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ORCIDCarlos Guestrin
2020 – today
- 2025
[j26]Mert Yüksekgönül
, Federico Bianchi, Joseph Boen, Sheng Liu, Pan Lu, Zhi Huang, Carlos Guestrin, James Zou:
Optimizing generative AI by backpropagating language model feedback. Nat. 639(8055): 609-616 (2025)- [c117]Irena Gao, Percy Liang, Carlos Guestrin:
Model Equality Testing: Which Model is this API Serving? ICLR 2025 - [c116]Nicole Meister, Carlos Guestrin, Tatsunori Hashimoto:
Benchmarking Distributional Alignment of Large Language Models. NAACL (Long Papers) 2025: 24-49 - [i65]Karan Dalal, Daniel Koceja, Gashon Hussein, Jiarui Xu, Yue Zhao, Youjin Song, Shihao Han, Ka Chun Cheung, Jan Kautz, Carlos Guestrin, Tatsunori Hashimoto, Sanmi Koyejo, Yejin Choi, Yu Sun, Xiaolong Wang:
One-Minute Video Generation with Test-Time Training. CoRR abs/2504.05298 (2025) - [i64]Judy Hanwen Shen, Carlos Guestrin:
Societal Impacts Research Requires Benchmarks for Creative Composition Tasks. CoRR abs/2504.06549 (2025) - 2024
- [j25]Liana Patel, Peter Kraft, Carlos Guestrin, Matei Zaharia:
ACORN: Performant and Predicate-Agnostic Search Over Vector Embeddings and Structured Data. Proc. ACM Manag. Data 2(3): 120 (2024) - [c115]Rishabh Ranjan, Saurabh Garg, Mrigank Raman, Carlos Guestrin, Zachary C. Lipton:
Post-Hoc Reversal: Are We Selecting Models Prematurely? NeurIPS 2024 - [c114]Theodora Worledge, Judy Hanwen Shen, Nicole Meister, Caleb Winston, Carlos Guestrin:
Unifying Corroborative and Contributive Attributions in Large Language Models. SaTML 2024: 665-683 - [c113]Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, Tatsunori Hashimoto:
Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks. SP (Workshops) 2024: 132-143 - [i63]Liana Patel, Peter Kraft, Carlos Guestrin, Matei Zaharia:
ACORN: Performant and Predicate-Agnostic Search Over Vector Embeddings and Structured Data. CoRR abs/2403.04871 (2024) - [i62]Rishabh Ranjan, Saurabh Garg, Mrigank Raman, Carlos Guestrin, Zachary Chase Lipton:
Post-Hoc Reversal: Are We Selecting Models Prematurely? CoRR abs/2404.07815 (2024) - [i61]Mert Yüksekgönül, Federico Bianchi, Joseph Boen, Sheng Liu, Zhi Huang, Carlos Guestrin, James Zou:
TextGrad: Automatic "Differentiation" via Text. CoRR abs/2406.07496 (2024) - [i60]Yu Sun, Xinhao Li, Karan Dalal, Jiarui Xu, Arjun Vikram, Genghan Zhang, Yann Dubois, Xinlei Chen, Xiaolong Wang, Sanmi Koyejo, Tatsunori Hashimoto, Carlos Guestrin:
Learning to (Learn at Test Time): RNNs with Expressive Hidden States. CoRR abs/2407.04620 (2024) - [i59]Liana Patel, Siddharth Jha, Carlos Guestrin, Matei Zaharia:
LOTUS: Enabling Semantic Queries with LLMs Over Tables of Unstructured and Structured Data. CoRR abs/2407.11418 (2024) - [i58]Asim Biswal, Liana Patel, Siddarth Jha, Amog Kamsetty, Shu Liu, Joseph E. Gonzalez, Carlos Guestrin, Matei Zaharia:
Text2SQL is Not Enough: Unifying AI and Databases with TAG. CoRR abs/2408.14717 (2024) - [i57]Irena Gao, Percy Liang, Carlos Guestrin:
Model Equality Testing: Which Model Is This API Serving? CoRR abs/2410.20247 (2024) - [i56]Nicole Meister, Carlos Guestrin, Tatsunori Hashimoto:
Benchmarking Distributional Alignment of Large Language Models. CoRR abs/2411.05403 (2024) - [i55]Theodora Worledge, Tatsunori Hashimoto, Carlos Guestrin:
The Extractive-Abstractive Spectrum: Uncovering Verifiability Trade-offs in LLM Generations. CoRR abs/2411.17375 (2024) - [i54]Edward Chen, Natalie Dullerud, Thomas Niedermayr, Elizabeth Kidd, Ransalu Senanayake, Pang Wei Koh, Sanmi Koyejo, Carlos Guestrin:
MoSH: Modeling Multi-Objective Tradeoffs with Soft and Hard Bounds. CoRR abs/2412.06154 (2024) - [i53]Luke Bailey, Alex Serrano, Abhay Sheshadri, Mikhail Seleznyov, Jordan Taylor, Erik Jenner, Jacob Hilton, Stephen Casper, Carlos Guestrin, Scott Emmons:
Obfuscated Activations Bypass LLM Latent-Space Defenses. CoRR abs/2412.09565 (2024) - 2023
- [c112]Yann Dubois, Chen Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto:
AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. NeurIPS 2023 - [c111]Mert Yüksekgönül, Linjun Zhang, James Y. Zou, Carlos Guestrin:
Beyond Confidence: Reliable Models Should Also Consider Atypicality. NeurIPS 2023 - [i52]Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, Tatsunori Hashimoto:
Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks. CoRR abs/2302.05733 (2023) - [i51]Yann Dubois, Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto:
AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. CoRR abs/2305.14387 (2023) - [i50]Mert Yüksekgönül, Linjun Zhang, James Zou, Carlos Guestrin:
Beyond Confidence: Reliable Models Should Also Consider Atypicality. CoRR abs/2305.18262 (2023) - [i49]Yu Sun, Xinhao Li, Karan Dalal, Chloe Hsu, Sanmi Koyejo, Carlos Guestrin, Xiaolong Wang, Tatsunori Hashimoto, Xinlei Chen:
Learning to (Learn at Test Time). CoRR abs/2310.13807 (2023) - [i48]Theodora Worledge, Judy Hanwen Shen, Nicole Meister, Caleb Winston, Carlos Guestrin:
Unifying Corroborative and Contributive Attributions in Large Language Models. CoRR abs/2311.12233 (2023) - 2021
- [c110]Mitchell Wortsman, Maxwell Horton, Carlos Guestrin, Ali Farhadi, Mohammad Rastegari:
Learning Neural Network Subspaces. ICML 2021: 11217-11227 - [c109]Marco Túlio Ribeiro, Tongshuang Wu, Carlos Guestrin, Sameer Singh:
Beyond Accuracy: Behavioral Testing of NLP Models with Checklist (Extended Abstract). IJCAI 2021: 4824-4828 - [i47]Mitchell Wortsman, Maxwell Horton, Carlos Guestrin, Ali Farhadi, Mohammad Rastegari:
Learning Neural Network Subspaces. CoRR abs/2102.10472 (2021) - 2020
- [j24]Michael Fire, Carlos Guestrin:
The rise and fall of network stars: Analyzing 2.5 million graphs to reveal how high-degree vertices emerge over time. Inf. Process. Manag. 57(2): 102041 (2020) - [c108]Marco Túlio Ribeiro, Tongshuang Wu, Carlos Guestrin, Sameer Singh:
Beyond Accuracy: Behavioral Testing of NLP Models with CheckList. ACL 2020: 4902-4912 - [c107]Tyler B. Johnson, Pulkit Agrawal, Haijie Gu, Carlos Guestrin:
AdaScale SGD: A User-Friendly Algorithm for Distributed Training. ICML 2020: 4911-4920 - [i46]Marco Túlio Ribeiro, Tongshuang Wu, Carlos Guestrin, Sameer Singh:
Beyond Accuracy: Behavioral Testing of NLP models with CheckList. CoRR abs/2005.04118 (2020) - [i45]Emilien Dupont, Miguel Ángel Bautista, Alex Colburn, Aditya Sankar, Carlos Guestrin, Josh M. Susskind, Qi Shan:
Equivariant Neural Rendering. CoRR abs/2006.07630 (2020) - [i44]Shuangfei Zhai, Walter Talbott, Miguel Ángel Bautista, Carlos Guestrin, Josh M. Susskind:
Set Distribution Networks: a Generative Model for Sets of Images. CoRR abs/2006.10705 (2020) - [i43]Tyler B. Johnson, Pulkit Agrawal, Haijie Gu, Carlos Guestrin:
AdaScale SGD: A User-Friendly Algorithm for Distributed Training. CoRR abs/2007.05105 (2020)
2010 – 2019
- 2019
- [j23]Thierry Moreau, Tianqi Chen, Luis Vega, Jared Roesch, Eddie Q. Yan, Lianmin Zheng, Josh Fromm, Ziheng Jiang, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy:
A Hardware-Software Blueprint for Flexible Deep Learning Specialization. IEEE Micro 39(5): 8-16 (2019) - [c106]Marco Túlio Ribeiro, Carlos Guestrin, Sameer Singh:
Are Red Roses Red? Evaluating Consistency of Question-Answering Models. ACL (1) 2019: 6174-6184 - [c105]Mitchell L. Gordon, Leon A. Gatys, Carlos Guestrin, Jeffrey P. Bigham, Andrew Trister, Kayur Patel:
App Usage Predicts Cognitive Ability in Older Adults. CHI 2019: 168 - [c104]Chen Huang, Shuangfei Zhai, Walter Talbott, Miguel Ángel Bautista, Shih-Yu Sun, Carlos Guestrin, Joshua M. Susskind:
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment. ICML 2019: 2891-2900 - [c103]Shiwen Zhao, Brandt Westing, Shawn Scully, Heri Nieto, Roman Holenstein, Minwoo Jeong, Krishna Sridhar, Brandon Newendorp, Mike Bastian, Sethu Raman, Tim Paek, Kevin Lynch, Carlos Guestrin:
Raise to Speak: An Accurate, Low-power Detector for Activating Voice Assistants on Smartwatches. KDD 2019: 2736-2744 - [c102]Carlos Guestrin:
4 Perspectives in Human-Centered Machine Learning. KDD 2019: 3162 - [c101]Carlos Guestrin:
4 Systems Perspectives into Human-Centered Machine Learning. MobiCom 2019: 57:1-57:2 - [c100]Shuangfei Zhai, Walter Talbott, Carlos Guestrin, Joshua M. Susskind:
Adversarial Fisher Vectors for Unsupervised Representation Learning. NeurIPS 2019: 11156-11166 - [i42]Chen Huang, Shuangfei Zhai, Walter Talbott, Miguel Ángel Bautista, Shih-Yu Sun, Carlos Guestrin, Joshua M. Susskind:
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment. CoRR abs/1905.05895 (2019) - [i41]Shuangfei Zhai, Walter Talbott, Carlos Guestrin, Joshua M. Susskind:
Adversarial Fisher Vectors for Unsupervised Representation Learning. CoRR abs/1910.13101 (2019) - 2018
- [c99]Marco Túlio Ribeiro, Sameer Singh, Carlos Guestrin:
Anchors: High-Precision Model-Agnostic Explanations. AAAI 2018: 1527-1535 - [c98]Marco Túlio Ribeiro, Sameer Singh, Carlos Guestrin:
Semantically Equivalent Adversarial Rules for Debugging NLP models. ACL (1) 2018: 856-865 - [c97]Tianqi Chen, Lianmin Zheng, Eddie Q. Yan, Ziheng Jiang, Thierry Moreau, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy:
Learning to Optimize Tensor Programs. NeurIPS 2018: 3393-3404 - [c96]Tyler B. Johnson, Carlos Guestrin:
Training Deep Models Faster with Robust, Approximate Importance Sampling. NeurIPS 2018: 7276-7286 - [c95]Tianqi Chen, Thierry Moreau, Ziheng Jiang, Lianmin Zheng, Eddie Q. Yan, Haichen Shen, Meghan Cowan, Leyuan Wang, Yuwei Hu, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy:
TVM: An Automated End-to-End Optimizing Compiler for Deep Learning. OSDI 2018: 578-594 - [r2]Amol Deshpande, Carlos Guestrin, Samuel Madden:
Model-Based Querying in Sensor Networks. Encyclopedia of Database Systems (2nd ed.) 2018 - [i40]Tianqi Chen, Thierry Moreau, Ziheng Jiang, Haichen Shen, Eddie Q. Yan, Leyuan Wang, Yuwei Hu, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy:
TVM: End-to-End Optimization Stack for Deep Learning. CoRR abs/1802.04799 (2018) - [i39]Pouya Pezeshkpour, Carlos Guestrin, Sameer Singh:
Compact Factorization of Matrices Using Generalized Round-Rank. CoRR abs/1805.00184 (2018) - [i38]Tianqi Chen, Lianmin Zheng, Eddie Q. Yan, Ziheng Jiang, Thierry Moreau, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy:
Learning to Optimize Tensor Programs. CoRR abs/1805.08166 (2018) - [i37]Thierry Moreau, Tianqi Chen, Ziheng Jiang, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy:
VTA: An Open Hardware-Software Stack for Deep Learning. CoRR abs/1807.04188 (2018) - [i36]Tyler B. Johnson, Carlos Guestrin:
A Fast, Principled Working Set Algorithm for Exploiting Piecewise Linear Structure in Convex Problems. CoRR abs/1807.08046 (2018) - [i35]Michael Fire, Carlos Guestrin:
Over-Optimization of Academic Publishing Metrics: Observing Goodhart's Law in Action. CoRR abs/1809.07841 (2018) - 2017
- [c94]Tianyi Zhou, Hua Ouyang, Jeff A. Bilmes, Yi Chang, Carlos Guestrin:
Scaling Submodular Maximization via Pruned Submodularity Graphs. AISTATS 2017: 316-324 - [c93]Tyler B. Johnson, Carlos Guestrin:
StingyCD: Safely Avoiding Wasteful Updates in Coordinate Descent. ICML 2017: 1752-1760 - [i34]Michael Fire, Carlos Guestrin:
The Rise and Fall of Network Stars. CoRR abs/1706.06690 (2017) - 2016
- [c92]Tianqi Chen, Carlos Guestrin:
XGBoost: A Scalable Tree Boosting System. KDD 2016: 785-794 - [c91]Marco Túlio Ribeiro, Sameer Singh, Carlos Guestrin:
"Why Should I Trust You?": Explaining the Predictions of Any Classifier. KDD 2016: 1135-1144 - [c90]Marco Túlio Ribeiro, Sameer Singh, Carlos Guestrin:
"Why Should I Trust You?": Explaining the Predictions of Any Classifier. HLT-NAACL Demos 2016: 97-101 - [c89]Tyler B. Johnson, Carlos Guestrin:
Unified Methods for Exploiting Piecewise Linear Structure in Convex Optimization. NIPS 2016: 4754-4762 - [i33]Marco Túlio Ribeiro, Sameer Singh, Carlos Guestrin:
"Why Should I Trust You?": Explaining the Predictions of Any Classifier. CoRR abs/1602.04938 (2016) - [i32]Tianqi Chen, Carlos Guestrin:
XGBoost: A Scalable Tree Boosting System. CoRR abs/1603.02754 (2016) - [i31]Michael Fire, Carlos Guestrin:
Analyzing Complex Network User Arrival Patterns and Their Effect on Network Topologies. CoRR abs/1603.07445 (2016) - [i30]Tianqi Chen, Bing Xu, Chiyuan Zhang, Carlos Guestrin:
Training Deep Nets with Sublinear Memory Cost. CoRR abs/1604.06174 (2016) - [i29]Tianyi Zhou, Hua Ouyang, Yi Chang, Jeff A. Bilmes, Carlos Guestrin:
Scaling Submodular Maximization via Pruned Submodularity Graphs. CoRR abs/1606.00399 (2016) - [i28]Marco Túlio Ribeiro, Sameer Singh, Carlos Guestrin:
Model-Agnostic Interpretability of Machine Learning. CoRR abs/1606.05386 (2016) - [i27]Marco Túlio Ribeiro, Sameer Singh, Carlos Guestrin:
Nothing Else Matters: Model-Agnostic Explanations By Identifying Prediction Invariance. CoRR abs/1611.05817 (2016) - [i26]Sameer Singh, Marco Túlio Ribeiro, Carlos Guestrin:
Programs as Black-Box Explanations. CoRR abs/1611.07579 (2016) - 2015
- [j22]Dafna Shahaf, Carlos Guestrin, Eric Horvitz, Jure Leskovec:
Information cartography. Commun. ACM 58(11): 62-73 (2015) - [c88]Tianqi Chen, Sameer Singh, Ben Taskar, Carlos Guestrin:
Efficient Second-Order Gradient Boosting for Conditional Random Fields. AISTATS 2015 - [c87]Tyler B. Johnson, Carlos Guestrin:
Blitz: A Principled Meta-Algorithm for Scaling Sparse Optimization. ICML 2015: 1171-1179 - [c86]Johan Ugander, Ryan Drapeau, Carlos Guestrin:
The Wisdom of Multiple Guesses. EC 2015: 643-660 - 2014
- [j21]Edward A. Lee, Björn Hartmann, John Kubiatowicz, Tajana Simunic Rosing, John Wawrzynek, David Wessel, Jan M. Rabaey, Kris Pister, Alberto L. Sangiovanni-Vincentelli, Sanjit A. Seshia, David T. Blaauw, Prabal Dutta, Kevin Fu, Carlos Guestrin, Ben Taskar, Roozbeh Jafari, Douglas L. Jones, Vijay Kumar, Rahul Mangharam, George J. Pappas, Richard M. Murray, Anthony Rowe:
The Swarm at the Edge of the Cloud. IEEE Des. Test 31(3): 8-20 (2014) - [c85]Santosh Kumar Divvala, Ali Farhadi, Carlos Guestrin:
Learning Everything about Anything: Webly-Supervised Visual Concept Learning. CVPR 2014: 3270-3277 - [c84]Eriko Nurvitadhi, Gabriel Weisz, Yu Wang, Skand Hurkat, Marie Nguyen, James C. Hoe, José F. Martínez, Carlos Guestrin:
GraphGen: An FPGA Framework for Vertex-Centric Graph Computation. FCCM 2014: 25-28 - [c83]Tianqi Chen, Emily B. Fox, Carlos Guestrin:
Stochastic Gradient Hamiltonian Monte Carlo. ICML 2014: 1683-1691 - [c82]Shingo Takamatsu, Carlos Guestrin:
Reducing Data Loading Bottleneck with Coarse Feature Vectors for Large Scale Learning. BigMine 2014: 46-60 - [c81]Tianyi Zhou, Jeff A. Bilmes, Carlos Guestrin:
Divide-and-Conquer Learning by Anchoring a Conical Hull. NIPS 2014: 1242-1250 - [c80]Ignacio Cano, Sameer Singh, Carlos Guestrin:
Distributed Non-Parametric Representations for Vital Filtering: UW at TREC KBA 2014. TREC 2014 - [c79]Yisong Yue, Chong Wang, Khalid El-Arini, Carlos Guestrin:
Personalized collaborative clustering. WWW 2014: 75-84 - [i25]Amarjeet Singh, Andreas Krause, Carlos Guestrin, William J. Kaiser:
Efficient Informative Sensing using Multiple Robots. CoRR abs/1401.3462 (2014) - [i24]Andreas Krause, Carlos Guestrin:
Optimal Value of Information in Graphical Models. CoRR abs/1401.3474 (2014) - [i23]Jonathan Huang, Ashish Kapoor, Carlos Guestrin:
Riffled Independence for Efficient Inference with Partial Rankings. CoRR abs/1401.6421 (2014) - [i22]Tianqi Chen, Emily B. Fox, Carlos Guestrin:
Stochastic Gradient Hamiltonian Monte Carlo. CoRR abs/1402.4102 (2014) - [i21]Aapo Kyrola, Carlos Guestrin:
GraphChi-DB: Simple Design for a Scalable Graph Database System - on Just a PC. CoRR abs/1403.0701 (2014) - [i20]Tianyi Zhou, Jeff A. Bilmes, Carlos Guestrin:
Divide-and-Conquer Learning by Anchoring a Conical Hull. CoRR abs/1406.5752 (2014) - [i19]Yucheng Low, Joseph E. Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin, Joseph M. Hellerstein:
GraphLab: A New Framework For Parallel Machine Learning. CoRR abs/1408.2041 (2014) - 2013
- [j20]Dafna Shahaf, Carlos Guestrin, Eric Horvitz:
"Metro maps of information" by Dafna Shahaf, Carlos Guestrin and Eric Horvitz, with Ching-man Au Yeung as coordinator. SIGWEB Newsl. 2013(Spring): 4:1-4:9 (2013) - [c78]Carlos Guestrin:
Usability in machine learning at scale with graphlab. CIKM 2013: 5-6 - [c77]Khalid El-Arini, Min Xu, Emily B. Fox, Carlos Guestrin:
Representing documents through their readers. KDD 2013: 14-22 - [i18]Carlos Guestrin, Geoffrey J. Gordon:
Distributed Planning in Hierarchical Factored MDPs. CoRR abs/1301.0571 (2013) - [i17]Carlos Guestrin, Dirk Ormoneit:
Robust Combination of Local Controllers. CoRR abs/1301.2273 (2013) - 2012
- [j19]Jonathan Huang, Ashish Kapoor, Carlos Guestrin:
Riffled Independence for Efficient Inference with Partial Rankings. J. Artif. Intell. Res. 44: 491-532 (2012) - [j18]Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin, Joseph M. Hellerstein:
Distributed GraphLab: A Framework for Machine Learning in the Cloud. Proc. VLDB Endow. 5(8): 716-727 (2012) - [j17]Dafna Shahaf, Carlos Guestrin:
Connecting Two (or Less) Dots: Discovering Structure in News Articles. ACM Trans. Knowl. Discov. Data 5(4): 24:1-24:31 (2012) - [c76]Yisong Yue, Sue Ann Hong, Carlos Guestrin:
Hierarchical Exploration for Accelerating Contextual Bandits. ICML 2012 - [c75]Dafna Shahaf, Carlos Guestrin, Eric Horvitz:
Metro maps of science. KDD 2012: 1122-1130 - [c74]Joseph E. Gonzalez, Yucheng Low, Haijie Gu, Danny Bickson, Carlos Guestrin:
PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs. OSDI 2012: 17-30 - [c73]Aapo Kyrola, Guy E. Blelloch, Carlos Guestrin:
GraphChi: Large-Scale Graph Computation on Just a PC. OSDI 2012: 31-46 - [c72]Dafna Shahaf, Carlos Guestrin, Eric Horvitz:
Trains of thought: generating information maps. WWW 2012: 899-908 - [c71]Joseph K. Bradley, Carlos Guestrin:
Sample Complexity of Composite Likelihood. AISTATS 2012: 136-160 - [i16]Jonathan Huang, Ashish Kapoor, Carlos Guestrin:
Efficient Probabilistic Inference with Partial Ranking Queries. CoRR abs/1202.3734 (2012) - [i15]Khalid El-Arini, Emily B. Fox, Carlos Guestrin:
Concept Modeling with Superwords. CoRR abs/1204.2523 (2012) - [i14]Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin, Joseph M. Hellerstein:
Distributed GraphLab: A Framework for Machine Learning in the Cloud. CoRR abs/1204.6078 (2012) - [i13]Joseph Gonzalez, Yucheng Low, Carlos Guestrin, David R. O'Hallaron:
Distributed Parallel Inference on Large Factor Graphs. CoRR abs/1205.2645 (2012) - [i12]Andreas Krause, Carlos Guestrin:
Near-optimal Nonmyopic Value of Information in Graphical Models. CoRR abs/1207.1394 (2012) - [i11]Carlos Guestrin, Milos Hauskrecht, Branislav Kveton:
Solving Factored MDPs with Continuous and Discrete Variables. CoRR abs/1207.4150 (2012) - [i10]Mark A. Paskin, Carlos Guestrin:
Robust Probabilistic Inference in Distributed Systems. CoRR abs/1207.4174 (2012) - 2011
- [j16]Andreas Krause, Ram Rajagopal, Anupam Gupta, Carlos Guestrin:
Simultaneous Optimization of Sensor Placements and Balanced Schedules. IEEE Trans. Autom. Control. 56(10): 2390-2405 (2011) - [j15]Andreas Krause, Carlos Guestrin:
Submodularity and its applications in optimized information gathering. ACM Trans. Intell. Syst. Technol. 2(4): 32:1-32:20 (2011) - [j14]Andreas Krause, Carlos Guestrin, Anupam Gupta, Jon M. Kleinberg:
Robust sensor placements at informative and communication-efficient locations. ACM Trans. Sens. Networks 7(4): 31:1-31:33 (2011) - [c70]Joseph K. Bradley, Aapo Kyrola, Danny Bickson, Carlos Guestrin:
Parallel Coordinate Descent for L1-Regularized Loss Minimization. ICML 2011: 321-328 - [c69]Dafna Shahaf, Carlos Guestrin:
Connecting the Dots between News Articles. IJCAI 2011: 2734-2739 - [c68]Khalid El-Arini, Carlos Guestrin:
Beyond keyword search: discovering relevant scientific literature. KDD 2011: 439-447 - [c67]Yisong Yue, Carlos Guestrin:
Linear Submodular Bandits and their Application to Diversified Retrieval. NIPS 2011: 2483-2491 - [c66]Jonathan Huang, Ashish Kapoor, Carlos Guestrin:
Efficient Probabilistic Inference with Partial Ranking Queries. UAI 2011: 355-362 - [c65]Joseph Gonzalez, Yucheng Low, Arthur Gretton, Carlos Guestrin:
Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees. AISTATS 2011: 324-332 - [c64]Le Song, Arthur Gretton, Danny Bickson, Yucheng Low, Carlos Guestrin:
Kernel Belief Propagation. AISTATS 2011: 707-715 - [i9]Joseph K. Bradley, Aapo Kyrola, Danny Bickson, Carlos Guestrin:
Parallel Coordinate Descent for L1-Regularized Loss Minimization. CoRR abs/1105.5379 (2011) - [i8]Le Song, Arthur Gretton, Danny Bickson, Yucheng Low, Carlos Guestrin:
Kernel Belief Propagation. CoRR abs/1105.5592 (2011) - [i7]Carlos Guestrin, Daphne Koller, Ronald Parr, Shobha Venkataraman:
Efficient Solution Algorithms for Factored MDPs. CoRR abs/1106.1822 (2011) - [i6]Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin:
GraphLab: A Distributed Framework for Machine Learning in the Cloud. CoRR abs/1107.0922 (2011) - [i5]Carlos Guestrin, Milos Hauskrecht, Branislav Kveton:
Solving Factored MDPs with Hybrid State and Action Variables. CoRR abs/1110.0028 (2011) - 2010
- [j13]Eric Horvitz, Lise Getoor, Carlos Guestrin, James A. Hendler, Joseph A. Konstan, Devika Subramanian, Michael P. Wellman, Henry A. Kautz:
AI Theory and Practice: A Discussion on Hard Challenges and Opportunities Ahead. AI Mag. 31(3): 103-114 (2010) - [c63]Alexandra Meliou, Carlos Guestrin, Joseph M. Hellerstein:
Multiresolution Cube Estimators for Sensor Network Aggregate Queries. AMW 2010 - [c62]Joseph K. Bradley, Carlos Guestrin:
Learning Tree Conditional Random Fields. ICML 2010: 127-134 - [c61]Jonathan Huang, Carlos Guestrin:
Learning Hierarchical Riffle Independent Groupings from Rankings. ICML 2010: 455-462 - [c60]Dafna Shahaf, Carlos Guestrin:
Connecting the dots between news articles. KDD 2010: 623-632 - [c59]Danny Bickson, Carlos Guestrin:
Inference with Multivariate Heavy-Tails in Linear Models. NIPS 2010: 208-216 - [c58]Anton Chechetka, Carlos Guestrin:
Evidence-Specific Structures for Rich Tractable CRFs. NIPS 2010: 352-360 - [c57]Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin, Joseph M. Hellerstein:
GraphLab: A New Framework For Parallel Machine Learning. UAI 2010: 340-349 - [c56]Anton Chechetka, Carlos Guestrin:
Focused Belief Propagation for Query-Specific Inference. AISTATS 2010: 89-96 - [c55]Le Song, Arthur Gretton, Carlos Guestrin:
Nonparametric Tree Graphical Models. AISTATS 2010: 765-772 - [i4]Jonathan Huang, Carlos Guestrin:
Uncovering the Riffled Independence Structure of Rankings. CoRR abs/1006.1328 (2010) - [i3]Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin, Joseph M. Hellerstein:
GraphLab: A New Framework for Parallel Machine Learning. CoRR abs/1006.4990 (2010) - [i2]Alexandra Meliou, Carlos Guestrin, Joseph M. Hellerstein:
Multiresolution Cube Estimators for Sensor Network Aggregate Queries. CoRR abs/1007.3781 (2010) - [i1]Danny Bickson, Carlos Guestrin:
Linear Characteristic Graphical Models: Representation, Inference and Applications. CoRR abs/1008.5325 (2010)
2000 – 2009
- 2009
- [j12]Andreas Krause, Carlos Guestrin:
Optimizing Sensing: From Water to the Web. Computer 42(8): 38-45 (2009) - [j11]Amarjeet Singh, Andreas Krause, Carlos Guestrin, William J. Kaiser:
Efficient Informative Sensing using Multiple Robots. J. Artif. Intell. Res. 34: 707-755 (2009) - [j10]Andreas Krause, Carlos Guestrin:
Optimal Value of Information in Graphical Models. J. Artif. Intell. Res. 35: 557-591 (2009) - [j9]Jonathan Huang, Carlos Guestrin, Leonidas J. Guibas:
Fourier Theoretic Probabilistic Inference over Permutations. J. Mach. Learn. Res. 10: 997-1070 (2009) - [c54]Andreas Krause, Ram Rajagopal, Anupam Gupta, Carlos Guestrin:
Simultaneous placement and scheduling of sensors. IPSN 2009: 181-192 - [c53]Alexandra Meliou, Carlos Guestrin, Joseph M. Hellerstein:
Approximating sensor network queries using in-network summaries. IPSN 2009: 229-240 - [c52]Carlos Guestrin:
How optimized environmental sensing helps address information overload on the web. KDD Workshop on Knowledge Discovery from Sensor Data 2009: 11 - [c51]Khalid El-Arini, Gaurav Veda, Dafna Shahaf, Carlos Guestrin:
Turning down the noise in the blogosphere. KDD 2009: 289-298 - [c50]Jonathan Huang, Carlos Guestrin:
Riffled Independence for Ranked Data. NIPS 2009: 799-807 - [c49]Joseph Gonzalez, Yucheng Low, Carlos Guestrin, David R. O'Hallaron:
Distributed Parallel Inference on Large Factor Graphs. UAI 2009: 203-212 - [c48]Dafna Shahaf, Carlos Guestrin:
Learning Thin Junction Trees via Graph Cuts. AISTATS 2009: 113-120 - [c47]Joseph Gonzalez, Yucheng Low, Carlos Guestrin:
Residual Splash for Optimally Parallelizing Belief Propagation. AISTATS 2009: 177-184 - [c46]Jonathan Huang, Carlos Guestrin, Xiaoye Jiang, Leonidas J. Guibas:
Exploiting Probabilistic Independence for Permutations. AISTATS 2009: 248-255 - [r1]Amol Deshpande, Carlos Guestrin, Samuel Madden:
Model-based Querying in Sensor Networks. Encyclopedia of Database Systems 2009: 1764-1768 - 2008
- [j8]Andreas Krause, Ajit Paul Singh, Carlos Guestrin:
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies. J. Mach. Learn. Res. 9: 235-284 (2008) - 2007
- [c45]Alexandra Meliou, Andreas Krause, Carlos Guestrin, Joseph M. Hellerstein:
Nonmyopic Informative Path Planning in Spatio-Temporal Models. AAAI 2007: 602-607 - [c44]Andreas Krause, Carlos Guestrin:
Near-optimal Observation Selection using Submodular Functions. AAAI 2007: 1650-1654 - [c43]Andreas Krause, Carlos Guestrin:
Nonmyopic active learning of Gaussian processes: an exploration-exploitation approach. ICML 2007: 449-456 - [c42]Amarjeet Singh, Andreas Krause, Carlos Guestrin, William J. Kaiser, Maxim A. Batalin:
Efficient Planning of Informative Paths for Multiple Robots. IJCAI 2007: 2204-2211 - [c41]Deepayan Chakrabarti, Jure Leskovec, Christos Faloutsos, Samuel Madden, Carlos Guestrin, Michalis Faloutsos:
Information Survival Threshold in Sensor and P2P Networks. INFOCOM 2007: 1316-1324 - [c40]Jure Leskovec, Andreas Krause, Carlos Guestrin, Christos Faloutsos, Jeanne M. VanBriesen, Natalie S. Glance:
Cost-effective outbreak detection in networks. KDD 2007: 420-429 - [c39]Anton Chechetka, Carlos Guestrin:
Efficient Principled Learning of Thin Junction Trees. NIPS 2007: 273-280 - [c38]Jonathan Huang, Carlos Guestrin, Leonidas J. Guibas:
Efficient Inference for Distributions on Permutations. NIPS 2007: 697-704 - [c37]Andreas Krause, H. Brendan McMahan, Carlos Guestrin, Anupam Gupta:
Selecting Observations against Adversarial Objectives. NIPS 2007: 777-784 - [c36]Bilge Mutlu, Andreas Krause, Jodi Forlizzi, Carlos Guestrin, Jessica K. Hodgins:
Robust, low-cost, non-intrusive sensing and recognition of seated postures. UIST 2007: 149-158 - 2006
- [j7]Branislav Kveton, Milos Hauskrecht, Carlos Guestrin:
Solving Factored MDPs with Hybrid State and Action Variables. J. Artif. Intell. Res. 27: 153-201 (2006) - [c35]Andreas Krause, Jure Leskovec, Carlos Guestrin:
Data association for topic intensity tracking. ICML 2006: 497-504 - [c34]Andreas Krause, Carlos Guestrin, Anupam Gupta, Jon M. Kleinberg:
Near-optimal sensor placements: maximizing information while minimizing communication cost. IPSN 2006: 2-10 - [c33]Stanislav Funiak, Carlos Guestrin, Mark A. Paskin, Rahul Sukthankar:
Distributed localization of networked cameras. IPSN 2006: 34-42 - [c32]Alexandra Meliou, David Chu, Joseph M. Hellerstein, Carlos Guestrin, Wei Hong:
Data gathering tours in sensor networks. IPSN 2006: 43-50 - [c31]Stanislav Funiak, Carlos Guestrin, Mark A. Paskin, Rahul Sukthankar:
Distributed Inference in Dynamical Systems. NIPS 2006: 433-440 - 2005
- [j6]Amol Deshpande, Carlos Guestrin, Samuel Madden:
Resource-Aware Wireless Sensor-Actuator Networks. IEEE Data Eng. Bull. 28(1): 40-47 (2005) - [j5]Jure Leskovec, Purnamrita Sarkar, Carlos Guestrin:
Modeling Link Qualities in a Sensor Network. Informatica (Slovenia) 29(4): 445-452 (2005) - [j4]Amol Deshpande, Carlos Guestrin, Samuel Madden, Joseph M. Hellerstein, Wei Hong:
Model-based approximate querying in sensor networks. VLDB J. 14(4): 417-443 (2005) - [c30]Amol Deshpande, Carlos Guestrin, Samuel Madden:
Using Probabilistic Models for Data Management in Acquisitional Environments. CIDR 2005: 317-328 - [c29]Amol Deshpande, Carlos Guestrin, Wei Hong, Samuel Madden:
Exploiting Correlated Attributes in Acquisitional Query Processing. ICDE 2005: 143-154 - [c28]Carlos Guestrin, Andreas Krause, Ajit Paul Singh:
Near-optimal sensor placements in Gaussian processes. ICML 2005: 265-272 - [c27]Benjamin Taskar, Vassil Chatalbashev, Daphne Koller, Carlos Guestrin:
Learning structured prediction models: a large margin approach. ICML 2005: 896-903 - [c26]Bhaskara Marthi, Stuart Russell, David Latham, Carlos Guestrin:
Concurrent Hierarchical Reinforcement Learning. IJCAI 2005: 779-785 - [c25]Andreas Krause, Carlos Guestrin:
Optimal Nonmyopic Value of Information in Graphical Models - Efficient Algorithms and Theoretical Limits. IJCAI 2005: 1339-1345 - [c24]Mark A. Paskin, Carlos Guestrin, Jim McFadden:
A robust architecture for distributed inference in sensor networks. IPSN 2005: 55-62 - [c23]Vipul Singhvi, Andreas Krause, Carlos Guestrin, James H. Garrett Jr., H. Scott Matthews:
Intelligent light control using sensor networks. SenSys 2005: 218-229 - [c22]Burak Aksak, Preethi Srinivas Bhat, Jason Campbell, Michael DeRosa, Stanislav Funiak, Phillip B. Gibbons, Seth Copen Goldstein, Carlos Guestrin, Ashish Gupta, Casey Helfrich, James F. Hoburg, Brian T. Kirby, James Kuffner, Peter Lee, Todd C. Mowry, Padmanabhan Pillai, Ram Ravichandran, Benjamin D. Rister, Srinivasan Seshan, Metin Sitti, Haifeng Yu:
Claytronics: highly scalable communications, sensing, and actuation networks. SenSys 2005: 299 - [c21]Andreas Krause, Carlos Guestrin:
Near-optimal Nonmyopic Value of Information in Graphical Models. UAI 2005: 324-331 - 2004
- [c20]Carlos Guestrin, Peter Bodík, Romain Thibaux, Mark A. Paskin, Samuel Madden:
Distributed regression: an efficient framework for modeling sensor network data. IPSN 2004: 1-10 - [c19]Carlos Guestrin, Milos Hauskrecht, Branislav Kveton:
Solving Factored MDPs with Continuous and Discrete Variables. UAI 2004: 235-242 - [c18]Mark A. Paskin, Carlos Guestrin:
Robust Probabilistic Inference in Distributed Systems. UAI 2004: 436-445 - [c17]Amol Deshpande, Carlos Guestrin, Samuel Madden, Joseph M. Hellerstein, Wei Hong:
Model-Driven Data Acquisition in Sensor Networks. VLDB 2004: 588-599 - 2003
- [b1]Carlos Guestrin:
Planning under uncertainty in complex structured environments. Stanford University, USA, 2003 - [j3]Carlos Guestrin, Daphne Koller, Ronald Parr, Shobha Venkataraman:
Efficient Solution Algorithms for Factored MDPs. J. Artif. Intell. Res. 19: 399-468 (2003) - [j2]Mehmet Serkan Apaydin, Douglas L. Brutlag, Carlos Guestrin, David Hsu, Jean-Claude Latombe, Chris Varma:
Stochastic Roadmap Simulation: An Efficient Representation and Algorithm for Analyzing Molecular Motion. J. Comput. Biol. 10(3/4): 257-281 (2003) - [c16]Carlos Guestrin, Daphne Koller, Chris Gearhart, Neal Kanodia:
Generalizing Plans to New Environments in Relational MDPs. IJCAI 2003: 1003-1010 - [c15]Benjamin Taskar, Carlos Guestrin, Daphne Koller:
Max-Margin Markov Networks. NIPS 2003: 25-32 - 2002
- [c14]Carlos Guestrin, Shobha Venkataraman, Daphne Koller:
Context-Specific Multiagent Coordination and Planning with Factored MDPs. AAAI/IAAI 2002: 253-259 - [c13]Relu Patrascu, Pascal Poupart, Dale Schuurmans, Craig Boutilier, Carlos Guestrin:
Greedy Linear Value-Approximation for Factored Markov Decision Processes. AAAI/IAAI 2002: 285-291 - [c12]Mehmet Serkan Apaydin, Carlos Guestrin, Chris Varma, Douglas L. Brutlag, Jean-Claude Latombe:
Stochastic roadmap simulation for the study of ligand-protein interactions. ECCB 2002: 18-26 - [c11]Douglas L. Brutlag, Mehmet Serkan Apaydin, Carlos Guestrin, David Hsu, Chris Varma, Amit Pal Singh, Jean-Claude Latombe:
Using robotics to fold proteins and dock ligands. ECCB 2002: 74-74 - [c10]Carlos Guestrin, Michail G. Lagoudakis, Ronald Parr:
Coordinated Reinforcement Learning. ICML 2002: 227-234 - [c9]Carlos Guestrin, Relu Patrascu, Dale Schuurmans:
Algorithm-Directed Exploration for Model-Based Reinforcement Learning in Factored MDPs. ICML 2002: 235-242 - [c8]Mehmet Serkan Apaydin, Douglas L. Brutlag, Carlos Guestrin, David Hsu, Jean-Claude Latombe:
Stochastic roadmap simulation: an efficient representation and algorithm for analyzing molecular motion. RECOMB 2002: 12-21 - [c7]Carlos Guestrin, Geoffrey J. Gordon:
Distributed Planning in Hierarchical Factored MDPs. UAI 2002: 197-206 - [c6]Mehmet Serkan Apaydin, Douglas L. Brutlag, Carlos Guestrin, David Hsu, Jean-Claude Latombe:
Stochastic Conformational Roadmaps for Computing Ensemble Properties of Molecular Motion. WAFR 2002: 131-148 - 2001
- [c5]Carlos Guestrin, Daphne Koller, Ronald Parr:
Max-norm Projections for Factored MDPs. IJCAI 2001: 673-682 - [c4]Carlos Guestrin, Daphne Koller, Ronald Parr:
Multiagent Planning with Factored MDPs. NIPS 2001: 1523-1530 - [c3]Carlos Guestrin, Dirk Ormoneit:
Robust Combination of Local Controllers. UAI 2001: 178-185 - 2000
- [j1]Fábio Gagliardi Cozman, Eric Krotkov, Carlos Guestrin:
Outdoor Visual Position Estimation for Planetary Rovers. Auton. Robots 9(2): 135-150 (2000)
1990 – 1999
- 1998
- [c2]Carlos Guestrin, Fábio Gagliardi Cozman, Eric Krotkov:
Fast software image stabilization with color registration. IROS 1998: 19-24 - [c1]Carlos Guestrin, Fábio Gagliardi Cozman, Marcelo Godoy Simões:
Industrial applications of image mosaicing and stabilization. KES (2) 1998: 174-183
Coauthor Index
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