Select Lab Publications


2013
Qiang Yan, XingXing Wang, Qiang Xu, Dongying Kong, Danny Bickson, Quan Yuan, and Qing Yang (2013). "Predicting Search Engine Switching in WSCD 2013 Challenge." Workshop on Web Search Click Data (WSCD). bib pdf            
Siyuan Liu, Yisong Yue, and Ramayya Krishnan (2013). "Adaptive Collective Routing Using Gaussian Process Dynamic Congestion Models." ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). bib/abs pdf            
Stephane Ross, Jiaji Zhou, Yisong Yue, Debadeepta Dey, and J. Andrew Bagnell (2013). "Learning Policies for Contextual Submodular Prediction." International Conference on Machine Learning (ICML). bib/abs pdf long          
2012
Aapo Kyrola, Guy Blelloch, and Carlos Guestrin (2012). "GraphChi: Large-Scale Graph computation on Just a PC." Proceedings of the 10th USENIX Symposium onOperating Systems Design and Implementation (OSDI '12). bib pdf            
Joseph E. Gonzalez, Yucheng Low, Haijie Gu, Danny Bickson, and Carlos Guestrin (2012). "PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs." Proceedings of the 10th USENIX Symposium onOperating Systems Design and Implementation (OSDI '12). bib/abs pdf            
Dafna Shahaf, Carlos Guestrin, and Eric Horvitz (2012). "Metro Maps of Science." ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). bib pdf   talk      
Khalid El-Arini, Ulrich Paquet, Ralf Herbrich, Jurgen Van Gael, and Blaise Aguera y Arcas (2012). "Transparent User Models for Personalization." ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). bib/abs pdf   talk poster
Yisong Yue, Lavanya Marla, and Ramayya Krishnan (2012). "An Efficient Simulation-based Approach to Ambulance Fleet Allocation and Dynamic Redeployment." AAAI Conference on Artificial Intelligence (AAAI). bib/abs pdf     poster    
Joseph K. Bradley and Carlos Guestrin (2012). "Sample Complexity of Composite Likelihood." In Artificial Intelligence and Statistics (AISTATS). bib/abs pdf   talk poster  
Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin and Joseph M. Hellerstein (2012). "Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud." PVLDB. bib/abs pdf   talk      
Dafna Shahaf, Carlos Guestrin, and Eric Horvitz (2012). "Trains of Thought: Generating Information Maps." International World Wide Web Conference (WWW). bib/abs pdf   talk      
Yisong Yue, Sue Ann Hong, and Carlos Guestrin (2012). "Hierarchical Exploration for Accelerating Contextual Bandits." International Conference on Machine Learning (ICML). bib/abs pdf long talk poster  
Jonathan Huang, Ashish Kapoor, and Carlos Guestrin (2012). "Riffled Independence for Efficient Inference with Partial Ranking." Journal of Artificial Intelligence, 44, 491-532. bib/abs pdf            
Jonathan Huang and Carlos Guestrin (2012). "Uncovering the riffled independence structure of ranked data." Electronic Journal of Statistics, 6, 199-230. bib/abs pdf            
2011
Yisong Yue and Carlos Guestrin (2011). "Linear Submodular Bandits and their Application to Diversified Retrieval." In Advances in Neural Information Processing Systems (NIPS). bib/abs pdf long   poster    
Andreas Krause, Ram Rajagopal, Anupam Gupta, and Carlos Guestrin (2011). "Simultaneous Optimization of Sensor Placements and Balanced Schedules." IEEE Transactions on Automatic Control, 56(10), 2390-2405. bib/abs pdf            
Khalid El-Arini and Carlos Guestrin (2011). "Beyond Keyword Search: Discovering Relevant Scientific Literature." ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). bib/abs pdf long talk      
Jonathan Huang (2011). Probabilistic Reasoning and Learning on Permutations: Exploiting Structural Decompositions of the Symmetric Group. Doctoral dissertation, Carnegie Mellon University. bib/abs pdf   talk      
Jonathan Huang, Ashish Kapoor, and Carlos Guestrin (2011). "Efficient Probabilistic Inference with Partial Ranking Queries." The 27th Conference on Uncertainty in Artificial Intelligence (UAI 2011). bib/abs pdf long   poster  
Joseph K. Bradley, Aapo Kyrola, Danny Bickson, and Carlos Guestrin (2011). "Parallel Coordinate Descent for L1-Regularized Loss Minimization." International Conference on Machine Learning (ICML 2011). bib/abs pdf   talk        
Joseph Gonzalez, Yucheng Low, Arthur Gretton, and Carlos Guestrin (2011). "Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees." In Artificial Intelligence and Statistics (AISTATS). bib/abs pdf   talk      
Le Song, Arthur Gretton, Danny Bickson, Yucheng Low, and Carlos Guestrin (2011). "Kernel Belief Propagation." In Artificial Intelligence and Statistics (AISTATS). bib pdf   talk      
Andreas Krause, Carlos Guestrin, Anupam Gupta, and Jon Kleinberg (2011). "Robust Sensor Placements at Informative and Communication-Efficient Locations." ACM Transactions on Sensor Networks, 7(4), 31:1-31:33. bib/abs pdf            
Yao Wu, Qiang Yan, Danny Bickson, Yucheng Low, and Qing Yang (2011). "Efficient Multicore Collaborative Filtering." ACM KDD CUP workshop. bib/abs pdf            
Dafna Shahaf and Carlos Guestrin (2011). "Connecting Two (or Less) Dots: Discovering Structure in News Articles." ACM Transactions on Knowledge Discovery from Data. bib              
D. Bickson, D. Baron, A. Ihler, H. Avissar, and D. Dolev (2011). "Fault identification via non-parametric belief propagation." IEEE Tran. on Signal Processing. bib/abs pdf            
Yucheng Low, Deepak Agarwal, and Alex J. Smola (2011). "Multiple domain user personalization." KDD '11: Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 123-131). bib/abs pdf   talk      
2010
Anton Chechetka and Carlos Guestrin (2010). "Evidence-Specific Structures for Rich Tractable CRFs." In Advances in Neural Information Processing Systems (NIPS). bib/abs pdf     poster  
Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin, and Joseph M. Hellerstein (2010). "GraphLab: A New Parallel Framework for Machine Learning." Conference on Uncertainty in Artificial Intelligence (UAI). bib/abs pdf   talk      
Jonathan Huang and Carlos Guestrin (2010). "Learning Hierarchical Riffle Independent Groupings from Rankings." International Conference on Machine Learning (ICML 2010). bib/abs pdf   talk      
Le Song, Byron Boot, Sajid Siddiqi, Geoff Gordon, and Alex Smola (2010). "Hilbert Space Embeddings of Hidden Markov Models." International Conference on Machine Learning (ICML 2010). Best Paper Award. bib pdf   talk      
Joseph K. Bradley and Carlos Guestrin (2010). "Learning Tree Conditional Random Fields." International Conference on Machine Learning (ICML 2010). bib/abs pdf   talk        
Le Song, Arthur Gretton, and Carlos Guestrin (2010). "Nonparametric Tree Graphical Models via Kernel Embeddings." In Artificial Intelligence and Statistics (AISTATS). bib pdf     poster  
Anton Chechetka and Carlos Guestrin (2010). "Focused Belief Propagation for Query-Specific Inference." In Artificial Intelligence and Statistics (AISTATS). Best Student Paper Award. bib/abs pdf   talk      
A. Gretton and L. Gyorfi (2010). "Consistent Nonparametric Tests of Independence." Journal of Machine Learning Research, 11, 1391-1423. bib pdf            
Dafna Shahaf and Carlos Guestrin (2010). "Connecting the Dots Between News Articles." ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Best Paper Award. bib/abs pdf   talk      
Danny Bickson and Carlos Guestrin (2010). "Inference with Multivariate Heavy-Tails in Linear Models." Neural Information Processing Systems (NIPS). bib pdf   talk      
B. Sriperumbudur, A. Gretton, K. Fukumizu, B. Schoelkopf, and G. Lanckriet (2010). "Hilbert Space Embeddings and Metrics on Probability Measures." Journal of Machine Learning Research, 11, 1517-1561. bib pdf            
2009
Jonathan Huang and Carlos Guestrin (2009). "Riffled Independence for Ranked Data." In Advances in Neural Information Processing Systems (NIPS). bib/abs pdf long   poster  
B. Sriperumbudur, K. Fukumizu, A. Gretton, G. Lanckriet, and B. Scholkopf (2009). "Kernel choice and classifiability for RKHS embeddings of probability distributions." In Advances in Neural Information Processing Systems (NIPS). Honorable Mention for Outstanding Student Paper. bib pdf            
R. Tillman, A. Gretton, and P. Spirtes (2009). "Nonlinear directed acyclic structure learning with weakly additive noise models." In Advances in Neural Information Processing Systems (NIPS). bib pdf            
A. Gretton, K. Fukumizu, Z. Harchaoui, and B. Sriperumbudur (2009). "A Fast, Consistent Kernel Two-Sample Test." In Advances in Neural Information Processing Systems (NIPS). bib pdf            
Joseph Gonzalez, Yucheng Low, Carlos Guestrin, and David O'Hallaron (2009). "Distributed Parallel Inference on Large Factor Graphs." Conference on Uncertainty in Artificial Intelligence (UAI). bib/abs pdf   talk      
Geoff Gordon, Sue Ann Hong, and Miroslav Dudik (2009). "First-Order Mixed Integer Linear Programming." Conference on Uncertainty in Artificial Intelligence (UAI). bib/abs pdf            
Khalid El-Arini, Gaurav Veda, Dafna Shahaf, and Carlos Guestrin (2009). "Turning Down the Noise in the Blogosphere." ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). bib/abs pdf long talk      
Jonathan Huang, Carlos Guestrin, and Leonidas Guibas (2009). "Fourier Theoretic Probabilistic Inference over Permutations." Journal of Machine Learning Research (JMLR), 10, 997-1070. bib/abs pdf            
Joseph Gonzalez, Yucheng Low, and Carlos Guestrin (2009). "Residual Splash for Optimally Parallelizing Belief Propagation." In Artificial Intelligence and Statistics (AISTATS). bib/abs pdf   talk      
Jonathan Huang, Carlos Guestrin, Xiaoye Jiang, and Leonidas Guibas (2009). "Exploiting Probabilistic Independence for Permutations." In Artificial Intelligence and Statistics (AISTATS). bib/abs pdf long talk        
Dafna Shahaf, Anton Chechetka, and Carlos Guestrin (2009). "Learning Thin Junction Trees via Graph Cuts." In Artificial Intelligence and Statistics (AISTATS). bib/abs pdf   talk      
Alexandra Meliou, Carlos Guestrin, and Joseph M. Hellerstein (2009). "Approximating Sensor Network Queries Using In-Network Summaries." Information Processing in Sensor Networks (IPSN). bib/abs pdf   talk      
Andreas Krause, Ram Rajagopal, Anupam Gupta, and Carlos Guestrin (2009). "Simultaneous Placement and Scheduling of Sensors." Information Processing in Sensor Networks (IPSN). bib/abs pdf   talk        
A. Gretton, K. Fukumizu, and B. Sriperumbudur (2009). "Discussion of: Brownian distance covariance." The Annals of Applied Statistics, 3(4), 1285-1294. bib pdf            
Amarjeet Singh, Andreas Krause, Carlos Guestrin, and William Kaiser (2009). "Efficient Informative Sensing using Multiple Robots." Journal of Artificial Intelligence Research (JAIR), 34, 707-755. bib/abs pdf            
Andreas Krause and Carlos Guestrin (2009). "Optimal Value of Information in Graphical Models." Journal of Artificial Intelligence Research (JAIR), 35, 557-591. bib/abs pdf            
Andreas Krause and Carlos Guestrin (2009). "Optimizing Sensing: From Water to the Web." IEEE Computer Magazine, 42(8), 38-45. bib/abs pdf            
2008
Andreas Krause (2008). Optimizing Sensing: Theory and Applications. Doctoral dissertation, Carnegie Mellon University. Honorable Mention for SCS Distinguished Dissertation Award. bib/abs pdf   talk        
Andreas Krause, Brendan McMahan, Carlos Guestrin, and Anupam Gupta (2008). "Robust Submodular Observation Selection." Journal of Machine Learning Research (JMLR), 9, 2761-2801. bib/abs pdf            
Andreas Krause, Jure Leskovec, Carlos Guestrin, Jeanne VanBriesen, and Christos Faloutsos (2008). "Efficient Sensor Placement Optimization for Securing Large Water Distribution Networks." Journal of Water Resources Planning and Management, 134(6), 516-526. (Draft; full version available here). Winner of the Best Research Paper Award. bib/abs pdf            
Stanislav Funiak, Padmanabhan Pillai, Michael P. Ashley-Rollman, Jason D. Campbell, and Seth Copen Goldstein (2008). "Distributed Localization of Modular Robot Ensembles." Proceedings of Robotics: Science and Systems (RSS). bib/abs pdf   talk        
Jonathan Huang, Carlos Guestrin, and Leonidas Guibas (2008). "Inference for Distributions over the Permutation Group." Technical report. Machine Learning Department, Carnegie Mellon University, CMU-ML-08-108. bib/abs pdf            
Andreas Krause, Ajit Singh, and Carlos Guestrin (2008). "Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies." Journal of Machine Learning Research (JMLR), 9, 235-284. bib/abs pdf            
Ajit P. Singh and Geoff J. Gordon (2008). "A Unified View of Matrix Factorization Models." Machine Learning and Knowledge Discovery in Databases, European Conference (ECML/PKDD). bib/abs pdf            
Ajit P. Singh and Geoffrey J. Gordon (2008). "Relational Learning via Collective Matrix Factorization." Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD). bib/abs pdf long          
2007
Jonathan Huang, Carlos Guestrin, and Leonidas Guibas (2007). "Efficient Inference for Distributions on Permutations." In Advances in Neural Information Processing Systems (NIPS). Honorable Mention for Outstanding Student Paper. bib/abs pdf   talk poster  
Anton Chechetka and Carlos Guestrin (2007). "Efficient Principled Learning of Thin Junction Trees." In Advances in Neural Information Processing Systems (NIPS). bib/abs pdf     poster  
Sajid Siddiqi, Geoffrey J. Gordon, and Andrew W. Moore (2007). "Fast State Discovery for HMM Model Selection and Learning." In Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AI-STATS). bib pdf   talk        
Andreas Krause, Brendan McMahan, Carlos Guestrin, and Anupam Gupta (2007). "Selecting Observations Against Adversarial Objectives." In Advances in Neural Information Processing Systems (NIPS). bib/abs pdf     poster  
Purnamrita Sarkar, Sajid Siddiqi, and Geoffrey J. Gordon (2007). "A Latent Space Approach to Dynamic Embedding of Cooccurrence Data." In Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AI-STATS). bib pdf   talk        
Sajid Siddiqi, Byron Boots, and Geoffrey J. Gordon (2007). "A Constraint Generation Approach to Learning Stable Linear Dynamical Systems." In Advances in Neural Information Processing Systems (NIPS). bib pdf   talk        
Bilge Mutlu, Andreas Krause, Jodi Forlizzi, Carlos Guestrin, and Jessica Hodgins (2007). "Robust, Low-cost, Non-intrusive Sensing and Recognition of Seated Postures." ACM Symposium on User Interface Software and Technology (UIST). bib/abs pdf   talk        
Jure Leskovec, Andreas Krause, Carlos Guestrin, Christos Faloutsos, Jeanne VanBriesen, and Natalie Glance (2007). "Cost-effective Outbreak Detection in Networks." ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) (pp. 420-429). Winner of the Best Paper Award. bib/abs pdf long talk        
Andreas Krause and Carlos Guestrin (2007). "Near-optimal Observation Selection using Submodular Functions." National Conference on Artificial Intelligence (AAAI), Nectar track. bib/abs pdf   talk        
Alexandra Meliou, Andreas Krause, Carlos Guestrin, and Joseph M. Hellerstein (2007). "Nonmyopic Informative Path Planning in Spatio-Temporal Models." National Conference on Artificial Intelligence (AAAI). bib/abs pdf   talk        
Andreas Krause and Carlos Guestrin (2007). "Nonmyopic active learning of Gaussian processes: an exploration-exploitation approach." International Conference on Machine Learning (ICML). bib/abs pdf long talk poster  
Amarjeet Singh, Andreas Krause, Carlos Guestrin, William Kaiser, and Maxim Batalin (2007). "Efficient Planning of Informative Paths for Multiple Robots." International Joint Conference on Artificial Intelligence (IJCAI). bib/abs pdf long talk        
2006
Stanislav Funiak, Carlos Guestrin, Mark Paskin, and Rahul Sukthankar (2006). "Distributed Inference in Dynamical Systems." Advances in Neural Information Processing Systems (NIPS 19). bib/abs pdf     poster  
Andreas Krause, Jure Leskovec, and Carlos Guestrin (2006). "Data Association for Topic Intensity Tracking." International conference on Machine learning (ICML). bib/abs pdf long talk        
Alexandra Meliou, David Chu, Carlos Guestrin, Joseph Hellerstein, and Wei Hong (2006). "Data Gathering Tours in Sensor Networks." Fifth International Conference on Information Processing in Sensor Networks (IPSN). bib/abs pdf   talk        
Stanislav Funiak, Carlos Guestrin, Rahul Sukthankar, and Mark Paskin (2006). "Distributed Localization of Networked Cameras." Fifth International Conference on Information Processing in Sensor Networks (IPSN'06) (pp. 34-42). Movies of results. bib/abs pdf   talk        
Andreas Krause, Carlos Guestrin, Anupam Gupta, and Jon Kleinberg (2006). "Near-optimal Sensor Placements: Maximizing Information while Minimizing Communication Cost." International Symposium on Information Processing in Sensor Networks (IPSN). Winner of the Best Paper Award. bib/abs pdf   talk        
Branislav Kveton, Milos Hauskrecht, and Carlos Guestrin (2006). "Solving Factored MDPs with Hybrid State and Action Variables." Journal of Artificial Intelligence Research (JAIR), 27. bib/abs pdf            
2005
Sajid Siddiqi and Andrew W. Moore (2005). "Fast Inference and Learning in Large State Space HMMs." Proceedings of the Twenty-Second International Conference on Machine Learning (ICML). bib pdf   talk        
Amol Deshpande, Carlos Guestrin, Sam Madden, Joseph Hellerstein, and Wei Hong (2005). "Model-based Approximate Querying in Sensor Networks." International Journal on Very Large Data Bases (VLDB), 14(4), 417-443. bib/abs pdf            
Vipul Singhvi, Andreas Krause, Carlos Guestrin, Jim Garrett, and H. Scott Matthews (2005). "Intelligent Light Control using Sensor Networks." ACM Conference on Embedded Networked Sensor Systems (SenSys). bib/abs pdf   talk        
Carlos Guestrin, Andreas Krause, and Ajit Singh (2005). "Near-optimal Sensor Placements in Gaussian Processes." International Conference on Machine Learning (ICML). Winner of the Best Paper Runner-up Award. bib/abs pdf long talk poster  
Ben Taskar, Vassil Chatalbashev, Daphne Koller, and Carlos Guestrin (2005). "Learning Structured Prediction Models: A Large Margin Approach." 22nd International Conference on Machine Learning (ICML). bib/abs pdf            
Andreas Krause and Carlos Guestrin (2005). "Near-optimal Value of Information in Graphical Models." Conference on Uncertainty in Artificial Intelligence (UAI). Winner of the Best Paper Runner-up Award. bib/abs pdf   talk        
Andreas Krause and Carlos Guestrin (2005). "Optimal Nonmyopic Value of Information in Graphical Models - Efficient Algorithms and Theoretical Limits." International Joint Conference on Artificial Intelligence (IJCAI). bib/abs pdf   talk        
Bhaskara Marthi, David Latham, Stuart Russell, and Carlos Guestrin (2005). "Concurrent Hierarchical Reinforcement Learning." Nineteenth International Joint Conference on Artificial Intelligence (IJCAI). bib/abs pdf            
Mark Paskin, Carlos Guestrin, and Jim McFadden (2005). "A Robust Architecture for Distributed Inference in Sensor Networks." Fourth International Conference on Information Processing in Sensor Networks (IPSN). Winner of the Best Paper Award. bib/abs pdf            
Amol Deshpande, Carlos Guestrin, Wei Hong, and Sam Madden (2005). "Exploiting Correlated Attributes in Acquisitional Query Processing." 21st International Conference on Data Engineering (ICDE). bib/abs pdf            
Amol Deshpande, Carlos Guestrin, and Sam Madden (2005). "Using Probabilistic Models for Data Management in Acquisitional Environments." 2nd Biennial Conference on Innovative Data Systems Research (CIDR). bib/abs pdf            
2004
Amol Deshpande, Carlos Guestrin, Sam Madden, Joseph Hellerstein, and Wei Hong (2004). "Model-Driven Data Acquisition in Sensor Networks." 30th International Conference on Very Large Data Bases (VLDB). Winner of the Best Paper Award. bib/abs pdf   talk        
Mark Paskin and Carlos Guestrin (2004). "Robust Probabilistic Inference in Distributed Systems." Twentieth Conference on Uncertainty in Artificial Intelligence (UAI). bib/abs pdf            
Carlos Guestrin, Milos Hauskrecht, and Branislav Kveton (2004). "Solving Factored MDPs with Continuous and Discrete Variables." Twentieth Conference on Uncertainty in Artificial Intelligence (UAI). bib/abs pdf     poster  
Carlos Guestrin, Peter Bodik, Romain Thibaux, Mark Paskin, and Samuel Madden (2004). "Distributed Regression: an Efficient Framework for Modeling Sensor Network Data." Information Processing in Sensor Networks (IPSN). bib/abs pdf   talk        
2003
Ben Taskar, Carlos Guestrin, and Daphne Koller (2003). "Max-Margin Markov Networks." Advances in Neural Information Processing Systems (NIPS). Winner of the Best Paper Award. bib/abs pdf            
Carlos Guestrin, Daphne Koller, Chris Gearhart, and Neal Kanodia (2003). "Generalizing Plans to New Environments in Relational MDPs." International Joint Conference on Artificial Intelligence (IJCAI). Videos of Freecraft results and RMDP model details. Freecraft interface and challence problems. bib/abs pdf   talk        
Carlos Guestrin (2003). Planning Under Uncertainty in Complex Structured Environments. Doctoral dissertation, Computer Science Department, Stanford University. bib/abs pdf   talk        
Carlos Guestrin, Daphne Koller, Ronald Parr, and Shobha Venkataraman (2003). "Efficient Solution Algorithms for Factored MDPs." Journal of Artificial Intelligence Research (JAIR), 19, 399-468. Winner of the 2007 IJCAI-JAIR Best Paper Prize. bib/abs pdf            
M. Serkan Apaydin, Douglas L. Brutlag, Carlos Guestrin, David Hsu, Jean-Claude Latombe, and Chris Varma (2003). "Stochastic Roadmap Simulation: An Efficient Representation and Algorithm for Analyzing Molecular Motion." Journal of Computational Biology (JCB), 10(3-4), 257-281. bib/abs pdf            
2002
Carlos Guestrin and Geoffrey Gordon (2002). "Distributed Planning in Hierarchical Factored MDPs." Eighteenth Conference on Uncertainty in Artificial Intelligence (UAI) (pp. 197-206). bib/abs pdf   talk        
Carlos Guestrin, Relu Patrascu, and Dale Schuurmans (2002). "Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs." Nineteenth International Conference on Machine Learning (ICML) (pp. 235-242). bib/abs pdf            
Carlos Guestrin, Shobha Venkataraman, and Daphne Koller (2002). "Context Specific Multiagent Coordination and Planning with Factored MDPs." Eighteenth National Conference on Artificial Intelligence (AAAI) (pp. 253-259). bib/abs pdf     poster  
Carlos Guestrin, Michail Lagoudakis, and Ronald Parr (2002). "Coordinated Reinforcement Learning." Nineteenth International Conference on Machine Learning (ICML) (pp. 227-234). bib/abs pdf            
M. Serkan Apaydin, Douglas L. Brutlag, Carlos Guestrin, David Hsu, and Jean-Claude Latombe (2002). "Stochastic Roadmap Simulation: An Efficient Representation and Algorithm for Analyzing Molecular Motion." Sixth Annual International Conference on Research in Computational Molecular Biology (RECOMB) (pp. 12-21). Project page. bib/abs pdf            
M. Serkan Apaydin, Carlos Guestrin, Chris Varma, Douglas L. Brutlag, and Jean-Claude Latombe (2002). "Stochastic Roadmap Simulation for the Study of Ligand-Protein Interactions." Bioinformatics, 18((Suppl. 2)), S18 - S26. bib/abs pdf            
2001
Carlos Guestrin, Daphne Koller, and Ronald Parr (2001). "Multiagent Planning with Factored MDPs." Advances in Neural Information Processing Systems (NIPS) (pp. 1523-1530). bib/abs pdf   talk poster  
Carlos Guestrin, Daphne Koller, and Ronald Parr (2001). "Max-norm Projections for Factored MDPs." International Joint Conference on Artificial Intelligence (IJCAI) (pp. 673-680). bib/abs pdf   talk        
Carlos Guestrin, Daphne Koller, and Ronald Parr (2001). "Solving Factored POMDPs with Linear Value Functions." IJCAI-01 workshop on Planning under Uncertainty and Incomplete Information (pp. 67-75). bib/abs pdf   talk        
Carlos Guestrin and Dirk Ormoneit (2001). "Robust Combination of Local Controllers." 17th Conference on Uncertainty in Artificial Intelligence (UAI) (pp. 178-185). Project demo page. bib/abs pdf   talk        
2000
Fabio Cozman, Eric Krotkov, and Carlos Guestrin (2000). "Outdoor Position Estimation for Planetary Rovers." Autonomous Robots Journal, 9(2), 135-150. bib pdf            
1998
Carlos Guestrin, Fabio Cozman, and Eric Krotkov (1998). "Fast Software Image Stabilization with Color Registration." IEEE International Conference on Intelligent Robots and Systems (IROS 1998) (pp. 19-24). bib pdf