the Social Web (with Feng-Tso Sun, Martin Griss, and Yi-Ting Yeh), Models for Spatial, Temporal and Network Data -- A UAI Application Workshop (2013)

Group-deal websites, where customers purchase products or services in groups, are an interesting phenomenon on...

 

Stochastic Local Search

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Initialization and Restart in Stochastic Local Search: Computing a Most Probable Explanation in Bayesian Networks (with David C. Wilkins and Dan Roth), IEEE Transactions on Knowledge and Data Engineering (2011)

For hard computational problems, stochastic local search has proven to be a competitive approach to...

 

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Portfolios in Stochastic Local Search: Efficiently Computing Most Probable Explanations in Bayesian Networks (with D Roth and D Wilkins), J Autom Reasoning (2010)

Portfolio methods support the combination of different algorithms and heuristics, including stochastic local search (SLS)...

 

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Understanding the Role of Noise in Stochastic Local Search: Analysis and Experiments, Artificial Intelligence (2008)

Stochastic local search (SLS) algorithms have recently been proven to be among the best approaches...

 

Electrical Power Systems

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Multi-Focus and Multi-Level Techniques for Visualization and Analysis of Networks with Thematic Data (with Michele Cossalter and Ted Selker), Proc. of Visualization and Data Analysis (VDA 2013) (2013)

Information-rich data sets bring several challenges in the areas of visualization and analysis, even when...

 

PDF

Multi-focus and Multi-window Techniques for Interactive Network Exploration (with Priya K. Sundararajan and Ted Selker), Proc. of Visualization and Data Analysis (VDA-13) (2013)

Networks analysts often need to compare nodes in different parts of a network. When zoomed...

 

PDF

Reactive Bayesian Network Computation using Feedback Control: An Empirical Study (with Abe Ishihara and Erik Reed), Proc. of the 9th Bayesian Modelling Applications Workshop (2012)

This paper investigates the challenge of integrating intelligent systems into varying computational platforms and application...

 

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Adaptive Control of Bayesian Network Computation (with Erik Reed and Abe Ishihara), Proc. 5th International Symposium on Resilient Control Systems (ISRCS) (2012)

This paper considers the problem of providing, for computational processes, soft real-time (or reactive) response...

 

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A Tutorial on Bayesian Networks for System Health Management (with Arthur Choi, Lu Zheng, and Adnan Darwiche), Machine Learning and Knowledge Discovery for Engineering Systems Health Management (2011)

Bayesian networks have established themselves as an indispensable tool in artificial intelligence, and are being...

 

Human Computer Interaction

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Adaptive Control of Apache Web Server (with Erik Reed and Abe Ishihara), 8th International Workshop on Feedback Computing (2013)

Traffic to a Web site can vary dramatically. At the same time it is highly...

 

PDF

Multi-Focus and Multi-Level Techniques for Visualization and Analysis of Networks with Thematic Data (with Michele Cossalter and Ted Selker), Proc. of Visualization and Data Analysis (VDA 2013) (2013)

Information-rich data sets bring several challenges in the areas of visualization and analysis, even when...

 

PDF

Multi-focus and Multi-window Techniques for Interactive Network Exploration (with Priya K. Sundararajan and Ted Selker), Proc. of Visualization and Data Analysis (VDA-13) (2013)

Networks analysts often need to compare nodes in different parts of a network. When zoomed...

 

PDF

Visualizing and Understanding Large-Scale Bayesian Networks (with Michele Cossalter and Ted Selker), The AAAI-11 Workshop on Scalable Integration of Analytics and Visualization (2011)

Bayesian networks are a theoretically well-founded approach to represent large multi-variate probability distributions, and have...

 

PDF

Verification and Validation of System Health Management Models using Parametric Testing (with Erik Reed and Johann Schumann), Proc. of Infotech@Aerospace 2011 (2011)

System Health Management (SHM) systems have found their way into many safety-critical aerospace and industrial...

 

Evolutionary Computation

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Adaptive Generalized Crowding for Genetic Algorithms (with Severinio Galan and Antonio de Dios), Information Science (2013)

The genetic algorithm technique known as crowding preserves population diversity by pairing each offspring with...

 

PDF

A Novel Mating Approach for Genetic Algorithms (with Severino Galan and Rafael Pinter), Evolutionary Computation (2013)

Genetic algorithms typically use crossover, which relies on mating a set of selected parents. As...

 

PDF

Age-Layered Expectation Maximization for Parameter Learning in Bayesian Networks (with Avneesh Saluja and Priya Sundararajan), Proc. of the Fifteenth International Conference on Artificial Intelligence and Statistics (2012)

The expectation maximization (EM) algorithm is a popular algorithm for parameter estimation in models with...

 

PDF

Generalized Crowding for Genetic Algorithms (with Severino F. Galan), Genetic and Evolutionary Computation Conference 2010 (GECCO-10) (2010)

Crowding is a technique used in genetic algorithms to preserve diversity in the population and...

 

PDF

Constraint Handling Using Tournament Selection: Abductive Inference in Partly Deterministic Bayesian Network (with Severino F. Galan), Evolutionary Computation (2009)

Constraints occur in many application areas of interest to evolutionary computation. The area considered here...

 

Parallel Computing

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Towards Real-time, On-board, Hardware-supported Sensor and Software Health Management for Unmanned Aerial Systems (with Johann Schumann, Kristin Y. Rozier, Thomas Reinbacher, Timmy Mbaya, and Corey Ippolito), Annual Conference of the Prognostics and Health Management Society (2013)

Unmanned aerial systems (UASs) can only be deployed if they can effectively complete their missions...

 

PDF

Optimizing Parallel Belief Propagation in Junction Trees using Regression (with Lu Zheng), The 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2013)

The junction tree approach, with applications in artificial intelligence, computer vision, machine learning, and statistics,...

 

PDF

Exploring Multiple Dimensions of Parallelism in Junction Tree Message Passing (with Lu Zheng), Models for Spatial, Temporal and Network Data -- A UAI Application Workshop (2013)

Belief propagation over junction trees is known to be computationally challenging in the general case....

 

PDF

MapReduce for Bayesian Network Parameter Learning using the EM Algorithm (with Aniruddha Basak and Irina Brinster), Proc. of Big Learning: Algorithms, Systems and Tools (2012)

This work applies the distributed computing framework MapReduce to Bayesian network parameter learning from incomplete...

 

PDF

Scaling Bayesian Network Parameter Learning with Expectation Maximization using MapReduce (with Erik B. Reed), Proc. of Big Learning: Algorithms, Systems and Tools (2012)

Bayesian network (BN) parameter learning from incomplete data can be a computationally expensive task for...

 

Synthetic Problems

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Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering (with David C. Wilkins and Dan Roth), Artificial Intelligence (2006)

This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty...

 

Diagnosis

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Towards Real-time, On-board, Hardware-supported Sensor and Software Health Management for Unmanned Aerial Systems (with Johann Schumann, Kristin Y. Rozier, Thomas Reinbacher, Timmy Mbaya, and Corey Ippolito), Annual Conference of the Prognostics and Health Management Society (2013)

Unmanned aerial systems (UASs) can only be deployed if they can effectively complete their missions...

 

PDF

Software Health Management with Bayesian Networks (with Johann Schumann, Timmy Mbaya, Knot Pipatsrisawat, Ashok Srivastava, Arthur Choi, and Adnan Darwiche), Innovations in Systems and Software Engineering (2013)

Software Health Management (SWHM) is an emerging field which addresses the critical need to detect,...

 

PDF

Multi-Focus and Multi-Level Techniques for Visualization and Analysis of Networks with Thematic Data (with Michele Cossalter and Ted Selker), Proc. of Visualization and Data Analysis (VDA 2013) (2013)

Information-rich data sets bring several challenges in the areas of visualization and analysis, even when...

 

PDF

Multi-focus and Multi-window Techniques for Interactive Network Exploration (with Priya K. Sundararajan and Ted Selker), Proc. of Visualization and Data Analysis (VDA-13) (2013)

Networks analysts often need to compare nodes in different parts of a network. When zoomed...

 

PDF

Software and System Health Management for Autonomous Robotics Missions (with Timmy Mbaya), Proc. of i-SAIRAS 2012 (2012)

Advanced autonomous robotics space missions rely heavily on the flawless interaction of complex hardware, multiple...

 

Junction Trees

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Optimizing Parallel Belief Propagation in Junction Trees using Regression (with Lu Zheng), The 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2013)

The junction tree approach, with applications in artificial intelligence, computer vision, machine learning, and statistics,...

 

PDF

Exploring Multiple Dimensions of Parallelism in Junction Tree Message Passing (with Lu Zheng), Models for Spatial, Temporal and Network Data -- A UAI Application Workshop (2013)

Belief propagation over junction trees is known to be computationally challenging in the general case....

 

PDF

Reactive Bayesian Network Computation using Feedback Control: An Empirical Study (with Abe Ishihara and Erik Reed), Proc. of the 9th Bayesian Modelling Applications Workshop (2012)

This paper investigates the challenge of integrating intelligent systems into varying computational platforms and application...

 

PDF

Accelerating Bayesian Network Parameter Learning Using Hadoop and MapReduce (with Aniruddha Basak, Irina Brinster, and Xianheng Ma), Proc. of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining (BigMine’12) (2012)

Learning conditional probability tables of large Bayesian Networks (BNs) with hidden nodes using the Expectation...

 

PDF

Adaptive Control of Bayesian Network Computation (with Erik Reed and Abe Ishihara), Proc. 5th International Symposium on Resilient Control Systems (ISRCS) (2012)

This paper considers the problem of providing, for computational processes, soft real-time (or reactive) response...

 

Arithmetic Circuits

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Towards Real-time, On-board, Hardware-supported Sensor and Software Health Management for Unmanned Aerial Systems (with Johann Schumann, Kristin Y. Rozier, Thomas Reinbacher, Timmy Mbaya, and Corey Ippolito), Annual Conference of the Prognostics and Health Management Society (2013)

Unmanned aerial systems (UASs) can only be deployed if they can effectively complete their missions...

 

PDF

Software Health Management with Bayesian Networks (with Johann Schumann, Timmy Mbaya, Knot Pipatsrisawat, Ashok Srivastava, Arthur Choi, and Adnan Darwiche), Innovations in Systems and Software Engineering (2013)

Software Health Management (SWHM) is an emerging field which addresses the critical need to detect,...

 

PDF

Software and System Health Management for Autonomous Robotics Missions (with Timmy Mbaya), Proc. of i-SAIRAS 2012 (2012)

Advanced autonomous robotics space missions rely heavily on the flawless interaction of complex hardware, multiple...

 

PDF

Bayesian Software Health Management for Aircraft Guidance, Navigation, and Control (with Johann M. Schumann and Timmy Mbaya), Annual conference of the prognostics and health management society 2011 (PHM-11) (2011)

Modern aircraft — both piloted fly-by-wire commercial aircraft as well as UAVs — more and...

 

PDF

Integrating Probabilistic Reasoning and Statistical Quality Control Techniques for Fault Diagnosis in Hybrid Domains (with Brian Ricks and Craig Harrison), Annual Conference of the Prognostics and Health Management Society 2011 (PHM-11) (2011)

Bayesian networks, which may be compiled to arithmetic circuits in the interest of speed and...

 

Software Engineering

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Towards Real-time, On-board, Hardware-supported Sensor and Software Health Management for Unmanned Aerial Systems (with Johann Schumann, Kristin Y. Rozier, Thomas Reinbacher, Timmy Mbaya, and Corey Ippolito), Annual Conference of the Prognostics and Health Management Society (2013)

Unmanned aerial systems (UASs) can only be deployed if they can effectively complete their missions...

 

PDF

Adaptive Control of Apache Web Server (with Erik Reed and Abe Ishihara), 8th International Workshop on Feedback Computing (2013)

Traffic to a Web site can vary dramatically. At the same time it is highly...

 

PDF

Software Health Management with Bayesian Networks (with Johann Schumann, Timmy Mbaya, Knot Pipatsrisawat, Ashok Srivastava, Arthur Choi, and Adnan Darwiche), Innovations in Systems and Software Engineering (2013)

Software Health Management (SWHM) is an emerging field which addresses the critical need to detect,...

 

PDF

Accelerating Bayesian Network Parameter Learning Using Hadoop and MapReduce (with Aniruddha Basak, Irina Brinster, and Xianheng Ma), Proc. of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining (BigMine’12) (2012)

Learning conditional probability tables of large Bayesian Networks (BNs) with hidden nodes using the Expectation...

 

PDF

Bayesian Software Health Management for Aircraft Guidance, Navigation, and Control (with Johann M. Schumann and Timmy Mbaya), Annual conference of the prognostics and health management society 2011 (PHM-11) (2011)

Modern aircraft — both piloted fly-by-wire commercial aircraft as well as UAVs — more and...

 

Verification and Validation

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Towards Real-time, On-board, Hardware-supported Sensor and Software Health Management for Unmanned Aerial Systems (with Johann Schumann, Kristin Y. Rozier, Thomas Reinbacher, Timmy Mbaya, and Corey Ippolito), Annual Conference of the Prognostics and Health Management Society (2013)

Unmanned aerial systems (UASs) can only be deployed if they can effectively complete their missions...

 

PDF

Software Health Management with Bayesian Networks (with Johann Schumann, Timmy Mbaya, Knot Pipatsrisawat, Ashok Srivastava, Arthur Choi, and Adnan Darwiche), Innovations in Systems and Software Engineering (2013)

Software Health Management (SWHM) is an emerging field which addresses the critical need to detect,...

 

PDF

Multi-focus and Multi-window Techniques for Interactive Network Exploration (with Priya K. Sundararajan and Ted Selker), Proc. of Visualization and Data Analysis (VDA-13) (2013)

Networks analysts often need to compare nodes in different parts of a network. When zoomed...

 

PDF

Verification and Validation of System Health Management Models using Parametric Testing (with Erik Reed and Johann Schumann), Proc. of Infotech@Aerospace 2011 (2011)

System Health Management (SHM) systems have found their way into many safety-critical aerospace and industrial...

 

PDF

A Framework for Systematic Benchmarking of Monitoring and Diagnostic Systems (with Tolga Kurtoglu and Scott Poll), Proc. of the 2008 Conference on Prognostics and Health Management (PHM-08) (2008)

In this paper, we present an architecture and a formal framework to be used for...

 

Stochastic Optimization

PDF

Adaptive Generalized Crowding for Genetic Algorithms (with Severinio Galan and Antonio de Dios), Information Science (2013)

The genetic algorithm technique known as crowding preserves population diversity by pairing each offspring with...

 

PDF

A Novel Mating Approach for Genetic Algorithms (with Severino Galan and Rafael Pinter), Evolutionary Computation (2013)

Genetic algorithms typically use crossover, which relies on mating a set of selected parents. As...

 

PDF

Age-Layered Expectation Maximization for Parameter Learning in Bayesian Networks (with Avneesh Saluja and Priya Sundararajan), Proc. of the Fifteenth International Conference on Artificial Intelligence and Statistics (2012)

The expectation maximization (EM) algorithm is a popular algorithm for parameter estimation in models with...

 

PDF

Constraint Handling Using Tournament Selection: Abductive Inference in Partly Deterministic Bayesian Network (with Severino F. Galan), Evolutionary Computation (2009)

Constraints occur in many application areas of interest to evolutionary computation. The area considered here...

 

PDF

Understanding the Role of Noise in Stochastic Local Search: Analysis and Experiments, Artificial Intelligence (2008)

Stochastic local search (SLS) algorithms have recently been proven to be among the best approaches...

 

Aerospace

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Towards Real-time, On-board, Hardware-supported Sensor and Software Health Management for Unmanned Aerial Systems (with Johann Schumann, Kristin Y. Rozier, Thomas Reinbacher, Timmy Mbaya, and Corey Ippolito), Annual Conference of the Prognostics and Health Management Society (2013)

Unmanned aerial systems (UASs) can only be deployed if they can effectively complete their missions...

 

PDF

Software Health Management with Bayesian Networks (with Johann Schumann, Timmy Mbaya, Knot Pipatsrisawat, Ashok Srivastava, Arthur Choi, and Adnan Darwiche), Innovations in Systems and Software Engineering (2013)

Software Health Management (SWHM) is an emerging field which addresses the critical need to detect,...

 

PDF

Multi-Focus and Multi-Level Techniques for Visualization and Analysis of Networks with Thematic Data (with Michele Cossalter and Ted Selker), Proc. of Visualization and Data Analysis (VDA 2013) (2013)

Information-rich data sets bring several challenges in the areas of visualization and analysis, even when...

 

PDF

Software and System Health Management for Autonomous Robotics Missions (with Timmy Mbaya), Proc. of i-SAIRAS 2012 (2012)

Advanced autonomous robotics space missions rely heavily on the flawless interaction of complex hardware, multiple...

 

PDF

Bayesian Software Health Management for Aircraft Guidance, Navigation, and Control (with Johann M. Schumann and Timmy Mbaya), Annual conference of the prognostics and health management society 2011 (PHM-11) (2011)

Modern aircraft — both piloted fly-by-wire commercial aircraft as well as UAVs — more and...

 

Markov Chains

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Generalized Crowding for Genetic Algorithms (with Severino F. Galan), Genetic and Evolutionary Computation Conference 2010 (GECCO-10) (2010)

Crowding is a technique used in genetic algorithms to preserve diversity in the population and...

 

PDF

Understanding the Role of Noise in Stochastic Local Search: Analysis and Experiments, Artificial Intelligence (2008)

Stochastic local search (SLS) algorithms have recently been proven to be among the best approaches...

 

Reconfiguration

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Diagnosis and Reconfiguration using Bayesian Networks: An Electrical Power System Case Study (with W. Bradley Knox), The IJCAI-09 Workshop on Self-* and Autonomous Systems: reasoning and integration challenges (SAS-09) (2009)

Automated diagnosis and reconfiguration are important computational techniques that aim to minimize human intervention in...

 

Feedback Control

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Adaptive Control of Apache Web Server (with Erik Reed and Abe Ishihara), 8th International Workshop on Feedback Computing (2013)

Traffic to a Web site can vary dramatically. At the same time it is highly...

 

PDF

Mobile Computing: Challenges and Opportunities for Autonomy and Feedback (with Bob Iannucci and Abe Ishihara), 8th International Workshop on Feedback Computing (2013)

Mobile devices have evolved to become computing platforms more similar to desktops and workstations than...

 

PDF

Reactive Bayesian Network Computation using Feedback Control: An Empirical Study (with Abe Ishihara and Erik Reed), Proc. of the 9th Bayesian Modelling Applications Workshop (2012)

This paper investigates the challenge of integrating intelligent systems into varying computational platforms and application...

 

PDF

Adaptive Control of Bayesian Network Computation (with Erik Reed and Abe Ishihara), Proc. 5th International Symposium on Resilient Control Systems (ISRCS) (2012)

This paper considers the problem of providing, for computational processes, soft real-time (or reactive) response...

 

Expectation Maximization

PDF

MapReduce for Bayesian Network Parameter Learning using the EM Algorithm (with Aniruddha Basak and Irina Brinster), Proc. of Big Learning: Algorithms, Systems and Tools (2012)

This work applies the distributed computing framework MapReduce to Bayesian network parameter learning from incomplete...

 

PDF

Scaling Bayesian Network Parameter Learning with Expectation Maximization using MapReduce (with Erik B. Reed), Proc. of Big Learning: Algorithms, Systems and Tools (2012)

Bayesian network (BN) parameter learning from incomplete data can be a computationally expensive task for...

 

PDF

Age-Layered Expectation Maximization for Parameter Learning in Bayesian Networks (with Avneesh Saluja and Priya Sundararajan), Proc. of the Fifteenth International Conference on Artificial Intelligence and Statistics (2012)

The expectation maximization (EM) algorithm is a popular algorithm for parameter estimation in models with...

 

Social Networks

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Will We Connect Again? Machine Learning for Link Prediction in Mobile Social Networks (with Raj Desai, Andrew Chen, and Brian Tran), Eleventh Workshop on Mining and Learning with Graphs (2013)

In this paper we examine link prediction for two types of data sets with mobility...

 

PDF

Latent Topic Analysis for Predicting Group Purchasing Behavior on the Social Web (with Feng-Tso Sun, Martin Griss, and Yi-Ting Yeh), Models for Spatial, Temporal and Network Data -- A UAI Application Workshop (2013)

Group-deal websites, where customers purchase products or services in groups, are an interesting phenomenon on...

 

PDF

Multi-Focus and Multi-Level Techniques for Visualization and Analysis of Networks with Thematic Data (with Michele Cossalter and Ted Selker), Proc. of Visualization and Data Analysis (VDA 2013) (2013)

Information-rich data sets bring several challenges in the areas of visualization and analysis, even when...

 

PDF

The Impact of Social Affinity on Phone Calling Patterns: Categorizing Social Ties from Call Data Records (with Sara Motahari, Phyllis Reuther, Sandeep Appala, Luca Zoia, and Jay Shah), Proc. of the Sixth Workshop on Social Network Mining and Analysis (2012)

Social ties defined by phone calls made between people can be grouped to various affinity...

 

MapReduce

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MapReduce for Bayesian Network Parameter Learning using the EM Algorithm (with Aniruddha Basak and Irina Brinster), Proc. of Big Learning: Algorithms, Systems and Tools (2012)

This work applies the distributed computing framework MapReduce to Bayesian network parameter learning from incomplete...

 

PDF

Scaling Bayesian Network Parameter Learning with Expectation Maximization using MapReduce (with Erik B. Reed), Proc. of Big Learning: Algorithms, Systems and Tools (2012)

Bayesian network (BN) parameter learning from incomplete data can be a computationally expensive task for...

 

Machine Learning

PDF

Optimizing Parallel Belief Propagation in Junction Trees using Regression (with Lu Zheng), The 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2013)

The junction tree approach, with applications in artificial intelligence, computer vision, machine learning, and statistics,...

 

PDF

Will We Connect Again? Machine Learning for Link Prediction in Mobile Social Networks (with Raj Desai, Andrew Chen, and Brian Tran), Eleventh Workshop on Mining and Learning with Graphs (2013)

In this paper we examine link prediction for two types of data sets with mobility...

 

PDF

Latent Topic Analysis for Predicting Group Purchasing Behavior on the Social Web (with Feng-Tso Sun, Martin Griss, and Yi-Ting Yeh), Models for Spatial, Temporal and Network Data -- A UAI Application Workshop (2013)

Group-deal websites, where customers purchase products or services in groups, are an interesting phenomenon on...

 

PDF

Mobile Computing: Challenges and Opportunities for Autonomy and Feedback (with Bob Iannucci and Abe Ishihara), 8th International Workshop on Feedback Computing (2013)

Mobile devices have evolved to become computing platforms more similar to desktops and workstations than...

 

Latent Dirichlet Allocation

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Latent Topic Analysis for Predicting Group Purchasing Behavior on the Social Web (with Feng-Tso Sun, Martin Griss, and Yi-Ting Yeh), Models for Spatial, Temporal and Network Data -- A UAI Application Workshop (2013)

Group-deal websites, where customers purchase products or services in groups, are an interesting phenomenon on...

 

Mobility

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Mobile Computing: Challenges and Opportunities for Autonomy and Feedback (with Bob Iannucci and Abe Ishihara), 8th International Workshop on Feedback Computing (2013)

Mobile devices have evolved to become computing platforms more similar to desktops and workstations than...

 

Web

PDF

Adaptive Control of Apache Web Server (with Erik Reed and Abe Ishihara), 8th International Workshop on Feedback Computing (2013)

Traffic to a Web site can vary dramatically. At the same time it is highly...