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Ole J. Mengshoel
Ole Jakob Mengshoel
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2020 – today
- 2024
- [j24]Shanmuga Venkatachalam, Harideep Nair, Ming Zeng, Cathy Tan, Ole J. Mengshoel, John Paul Shen:
Corrigendum: SemNet: Learning semantic attributes for human activity recognition with deep belief networks. Frontiers Big Data 6 (2024) - [j23]Jianpeng Chen, Yujing Wang, Ming Zeng, Zongyi Xiang, Bitan Hou, Tong Yu, Ole J. Mengshoel, Yazhou Ren:
Customizing graph neural networks using path reweighting. Inf. Sci. 674: 120681 (2024) - [c83]Xavier F. C. Sánchez-Díaz, Ole Jakob Mengshoel:
Estimating the Number of Local Optima in Multimodal Pseudo-Boolean Functions: Validation via Landscapes of Triangles. GECCO Companion 2024: 211-214 - [c82]Xavier F. C. Sánchez-Díaz, Corentin Masson, Ole Jakob Mengshoel:
Regularized Feature Selection Landscapes: An Empirical Study of Multimodality. PPSN (1) 2024: 409-426 - [c81]Erling Olweus, Ole J. Mengshoel:
Detecting and Segmenting Solar Farms in Satellite Imagery: A Study of Deep Neural Network Architectures. SCAI 2024: 19-28 - [c80]Jan-Marius Vatle, Bjørn-Olav H. Eriksen, Ole J. Mengshoel:
Green Urban Mobility with Autonomous Electric Ferries: Studies of Simulated Maritime Collisions using Adaptive Stress Testing. SCAI 2024: 47-56 - 2023
- [j22]Aniruddha Basak, Kevin M. Schmidt, Ole Jakob Mengshoel:
From data to interpretable models: machine learning for soil moisture forecasting. Int. J. Data Sci. Anal. 15(1): 9-32 (2023) - [c79]Eirik Lund Flogard, Ole Jakob Mengshoel, Ole Magnus Theisen, Kerstin Bach:
Creating Explainable Dynamic Checklists via Machine Learning to Ensure Decent Working Environment for All: A Field Study with Labour Inspections. ECAI 2023: 3218-3225 - [c78]Ole Jakob Mengshoel, Xavier F. C. Sánchez-Díaz, Fredrik Foss:
Controlling Hybrid Evolutionary Algorithms in Subset Selection for Multimodal Optimization. GECCO Companion 2023: 507-510 - [c77]Magnus Eide Schjølberg, Nicklas Paus Bekkevold, Xavier F. C. Sánchez-Díaz, Ole Jakob Mengshoel:
Comparing Metaheuristic Optimization Algorithms for Ambulance Allocation: An Experimental Simulation Study. GECCO 2023: 1454-1463 - [c76]Ellen Zhang Chang, Ole Jakob Mengshoel:
Generating Natural Language Dialogues Using Large Language Models with Adapters. NAIS 2023 - [c75]Xavier F. C. Sánchez-Díaz, Ole Jakob Mengshoel:
EvoLP.jl: A Playground for Evolutionary Computation in Julia. NAIS 2023 - 2022
- [j21]Shanmuga Venkatachalam, Harideep Nair, Ming Zeng, Cathy Tan, Ole J. Mengshoel, John Paul Shen:
SemNet: Learning semantic attributes for human activity recognition with deep belief networks. Frontiers Big Data 5 (2022) - [c74]Ole Jakob Mengshoel, Eirik Lund Flogard, Tong Yu, Jon Riege:
Understanding the cost of fitness evaluation for subset selection: Markov chain analysis of stochastic local search. GECCO 2022: 251-259 - [c73]Eirik Lund Flogard, Ole Jakob Mengshoel, Kerstin Bach:
Creating Dynamic Checklists via Bayesian Case-Based Reasoning: Towards Decent Working Conditions for All. IJCAI 2022: 5108-5114 - [c72]Eirik Lund Flogard, Ole Jakob Mengshoel:
A Dataset for Efforts Towards Achieving the Sustainable Development Goal of Safe Working Environments. NeurIPS 2022 - 2021
- [c71]Ole Jakob Mengshoel, Tong Yu, Jon Riege, Eirik Flogard:
Stochastic local search for efficient hybrid feature selection. GECCO Companion 2021: 133-134 - [c70]Fredrik Foss, Ole Jakob Mengshoel:
A multimethod approach to multimodal function optimization. GECCO Companion 2021: 235-236 - [c69]Eirik Høgdahl Skjærseth, Harald Vinje, Ole Jakob Mengshoel:
Novelty search for evolving interesting character mechanics for a two-player video game. GECCO Companion 2021: 321-322 - [c68]Jan Burak, Ole Jakob Mengshoel:
A multi-objective genetic algorithm for jacket optimization. GECCO Companion 2021: 1549-1556 - [c67]Eirik Flogard, Ole Jakob Mengshoel, Kerstin Bach:
Bayesian Feature Construction for Case-Based Reasoning: Generating Good Checklists. ICCBR 2021: 94-109 - [c66]Anna Haugsbø Hermansen, Ole Jakob Mengshoel:
Forecasting Ambulance Demand using Machine Learning: A Case Study from Oslo, Norway. SSCI 2021: 1-10 - [c65]Ingrid Ravn Turkerud, Ole Jakob Mengshoel:
Image Captioning using Deep Learning: Text Augmentation by Paraphrasing via Backtranslation. SSCI 2021: 1-10 - [d1]Eirik Flogard, Ole Jakob Mengshoel, Kerstin Bach:
Labour Inspection Checklist Content. IEEE DataPort, 2021 - 2020
- [j20]Ritchie Lee, Ole J. Mengshoel, Anshu Saksena, Ryan W. Gardner, Daniel Genin, Joshua Silbermann, Michael P. Owen, Mykel J. Kochenderfer:
Adaptive Stress Testing: Finding Likely Failure Events with Reinforcement Learning. J. Artif. Intell. Res. 69: 1165-1201 (2020) - [c64]Ole Jakob Mengshoel, Tong Yu, Ming Zeng:
Stochastic Local Search and Machine Learning: From Theory to Applications and Vice Versa. ECAI 2020: 2919-2920 - [c63]Tong Yu, Branislav Kveton, Zheng Wen, Ruiyi Zhang, Ole J. Mengshoel:
Graphical Models Meet Bandits: A Variational Thompson Sampling Approach. ICML 2020: 10902-10912 - [i11]Tong Yu, Branislav Kveton, Zheng Wen, Ruiyi Zhang, Ole J. Mengshoel:
Influence Diagram Bandits: Variational Thompson Sampling for Structured Bandit Problems. CoRR abs/2007.04915 (2020)
2010 – 2019
- 2019
- [c62]Harideep Nair, Cathy Tan, Ming Zeng, Ole J. Mengshoel, John Paul Shen:
AttriNet: learning mid-level features for human activity recognition with deep belief networks. UbiComp/ISWC Adjunct 2019: 510-517 - [i10]Bitan Hou, Yujing Wang, Ming Zeng, Shan Jiang, Ole J. Mengshoel, Yunhai Tong, Jing Bai:
Customized Graph Embedding: Tailoring the Embedding Vector to a Specific Application. CoRR abs/1911.09454 (2019) - 2018
- [j19]Severino F. Galán, Ole J. Mengshoel:
Neighborhood beautification: Graph layout through message passing. J. Vis. Lang. Comput. 44: 72-88 (2018) - [c61]Tong Yu, Shijia Pan, Susu Xu, Xinlei Chen, Mostafa Mirshekari, Jonathon Fagert, Hae Young Noh, Pei Zhang, Ole J. Mengshoel:
ILPC: Iterative Learning Using Physical Constraints in Real-World Sensing Data. AAAI Workshops 2018: 202-208 - [c60]Bing Liu, Tong Yu, Ian R. Lane, Ole J. Mengshoel:
Customized Nonlinear Bandits for Online Response Selection in Neural Conversation Models. AAAI 2018: 5245-5252 - [c59]Zhou Fang, Mulong Luo, Tong Yu, Ole J. Mengshoel, Mani B. Srivastava, Rajesh K. Gupta:
Mitigating Multi-tenant Interference in Continuous Mobile Offloading. CLOUD 2018: 20-36 - [c58]Aniruddha Basak, Ole J. Mengshoel, Kevin M. Schmidt, Chinmay Kulkarni:
Wetting and Drying of Soil: From Data to Understandable Models for Prediction. DSAA 2018: 303-312 - [c57]Anshu Rajendra, Ritwik Rajendra, Ole J. Mengshoel, Ming Zeng, Momina Haider:
Captioning with Language-Based Attention. DSAA 2018: 415-423 - [c56]Ming Zeng, Haoxiang Gao, Tong Yu, Ole J. Mengshoel, Helge Langseth, Ian R. Lane, Xiaobing Liu:
Understanding and improving recurrent networks for human activity recognition by continuous attention. UbiComp 2018: 56-63 - [c55]Ming Zeng, Tong Yu, Ole J. Mengshoel, Helen Qin, Chris Lee, John Paul Shen:
Improving Bag-Of-Words: Capturing Local Information for Motion-Based Activity Recognition. UbiComp/ISWC Adjunct 2018: 1345-1354 - [c54]Xiaoyi Fu, Xinqi Ren, Ole J. Mengshoel, Xindong Wu:
Stochastic Optimization for Market Return Prediction Using Financial Knowledge Graph. ICBK 2018: 25-32 - [c53]Ole J. Mengshoel, Priya Krishnan Sundararajan, Erik Reed, Dongzhen Piao, Briana Johnson:
Renewable Energy Integration: Bayesian Networks for Probabilistic State Estimation. DARE@PKDD/ECML 2018: 63-82 - [c52]Tong Yu, Branislav Kveton, Zheng Wen, Hung Bui, Ole J. Mengshoel:
SpectralLeader: Online Spectral Learning for Single Topic Models. ECML/PKDD (2) 2018: 379-395 - [c51]Ritchie Lee, Mykel J. Kochenderfer, Ole J. Mengshoel, Joshua Silbermann:
Interpretable Categorization of Heterogeneous Time Series Data. SDM 2018: 216-224 - [i9]Ming Zeng, Tong Yu, Xiao Wang, Le T. Nguyen, Ole J. Mengshoel, Ian R. Lane:
Semi-Supervised Convolutional Neural Networks for Human Activity Recognition. CoRR abs/1801.07827 (2018) - [i8]Aniruddha Basak, Kamalika Das, Ole J. Mengshoel:
CADDeLaG: Framework for distributed anomaly detection in large dense graph sequences. CoRR abs/1802.05421 (2018) - [i7]Ming Zeng, Haoxiang Gao, Tong Yu, Ole J. Mengshoel, Helge Langseth, Ian R. Lane, Xiaobing Liu:
Understanding and Improving Recurrent Networks for Human Activity Recognition by Continuous Attention. CoRR abs/1810.04038 (2018) - [i6]Ritchie Lee, Ole J. Mengshoel, Anshu Saksena, Ryan W. Gardner, Daniel Genin, Joshua Silbermann, Michael P. Owen, Mykel J. Kochenderfer:
Adaptive Stress Testing: Finding Failure Events with Reinforcement Learning. CoRR abs/1811.02188 (2018) - 2017
- [j18]Shijia Pan, Tong Yu, Mostafa Mirshekari, Jonathon Fagert, Amelie Bonde, Ole J. Mengshoel, Hae Young Noh, Pei Zhang:
FootprintID: Indoor Pedestrian Identification through Ambient Structural Vibration Sensing. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1(3): 89:1-89:31 (2017) - [c50]Ming Zeng, Tong Yu, Xiao Wang, Le T. Nguyen, Ole J. Mengshoel, Ian R. Lane:
Semi-supervised convolutional neural networks for human activity recognition. IEEE BigData 2017: 522-529 - [c49]Zhou Fang, Tong Yu, Ole J. Mengshoel, Rajesh K. Gupta:
QoS-Aware Scheduling of Heterogeneous Servers for Inference in Deep Neural Networks. CIKM 2017: 2067-2070 - [c48]Zhou Fang, Mulong Luo, Tong Yu, Ole J. Mengshoel, Mani B. Srivastava, Rajesh K. Gupta:
Mitigating multi-tenant interference on mobile offloading servers: poster abstract. SoCC 2017: 644 - [c47]Aniruddha Basak, Ole J. Mengshoel, Chinmay Kulkarni, Kevin M. Schmidt, Prathi Shastry, Rao Rapeta:
Optimizing the decomposition of time series using evolutionary algorithms: soil moisture analytics. GECCO 2017: 1073-1080 - [c46]Tong Yu, Branislav Kveton, Ole J. Mengshoel:
Thompson Sampling for Optimizing Stochastic Local Search. ECML/PKDD (1) 2017: 493-510 - [c45]Charlie Wang, Arpita Agrawal, Xiaojun Li, Tanima Makkad, Ejaz Veljee, Ole J. Mengshoel, Alvin Jude:
Content-based top-N recommendations with perceived similarity. SMC 2017: 1052-1057 - [c44]Xiao Wang, Tong Yu, Ole J. Mengshoel, Patrick Tague:
Towards continuous and passive authentication across mobile devices: an empirical study. WISEC 2017: 35-45 - [p4]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:
Synthesis and Verification of Self-aware Computing Systems. Self-Aware Computing Systems 2017: 337-373 - [p3]Martina Maggio, Tarek F. Abdelzaher, Lukas Esterle, Holger Giese, Jeffrey O. Kephart, Ole J. Mengshoel, Alessandro Vittorio Papadopoulos, Anders Robertsson, Katinka Wolter:
Self-adaptation for Individual Self-aware Computing Systems. Self-Aware Computing Systems 2017: 375-399 - [p2]Nikolas Herbst, Ayman A. Amin, Artur Andrzejak, Lars Grunske, Samuel Kounev, Ole J. Mengshoel, Priya Krishnan Sundararajan:
Online Workload Forecasting. Self-Aware Computing Systems 2017: 529-553 - [p1]Alexandru Iosup, Xiaoyun Zhu, Arif Merchant, Eva Kalyvianaki, Martina Maggio, Simon Spinner, Tarek F. Abdelzaher, Ole J. Mengshoel, Sara Bouchenak:
Self-awareness of Cloud Applications. Self-Aware Computing Systems 2017: 575-610 - [i5]Ritchie Lee, Mykel J. Kochenderfer, Ole J. Mengshoel, Joshua Silbermann:
Interpretable Categorization of Heterogeneous Time Series Data. CoRR abs/1708.09121 (2017) - [i4]Tong Yu, Branislav Kveton, Zheng Wen, Hung Bui, Ole J. Mengshoel:
SpectralFPL: Online Spectral Learning for Single Topic Models. CoRR abs/1709.07172 (2017) - [i3]Bing Liu, Tong Yu, Ian R. Lane, Ole J. Mengshoel:
Customized Nonlinear Bandits for Online Response Selection in Neural Conversation Models. CoRR abs/1711.08493 (2017) - 2016
- [c43]Aniruddha Basak, Ole J. Mengshoel, Stefan Hosein, Rodney Martin:
Scalable Causal Learning for Predicting Adverse Events in Smart Buildings. AAAI Workshop: AI for Smart Grids and Smart Buildings 2016 - [c42]Aniruddha Basak, Ole J. Mengshoel, Stefan Hosein, Rodney Martin, Jayasudha Jayakumaran, Mario Gurrola Morga, Ishwari Aghav:
Identifying Contributing Factors of Occupant Thermal Discomfort in a Smart Building. AAAI Workshop: AI for Smart Grids and Smart Buildings 2016 - [c41]Tong Yu, Ole J. Mengshoel, Alvin Jude, Eugen Feller, Julien Forgeat, Nimish Radia:
Incremental learning for matrix factorization in recommender systems. IEEE BigData 2016: 1056-1063 - [c40]Ole J. Mengshoel, Youssef Ahres, Tong Yu:
Markov Chain Analysis of Noise and Restart in Stochastic Local Search. IJCAI 2016: 639-646 - [c39]Tong Yu, Yong Zhuang, Ole J. Mengshoel, Osman Yagan:
Hybridizing Personal and Impersonal Machine Learning Models for Activity Recognition on Mobile Devices. MobiCASE 2016: 117-126 - [c38]Priya Krishnan Sundararajan, Ole J. Mengshoel:
A Genetic Algorithm for Learning Parameters in Bayesian Networks using Expectation Maximization. Probabilistic Graphical Models 2016: 511-522 - [c37]Dipan K. Pal, Ole J. Mengshoel:
Stochastic CoSaMP: Randomizing Greedy Pursuit for Sparse Signal Recovery. ECML/PKDD (1) 2016: 761-776 - [i2]Alexandru Iosup, Xiaoyun Zhu, Arif Merchant, Eva Kalyvianaki, Martina Maggio, Simon Spinner, Tarek F. Abdelzaher, Ole J. Mengshoel, Sara Bouchenak:
Self-Awareness of Cloud Applications. CoRR abs/1611.00323 (2016) - 2015
- [c36]Priya Krishnan Sundararajan, Eugen Feller, Julien Forgeat, Ole J. Mengshoel:
A Constrained Genetic Algorithm for Rebalancing of Services in Cloud Data Centers. CLOUD 2015: 653-660 - 2014
- [j17]Brian Ricks, Ole J. Mengshoel:
Diagnosis for uncertain, dynamic and hybrid domains using Bayesian networks and arithmetic circuits. Int. J. Approx. Reason. 55(5): 1207-1234 (2014) - [j16]Ole J. Mengshoel, Severino F. Galán, Antonio de Dios:
Adaptive generalized crowding for genetic algorithms. Inf. Sci. 258: 140-159 (2014) - [c35]Dongzhen Piao, Prahlad G. Menon, Ole J. Mengshoel:
Computing Probabilistic Optical Flow Using Markov Random Fields. CompIMAGE 2014: 241-247 - [c34]Stephen Kruzick, Ole J. Mengshoel, Prahlad G. Menon:
Detection of Myocardial Perfusion Defects Using First Pass Perfusion Cardiac MRI Data. CompIMAGE 2014: 248-254 - [c33]Eric Yawei Chen, Lin-Shung Huang, Ole J. Mengshoel, Jason D. Lohn:
Darwin: a ground truth agnostic CAPTCHA generator using evolutionary algorithm. GECCO (Companion) 2014: 165-166 - [c32]Jun Shi, Ole J. Mengshoel, Dipan K. Pal:
Feedback control for multi-modal optimization using genetic algorithms. GECCO 2014: 839-846 - [c31]Ming Zeng, Xiao Wang, Le T. Nguyen, Pang Wu, Ole J. Mengshoel, Joy Zhang:
Adaptive activity recognition with dynamic heterogeneous sensor fusion. MobiCASE 2014: 189-196 - [c30]Ming Zeng, Le T. Nguyen, Bo Yu, Ole J. Mengshoel, Jiang Zhu, Pang Wu, Joy Zhang:
Convolutional Neural Networks for human activity recognition using mobile sensors. MobiCASE 2014: 197-205 - [c29]Erik Reed, Ole J. Mengshoel:
Bayesian Network Parameter Learning using EM with Parameter Sharing. BMA@UAI 2014: 48-59 - 2013
- [j15]Severino F. Galán, Ole J. Mengshoel, Rafael Pinter:
A Novel Mating Approach for Genetic Algorithms. Evol. Comput. 21(2): 197-229 (2013) - [j14]Johann Schumann, Timmy Mbaya, Ole J. Mengshoel, Knot Pipatsrisawat, Ashok N. Srivastava, Arthur Choi, Adnan Darwiche:
Software health management with Bayesian networks. Innov. Syst. Softw. Eng. 9(4): 271-292 (2013) - [c28]Ole J. Mengshoel, Bob Iannucci, Abe Ishihara:
Mobile Computing: Challenges and Opportunities for Autonomy and Feedback. Feedback Computing 2013 - [c27]Erik Reed, Abe Ishihara, Ole J. Mengshoel:
Adaptive Control of Apache Web Server. Feedback Computing 2013 - [c26]Lu Zheng, Ole J. Mengshoel:
Optimizing parallel belief propagation in junction treesusing regression. KDD 2013: 757-765 - [c25]Feng-Tso Sun, Yi-Ting Yeh, Ole J. Mengshoel, Martin L. Griss:
Latent Topic Analysis for Predicting Group Purchasing Behavior on the Social Web. UAI Application Workshops 2013: 67-76 - [c24]Lu Zheng, Ole J. Mengshoel:
Exploring Multiple Dimensions of Parallelism in Junction Tree Message Passing. UAI Application Workshops 2013: 87-96 - [c23]Priya Krishnan Sundararajan, Ole J. Mengshoel, Ted Selker:
Multi-focus and multi-window techniques for interactive network exploration. Visualization and Data Analysis 2013: 86540O - [c22]Michele Cossalter, Ole J. Mengshoel, Ted Selker:
Multi-focus and multi-level techniques for visualization and analysis of networks with thematic data. Visualization and Data Analysis 2013: 865403 - [e1]Russell G. Almond, Ole J. Mengshoel:
Proceedings of the 2013 UAI Application Workshops: Big Data meet Complex Models and Models for Spatial, Temporal and Network Data, Bellvue, Washington, USA. CEUR Workshop Proceedings 1024, CEUR-WS.org 2013 [contents] - 2012
- [j13]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:
Reports of the AAAI 2011 Conference Workshops. AI Mag. 33(1): 57-70 (2012) - [c21]Aniruddha Basak, Irina Brinster, Xianheng Ma, Ole J. Mengshoel:
Accelerating Bayesian network parameter learning using Hadoop and MapReduce. BigMine 2012: 101-108 - [c20]Ole J. Mengshoel, Abe Ishihara, Erik Reed:
Reactive Bayesian Network Computation using Feedback Control: An Empirical Study. BMA 2012: 44-54 - [c19]Avneesh Singh Saluja, Priya Krishnan Sundararajan, Ole J. Mengshoel:
Age-Layered Expectation Maximization for Parameter Learning in Bayesian Networks. AISTATS 2012: 984-992 - [i1]Lu Zheng, Ole J. Mengshoel, Jike Chong:
Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization. CoRR abs/1202.3777 (2012) - 2011
- [j12]Ole J. Mengshoel, Dan Roth, David C. Wilkins:
Portfolios in Stochastic Local Search: Efficiently Computing Most Probable Explanations in Bayesian Networks. J. Autom. Reason. 46(2): 103-160 (2011) - [j11]Ole J. Mengshoel, David C. Wilkins, Dan Roth:
Initialization and Restart in Stochastic Local Search: Computing a Most Probable Explanation in Bayesian Networks. IEEE Trans. Knowl. Data Eng. 23(2): 235-247 (2011) - [c18]Michele Cossalter, Ole J. Mengshoel, Ted Selker:
Visualizing and Understanding Large-Scale Bayesian Networks. Scalable Integration of Analytics and Visualization 2011 - [c17]Priya Krishnan Sundararajan, Ole J. Mengshoel, Ted Selker:
Multi-Fisheye for Interactive Visualization of Large Graphs. Scalable Integration of Analytics and Visualization 2011 - [c16]Lu Zheng, Ole J. Mengshoel, Jike Chong:
Belief Propagation by Message Passing in Junction Trees: Computing Each Message Faster Using GPU Parallelization. UAI 2011: 822-830 - 2010
- [j10]Ole J. Mengshoel:
Understanding the scalability of Bayesian network inference using clique tree growth curves. Artif. Intell. 174(12-13): 984-1006 (2010) - [j9]Ole J. Mengshoel, Mark Chavira, Keith Cascio, Scott Poll, Adnan Darwiche, N. Serdar Uckun:
Probabilistic Model-Based Diagnosis: An Electrical Power System Case Study. IEEE Trans. Syst. Man Cybern. Part A 40(5): 874-885 (2010) - [c15]Severino F. Galán, Ole J. Mengshoel:
Generalized crowding for genetic algorithms. GECCO 2010: 775-782 - [c14]Bruce DeBruhl, Michele Cossalter, Roy Want, Ole J. Mengshoel, Pei Zhang:
Inferring Complex Human Behavior Using a Non-obtrusive Mobile Sensing Platform. MobiCASE 2010: 306-310 - [c13]Johann Schumann, Ashok N. Srivastava, Ole J. Mengshoel:
Who Guards the Guardians? - Toward V&V of Health Management Software - (Short Paper). RV 2010: 399-404 - [c12]Johann Schumann, Ole J. Mengshoel, Ashok N. Srivastava, Adnan Darwiche:
Towards software health management with bayesian networks. FoSER 2010: 331-336
2000 – 2009
- 2009
- [j8]Severino F. Galán, Ole J. Mengshoel:
Constraint Handling Using Tournament Selection: Abductive Inference in Partly Deterministic Bayesian Networks. Evol. Comput. 17(1): 55-88 (2009) - 2008
- [j7]Ole J. Mengshoel:
Understanding the role of noise in stochastic local search: Analysis and experiments. Artif. Intell. 172(8-9): 955-990 (2008) - [j6]Ole J. Mengshoel, David E. Goldberg:
The Crowding Approach to Niching in Genetic Algorithms. Evol. Comput. 16(3): 315-354 (2008) - [c11]Ole J. Mengshoel, Adnan Darwiche, Keith Cascio, Mark Chavira, Scott Poll, N. Serdar Uckun:
Diagnosing Faults in Electrical Power Systems of Spacecraft and Aircraft. AAAI 2008: 1699-1705 - 2007
- [c10]Ole J. Mengshoel:
Macroscopic Models of Clique Tree Growth for Bayesian Networks. AAAI 2007: 1256-1262 - 2006
- [j5]Ole J. Mengshoel, David C. Wilkins, Dan Roth:
Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering. Artif. Intell. 170(16-17): 1137-1174 (2006) - 2003
- [c9]Corinne Clinton Ruokangas, Ole J. Mengshoel:
Information filtering using bayesian networks: effective user interfaces for aviation weather data. IUI 2003: 280-283 - 2000
- [c8]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:
CoRaven: model-based design of a cognitive tool for real-time intelligence monitoring and analysis. SMC 2000: 1117-1122
1990 – 1999
- 1999
- [b1]Ole Jakob Mengshoel:
Efficient Bayesian Network Inference: Genetic Algorithms, Stochastic Local Search, and Abstraction. University of Illinois Urbana-Champaign, USA, 1999 - 1998
- [c7]