Ole J. Mengshoel

104 papers A* 6A 8B 9Misc 3Journal 34Unranked 39
YearRankTypeTitle / Venue / Authors
2024 J jnl
Corrigendum: SemNet: Learning semantic attributes for human activity recognition with deep belief networks.
Frontiers Big Data
Shanmuga Venkatachalam, Harideep Nair, Ming Zeng, Cathy Tan, Ole J. Mengshoel, John Paul Shen
2024 J jnl
Customizing graph neural networks using path reweighting.
Inf. Sci.
Jianpeng Chen, Yujing Wang, Ming Zeng, Zongyi Xiang, Bitan Hou, Tong Yu, Ole J. Mengshoel, Yazhou Ren
2024 — conf
Detecting and Segmenting Solar Farms in Satellite Imagery: A Study of Deep Neural Network Architectures.
SCAI
Erling Olweus, Ole J. Mengshoel
2024 — conf
Green Urban Mobility with Autonomous Electric Ferries: Studies of Simulated Maritime Collisions using Adaptive Stress Testing.
SCAI
Jan-Marius Vatle, Bjørn-Olav H. Eriksen, Ole J. Mengshoel
2022 J jnl
SemNet: Learning semantic attributes for human activity recognition with deep belief networks.
Frontiers Big Data
Shanmuga Venkatachalam, Harideep Nair, Ming Zeng, Cathy Tan, Ole J. Mengshoel, John Paul Shen
2020 J jnl
Adaptive Stress Testing: Finding Likely Failure Events with Reinforcement Learning.
J. Artif. Intell. Res.
Ritchie Lee, Ole J. Mengshoel, Anshu Saksena, Ryan W. Gardner, Daniel Genin, Joshua Silbermann, Michael P. Owen, Mykel J. Kochenderfer
2020 A* conf
Graphical Models Meet Bandits: A Variational Thompson Sampling Approach.
ICML
Tong Yu, Branislav Kveton, Zheng Wen, Ruiyi Zhang, Ole J. Mengshoel
2020 J jnl
Influence Diagram Bandits: Variational Thompson Sampling for Structured Bandit Problems.
CoRR
Tong Yu, Branislav Kveton, Zheng Wen, Ruiyi Zhang, Ole J. Mengshoel
2019 — conf
AttriNet: learning mid-level features for human activity recognition with deep belief networks.
UbiComp/ISWC Adjunct
Harideep Nair, Cathy Tan, Ming Zeng, Ole J. Mengshoel, John Paul Shen
2019 J jnl
Customized Graph Embedding: Tailoring the Embedding Vector to a Specific Application.
CoRR
Bitan Hou, Yujing Wang, Ming Zeng, Shan Jiang, Ole J. Mengshoel, Yunhai Tong, Jing Bai
2018 J jnl
Adaptive Stress Testing: Finding Failure Events with Reinforcement Learning.
CoRR
Ritchie Lee, Ole J. Mengshoel, Anshu Saksena, Ryan W. Gardner, Daniel Genin, Joshua Silbermann, Michael P. Owen, Mykel J. Kochenderfer
2018 J jnl
CADDeLaG: Framework for distributed anomaly detection in large dense graph sequences.
CoRR
Aniruddha Basak, Kamalika Das, Ole J. Mengshoel
2018 B conf
Captioning with Language-Based Attention.
DSAA
Anshu Rajendra, Ritwik Rajendra, Ole J. Mengshoel, Ming Zeng, Momina Haider
2018 A* conf
Customized Nonlinear Bandits for Online Response Selection in Neural Conversation Models.
AAAI
Bing Liu, Tong Yu, Ian R. Lane, Ole J. Mengshoel
2018 — conf
ILPC: Iterative Learning Using Physical Constraints in Real-World Sensing Data.
AAAI Workshops
Tong Yu, Shijia Pan, Susu Xu, Xinlei Chen, Mostafa Mirshekari, Jonathon Fagert, Hae Young Noh, Pei Zhang, Ole J. Mengshoel
2018 — conf
Improving Bag-Of-Words: Capturing Local Information for Motion-Based Activity Recognition.
UbiComp/ISWC Adjunct
Ming Zeng, Tong Yu, Ole J. Mengshoel, Helen Qin, Chris Lee, John Paul Shen
2018 A conf
Interpretable Categorization of Heterogeneous Time Series Data.
SDM
Ritchie Lee, Mykel J. Kochenderfer, Ole J. Mengshoel, Joshua Silbermann
2018 B conf
Mitigating Multi-tenant Interference in Continuous Mobile Offloading.
CLOUD
Zhou Fang, Mulong Luo, Tong Yu, Ole J. Mengshoel, Mani B. Srivastava, Rajesh K. Gupta
2018 J jnl
Neighborhood beautification: Graph layout through message passing.
J. Vis. Lang. Comput.
Severino F. Galán, Ole J. Mengshoel
2018 — conf
Renewable Energy Integration: Bayesian Networks for Probabilistic State Estimation.
DARE@PKDD/ECML
Ole J. Mengshoel, Priya Krishnan Sundararajan, Erik Reed, Dongzhen Piao, Briana Johnson
2018 J jnl
Semi-Supervised Convolutional Neural Networks for Human Activity Recognition.
CoRR
Ming Zeng, Tong Yu, Xiao Wang, Le T. Nguyen, Ole J. Mengshoel, Ian R. Lane
2018 — conf
SpectralLeader: Online Spectral Learning for Single Topic Models.
ECML/PKDD (2)
Tong Yu, Branislav Kveton, Zheng Wen, Hung Bui, Ole J. Mengshoel
2018 — conf
Stochastic Optimization for Market Return Prediction Using Financial Knowledge Graph.
ICBK
Xiaoyi Fu, Xinqi Ren, Ole J. Mengshoel, Xindong Wu
2018 J jnl
Understanding and Improving Recurrent Networks for Human Activity Recognition by Continuous Attention.
CoRR
Ming Zeng, Haoxiang Gao, Tong Yu, Ole J. Mengshoel, Helge Langseth, Ian R. Lane, Xiaobing Liu
2018 Misc conf
Understanding and improving recurrent networks for human activity recognition by continuous attention.
UbiComp
Ming Zeng, Haoxiang Gao, Tong Yu, Ole J. Mengshoel, Helge Langseth, Ian R. Lane, Xiaobing Liu
2018 B conf
Wetting and Drying of Soil: From Data to Understandable Models for Prediction.
DSAA
Aniruddha Basak, Ole J. Mengshoel, Kevin M. Schmidt, Chinmay Kulkarni
2017 B conf
Content-based top-N recommendations with perceived similarity.
SMC
Charlie Wang, Arpita Agrawal, Xiaojun Li, Tanima Makkad, Ejaz Veljee, Ole J. Mengshoel, Alvin Jude
2017 J jnl
Customized Nonlinear Bandits for Online Response Selection in Neural Conversation Models.
CoRR
Bing Liu, Tong Yu, Ian R. Lane, Ole J. Mengshoel
2017 J jnl
FootprintID: Indoor Pedestrian Identification through Ambient Structural Vibration Sensing.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.
Shijia Pan, Tong Yu, Mostafa Mirshekari, Jonathon Fagert, Amelie Bonde, Ole J. Mengshoel, Hae Young Noh, Pei Zhang
2017 J jnl
Interpretable Categorization of Heterogeneous Time Series Data.
CoRR
Ritchie Lee, Mykel J. Kochenderfer, Ole J. Mengshoel, Joshua Silbermann
2017 — conf
Mitigating multi-tenant interference on mobile offloading servers: poster abstract.
SoCC
Zhou Fang, Mulong Luo, Tong Yu, Ole J. Mengshoel, Mani B. Srivastava, Rajesh K. Gupta
2017 — ch.
Online Workload Forecasting.
Self-Aware Computing Systems
Nikolas Herbst, Ayman A. Amin, Artur Andrzejak, Lars Grunske, Samuel Kounev, Ole J. Mengshoel, Priya Krishnan Sundararajan
2017 A conf
Optimizing the decomposition of time series using evolutionary algorithms: soil moisture analytics.
GECCO
Aniruddha Basak, Ole J. Mengshoel, Chinmay Kulkarni, Kevin M. Schmidt, Prathi Shastry, Rao Rapeta
2017 A conf
QoS-Aware Scheduling of Heterogeneous Servers for Inference in Deep Neural Networks.
CIKM
Zhou Fang, Tong Yu, Ole J. Mengshoel, Rajesh K. Gupta
2017 — ch.
Self-adaptation for Individual Self-aware Computing Systems.
Self-Aware Computing Systems
Martina Maggio, Tarek F. Abdelzaher, Lukas Esterle, Holger Giese, Jeffrey O. Kephart, Ole J. Mengshoel, Alessandro Vittorio Papadopoulos, Anders Robertsson, Katinka Wolter
2017 — ch.
Self-awareness of Cloud Applications.
Self-Aware Computing Systems
Alexandru Iosup, Xiaoyun Zhu, Arif Merchant, Eva Kalyvianaki, Martina Maggio, Simon Spinner, Tarek F. Abdelzaher, Ole J. Mengshoel, Sara Bouchenak
2017 — conf
Semi-supervised convolutional neural networks for human activity recognition.
IEEE BigData
Ming Zeng, Tong Yu, Xiao Wang, Le T. Nguyen, Ole J. Mengshoel, Ian R. Lane
2017 J jnl
SpectralFPL: Online Spectral Learning for Single Topic Models.
CoRR
Tong Yu, Branislav Kveton, Zheng Wen, Hung Bui, Ole J. Mengshoel
2017 — ch.
Synthesis and Verification of Self-aware Computing Systems.
Self-Aware Computing Systems
Radu Calinescu, Marco Autili, Javier Cámara, Antinisca Di Marco, Simos Gerasimou, Paola Inverardi, Alexander Perucci, Nils Jansen, Joost-Pieter Katoen, Marta Z. Kwiatkowska, Ole J. Mengshoel, Romina Spalazzese, Massimo Tivoli
2017 — conf
Thompson Sampling for Optimizing Stochastic Local Search.
ECML/PKDD (1)
Tong Yu, Branislav Kveton, Ole J. Mengshoel
2017 — conf
Towards continuous and passive authentication across mobile devices: an empirical study.
WISEC
Xiao Wang, Tong Yu, Ole J. Mengshoel, Patrick Tague
2016 — conf
A Genetic Algorithm for Learning Parameters in Bayesian Networks using Expectation Maximization.
Probabilistic Graphical Models
Priya Krishnan Sundararajan, Ole J. Mengshoel
2016 — conf
Hybridizing Personal and Impersonal Machine Learning Models for Activity Recognition on Mobile Devices.
MobiCASE
Tong Yu, Yong Zhuang, Ole J. Mengshoel, Osman Yagan
2016 — conf
Identifying Contributing Factors of Occupant Thermal Discomfort in a Smart Building.
AAAI Workshop: AI for Smart Grids and Smart Buildings
Aniruddha Basak, Ole J. Mengshoel, Stefan Hosein, Rodney Martin, Jayasudha Jayakumaran, Mario Gurrola Morga, Ishwari Aghav
2016 — conf
Incremental learning for matrix factorization in recommender systems.
IEEE BigData
Tong Yu, Ole J. Mengshoel, Alvin Jude, Eugen Feller, Julien Forgeat, Nimish Radia
2016 A* conf
Markov Chain Analysis of Noise and Restart in Stochastic Local Search.
IJCAI
Ole J. Mengshoel, Youssef Ahres, Tong Yu
2016 — conf
Scalable Causal Learning for Predicting Adverse Events in Smart Buildings.
AAAI Workshop: AI for Smart Grids and Smart Buildings
Aniruddha Basak, Ole J. Mengshoel, Stefan Hosein, Rodney Martin
2016 J jnl
Self-Awareness of Cloud Applications.
CoRR
Alexandru Iosup, Xiaoyun Zhu, Arif Merchant, Eva Kalyvianaki, Martina Maggio, Simon Spinner, Tarek F. Abdelzaher, Ole J. Mengshoel, Sara Bouchenak
2016 — conf
Stochastic CoSaMP: Randomizing Greedy Pursuit for Sparse Signal Recovery.
ECML/PKDD (1)
Dipan K. Pal, Ole J. Mengshoel
2015 B conf
A Constrained Genetic Algorithm for Rebalancing of Services in Cloud Data Centers.
CLOUD
Priya Krishnan Sundararajan, Eugen Feller, Julien Forgeat, Ole J. Mengshoel
2014 — conf
Adaptive activity recognition with dynamic heterogeneous sensor fusion.
MobiCASE
Ming Zeng, Xiao Wang, Le T. Nguyen, Pang Wu, Ole J. Mengshoel, Joy Zhang
2014 J jnl
Adaptive generalized crowding for genetic algorithms.
Inf. Sci.
Ole J. Mengshoel, Severino F. Galán, Antonio de Dios
2014 — conf
Bayesian Network Parameter Learning using EM with Parameter Sharing.
BMA@UAI
Erik Reed, Ole J. Mengshoel
2014 — conf
Computing Probabilistic Optical Flow Using Markov Random Fields.
CompIMAGE
Dongzhen Piao, Prahlad G. Menon, Ole J. Mengshoel
2014 — conf
Convolutional Neural Networks for human activity recognition using mobile sensors.
MobiCASE
Ming Zeng, Le T. Nguyen, Bo Yu, Ole J. Mengshoel, Jiang Zhu, Pang Wu, Joy Zhang
2014 — conf
Darwin: a ground truth agnostic CAPTCHA generator using evolutionary algorithm.
GECCO (Companion)
Eric Yawei Chen, Lin-Shung Huang, Ole J. Mengshoel, Jason D. Lohn
2014 — conf
Detection of Myocardial Perfusion Defects Using First Pass Perfusion Cardiac MRI Data.
CompIMAGE
Stephen Kruzick, Ole J. Mengshoel, Prahlad G. Menon
2014 J jnl
Diagnosis for uncertain, dynamic and hybrid domains using Bayesian networks and arithmetic circuits.
Int. J. Approx. Reason.
Brian Ricks, Ole J. Mengshoel
2014 A conf
Feedback control for multi-modal optimization using genetic algorithms.
GECCO
Jun Shi, Ole J. Mengshoel, Dipan K. Pal
2013 J jnl
A Novel Mating Approach for Genetic Algorithms.
Evol. Comput.
Severino F. Galán, Ole J. Mengshoel, Rafael Pinter
2013 — conf
Adaptive Control of Apache Web Server.
Feedback Computing
Erik Reed, Abe Ishihara, Ole J. Mengshoel
2013 — conf
Exploring Multiple Dimensions of Parallelism in Junction Tree Message Passing.
UAI Application Workshops
Lu Zheng, Ole J. Mengshoel
2013 — conf
Latent Topic Analysis for Predicting Group Purchasing Behavior on the Social Web.
UAI Application Workshops
Feng-Tso Sun, Yi-Ting Yeh, Ole J. Mengshoel, Martin L. Griss
2013 — conf
Mobile Computing: Challenges and Opportunities for Autonomy and Feedback.
Feedback Computing
Ole J. Mengshoel, Bob Iannucci, Abe Ishihara
2013 Misc conf
Multi-focus and multi-level techniques for visualization and analysis of networks with thematic data.
Visualization and Data Analysis
Michele Cossalter, Ole J. Mengshoel, Ted Selker
2013 Misc conf
Multi-focus and multi-window techniques for interactive network exploration.
Visualization and Data Analysis
Priya Krishnan Sundararajan, Ole J. Mengshoel, Ted Selker
2013 A* conf
Optimizing parallel belief propagation in junction treesusing regression.
KDD
Lu Zheng, Ole J. Mengshoel
2013 — ed.
Proceedings of the 2013 UAI Application Workshops: Big Data meet Complex Models and Models for Spatial, Temporal and Network Data, Bellvue, Washington, USA
UAI Application Workshops
Russell G. Almond, Ole J. Mengshoel
2013 J jnl
Software health management with Bayesian networks.
Innov. Syst. Softw. Eng.
Johann Schumann, Timmy Mbaya, Ole J. Mengshoel, Knot Pipatsrisawat, Ashok N. Srivastava, Arthur Choi, Adnan Darwiche
2012 — conf
Accelerating Bayesian network parameter learning using Hadoop and MapReduce.
BigMine
Aniruddha Basak, Irina Brinster, Xianheng Ma, Ole J. Mengshoel
2012 A conf
Age-Layered Expectation Maximization for Parameter Learning in Bayesian Networks.
AISTATS
Avneesh Singh Saluja, Priya Krishnan Sundararajan, Ole J. Mengshoel
2012 J jnl
Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization
CoRR
Lu Zheng, Ole J. Mengshoel, Jike Chong
2012 — conf
Reactive Bayesian Network Computation using Feedback Control: An Empirical Study.
BMA
Ole J. Mengshoel, Abe Ishihara, Erik Reed
2012 J jnl
Reports of the AAAI 2011 Conference Workshops.
AI Mag.
Noa Agmon, Vikas Agrawal, David W. Aha, Yiannis Aloimonos, Donagh Buckley, Prashant Doshi, Christopher W. Geib, Floriana Grasso, Nancy L. Green, Benjamin Johnston, Burt Kaliski, Christopher Kiekintveld, Edith Law, Henry Lieberman, Ole J. Mengshoel, Ted Metzler, Joseph Modayil, Douglas W. Oard, Nilufer Onder, Barry O'Sullivan, Katerina Pastra, Doina Precup, Sowmya Ramachandran, Chris Reed, Sanem Sariel Talay, Ted Selker, Lokendra Shastri, Stephen F. Smith, Satinder Singh, Siddharth Srivastava, Gita Sukthankar, David C. Uthus, Mary-Anne Williams
2011 A conf
Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization.
UAI
Lu Zheng, Ole J. Mengshoel, Jike Chong
2011 J jnl
Initialization and Restart in Stochastic Local Search: Computing a Most Probable Explanation in Bayesian Networks.
IEEE Trans. Knowl. Data Eng.
Ole J. Mengshoel, David C. Wilkins, Dan Roth
2011 — conf
Multi-Fisheye for Interactive Visualization of Large Graphs.
Scalable Integration of Analytics and Visualization
Priya Krishnan Sundararajan, Ole J. Mengshoel, Ted Selker
2011 J jnl
Portfolios in Stochastic Local Search: Efficiently Computing Most Probable Explanations in Bayesian Networks.
J. Autom. Reason.
Ole J. Mengshoel, Dan Roth, David C. Wilkins
2011 — conf
Visualizing and Understanding Large-Scale Bayesian Networks.
Scalable Integration of Analytics and Visualization
Michele Cossalter, Ole J. Mengshoel, Ted Selker
2010 A conf
Generalized crowding for genetic algorithms.
GECCO
Severino F. Galán, Ole J. Mengshoel
2010 — conf
Inferring Complex Human Behavior Using a Non-obtrusive Mobile Sensing Platform.
MobiCASE
Bruce DeBruhl, Michele Cossalter, Roy Want, Ole J. Mengshoel, Pei Zhang
2010 J jnl
Probabilistic Model-Based Diagnosis: An Electrical Power System Case Study.
IEEE Trans. Syst. Man Cybern. Part A
Ole J. Mengshoel, Mark Chavira, Keith Cascio, Scott Poll, Adnan Darwiche, N. Serdar Uckun
2010 — conf
Towards software health management with bayesian networks.
FoSER
Johann Schumann, Ole J. Mengshoel, Ashok N. Srivastava, Adnan Darwiche
2010 J jnl
Understanding the scalability of Bayesian network inference using clique tree growth curves.
Artif. Intell.
Ole J. Mengshoel
2010 B conf
Who Guards the Guardians? - Toward V&V of Health Management Software - (Short Paper).
RV
Johann Schumann, Ashok N. Srivastava, Ole J. Mengshoel
2009 J jnl
Constraint Handling Using Tournament Selection: Abductive Inference in Partly Deterministic Bayesian Networks.
Evol. Comput.
Severino F. Galán, Ole J. Mengshoel
2008 A* conf
Diagnosing Faults in Electrical Power Systems of Spacecraft and Aircraft.
AAAI
Ole J. Mengshoel, Adnan Darwiche, Keith Cascio, Mark Chavira, Scott Poll, N. Serdar Uckun
2008 J jnl
The Crowding Approach to Niching in Genetic Algorithms.
Evol. Comput.
Ole J. Mengshoel, David E. Goldberg
2008 J jnl
Understanding the role of noise in stochastic local search: Analysis and experiments.
Artif. Intell.
Ole J. Mengshoel
2007 A* conf
Macroscopic Models of Clique Tree Growth for Bayesian Networks.
AAAI
Ole J. Mengshoel
2006 J jnl
Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering.
Artif. Intell.
Ole J. Mengshoel, David C. Wilkins, Dan Roth
2003 A conf
Information filtering using bayesian networks: effective user interfaces for aviation weather data.
IUI
Corinne Clinton Ruokangas, Ole J. Mengshoel
2000 B conf
CoRaven: model-based design of a cognitive tool for real-time intelligence monitoring and analysis.
SMC
Caroline C. Hayes, Robin R. Penner, Hakan Ergan, Li Lu, Nan Tu, Patricia M. Jones, Peter Asaro, Robin Bargar, Oleksandr Chernyshenko, Insook Choi, Nora Danner, Ole J. Mengshoel, Janet A. Sniezek, David C. Wilkins
1998 B conf
CoRAVEN: modeling and design of a multimedia intelligent infrastructure for collaborative intelligence analysis.
SMC
Patricia M. Jones, Caroline C. Hayes, David C. Wilkins, Robin Bargar, Janet A. Sniezek, Peter Asaro, Ole J. Mengshoel, D. Kessler, Martin J. Lucenti Jr., Insook Choi, Nan Tu, J. L. Schlabach
1998 — conf
Genetic Algorithms for Belief Network Inference: The Role of Scaling and Niching.
Evolutionary Programming
Ole J. Mengshoel, David C. Wilkins
1997 — conf
Belief Network Inference in Dynamic Environments.
AAAI/IAAI
Ole J. Mengshoel
1997 J jnl
Visual reasoning instructional software system.
Comput. Educ.
Carol Hubbard, Ole J. Mengshoel, Chris Moon, Yong Se Kim
1996 J jnl
Intelligent critiquing and tutoring of spatial reasoning skills.
Artif. Intell. Eng. Des. Anal. Manuf.
Ole J. Mengshoel, Sanjeev Chauhan, Yong Se Kim
1996 — conf
Multimedia Instructional Software for Visual Reasoning: Visual Reasoning Tutor (VRT).
ICMCS
Carol Hubbard, Ole J. Mengshoel, Chris Moon, Yong Se Kim
1996 — conf
ReCognition and Critiquing of Erroneous Agent Actions.
Agent Modeling
Ole J. Mengshoel, David C. Wilkins
1995 J jnl
A reformulation technique and tool for knowledge interchange during knowledge acquisition.
Int. J. Hum. Comput. Stud.
Ole J. Mengshoel
1993 B conf
Acquisition and Modeling of Uncertain, Incomplete and Time-Varying Knowldege.
EKAW
Ole J. Mengshoel, Ingeborg Sølvberg
1993 J jnl
Knowledge Validation: Principles and Practice.
IEEE Expert
Ole J. Mengshoel
1991 — conf
KVAT: A Tool for Incremental Knowledge Validation in a Knowledge Engineering Workbench.
EUROVAV
Ole J. Mengshoel