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ORCIDRoman Garnett
Person information
- affiliation: Washington University in Saint Louis, MO, USA
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2020 – today
- 2024
[c46]Julia Grosse, Rahel Fischer, Roman Garnett, Philipp Hennig:
A Greedy Approximation for k-Determinantal Point Processes. AISTATS 2024: 3052-3060- [c45]Anindya Sarkar, Michael Lanier, Scott Alfeld, Jiarui Feng, Roman Garnett, Nathan Jacobs, Yevgeniy Vorobeychik:
A Visual Active Search Framework for Geospatial Exploration. WACV 2024: 8301-8310 - [i24]Quan Nguyen, Anindya Sarkar, Roman Garnett:
Amortized nonmyopic active search via deep imitation learning. CoRR abs/2405.15031 (2024) - [i23]Yehu Chen, Muchen Xi, Jacob M. Montgomery, Joshua Jackson, Roman Garnett:
Idiographic Personality Gaussian Process for Psychological Assessment. CoRR abs/2407.04970 (2024) - 2023
- [j11]Shayan Monadjemi
, Mengtian Guo, David Gotz, Roman Garnett, Alvitta Ottley:
Human-Computer Collaboration for Visual Analytics: an Agent-based Framework. Comput. Graph. Forum 42(3): 199-210 (2023) - [j10]Sunwoo Ha, Shayan Monadjemi, Roman Garnett, Alvitta Ottley:
A Unified Comparison of User Modeling Techniques for Predicting Data Interaction and Detecting Exploration Bias. IEEE Trans. Vis. Comput. Graph. 29(1): 483-492 (2023) - [c44]Yehu Chen, Annamaria Prati, Jacob M. Montgomery, Roman Garnett:
A Multi-Task Gaussian Process Model for Inferring Time-Varying Treatment Effects in Panel Data. AISTATS 2023: 4068-4088 - [c43]Quan Nguyen, Roman Garnett:
Nonmyopic Multiclass Active Search with Diminishing Returns for Diverse Discovery. AISTATS 2023: 5231-5249 - [c42]Kaiwen Wu, Kyurae Kim, Roman Garnett, Jacob R. Gardner:
The Behavior and Convergence of Local Bayesian Optimization. NeurIPS 2023 - [e7]Aleksandra Faust, Roman Garnett, Colin White, Frank Hutter, Jacob R. Gardner:
International Conference on Automated Machine Learning, 12-15 November 2023, Hasso Plattner Institute, Potsdam, Germany. Proceedings of Machine Learning Research 224, PMLR 2023 [contents] - [i22]Shayan Monadjemi, Mengtian Guo, David Gotz, Roman Garnett, Alvitta Ottley:
Human-Computer Collaboration for Visual Analytics: an Agent-based Framework. CoRR abs/2304.09415 (2023) - [i21]Kaiwen Wu, Kyurae Kim, Roman Garnett, Jacob R. Gardner:
The Behavior and Convergence of Local Bayesian Optimization. CoRR abs/2305.15572 (2023) - 2022
- [c41]Quan Nguyen, Kaiwen Wu, Jacob R. Gardner, Roman Garnett:
Local Bayesian optimization via maximizing probability of descent. NeurIPS 2022 - [c40]Shayan Monadjemi, Sunwoo Ha, Quan Nguyen, Henry Chai, Roman Garnett, Alvitta Ottley:
Guided Data Discovery in Interactive Visualizations via Active Search. IEEE VIS (Short Papers) 2022: 70-74 - [e6]Isabelle Guyon, Marius Lindauer, Mihaela van der Schaar, Frank Hutter, Roman Garnett:
International Conference on Automated Machine Learning, AutoML 2022, 25-27 July 2022, Johns Hopkins University, Baltimore, MD, USA. Proceedings of Machine Learning Research 188, PMLR 2022 [contents] - [i20]Quan Nguyen, Roman Garnett:
Nonmyopic Multiclass Active Search for Diverse Discovery. CoRR abs/2202.03593 (2022) - [i19]Sunwoo Ha, Shayan Monadjemi, Roman Garnett, Alvitta Ottley:
A Unified Comparison of User Modeling Techniques for Predicting Data Interaction and Detecting Exploration Bias. CoRR abs/2208.05021 (2022) - [i18]Quan Nguyen, Kaiwen Wu, Jacob R. Gardner, Roman Garnett:
Local Bayesian optimization via maximizing probability of descent. CoRR abs/2210.11662 (2022) - [i17]Anindya Sarkar, Michael Lanier, Scott Alfeld, Roman Garnett, Nathan Jacobs, Yevgeniy Vorobeychik:
A Visual Active Search Framework for Geospatial Exploration. CoRR abs/2211.15788 (2022) - 2021
- [j9]Fatemah Mukadum, Quan Nguyen, Daniel M. Adrion, Gabriel Appleby, Rui Chen, Haley Dang, Remco Chang, Roman Garnett, Steven A. Lopez:
Efficient Discovery of Visible Light-Activated Azoarene Photoswitches with Long Half-Lives Using Active Search. J. Chem. Inf. Model. 61(11): 5524-5534 (2021) - [j8]Shayan Monadjemi, Roman Garnett, Alvitta Ottley:
Competing Models: Inferring Exploration Patterns and Information Relevance via Bayesian Model Selection. IEEE Trans. Vis. Comput. Graph. 27(2): 412-421 (2021) - [c39]Quan Nguyen, Sanmay Das, Roman Garnett:
Scarce Societal Resource Allocation and the Price of (Local) Justice. AAAI 2021: 5628-5636 - [c38]Quan Nguyen, Arghavan Modiri, Roman Garnett:
Nonmyopic Multifidelity Acitve Search. ICML 2021: 8109-8118 - [i16]Quan Nguyen, Arghavan Modiri, Roman Garnett:
Nonmyopic Multifidelity Active Search. CoRR abs/2106.06356 (2021) - 2020
- [c37]Shali Jiang, Henry Chai, Javier Gonzalez, Roman Garnett:
BINOCULARS for efficient, nonmyopic sequential experimental design. ICML 2020: 4794-4803 - [c36]Shali Jiang, Daniel R. Jiang, Maximilian Balandat, Brian Karrer, Jacob R. Gardner, Roman Garnett:
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees. NeurIPS 2020 - [c35]JBrandon Duck-Mayr, Roman Garnett, Jacob M. Montgomery:
GPIRT: A Gaussian Process Model for Item Response Theory. UAI 2020: 520-529 - [i15]JBrandon Duck-Mayr, Roman Garnett, Jacob M. Montgomery:
GPIRT: A Gaussian Process Model for Item Response Theory. CoRR abs/2006.09900 (2020) - [i14]Shali Jiang, Daniel R. Jiang, Maximilian Balandat, Brian Karrer, Jacob R. Gardner, Roman Garnett:
Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees. CoRR abs/2006.15779 (2020) - [i13]Shayan Monadjemi, Roman Garnett, Alvitta Ottley:
Competing Models: Inferring Exploration Patterns and Information Relevance via Bayesian Model Selection. CoRR abs/2009.06042 (2020) - [i12]Shayan Monadjemi, Quan Nguyen, Henry Chai, Roman Garnett, Alvitta Ottley:
Active Visual Analytics: Assisted Data Discovery in Interactive Visualizations via Active Search. CoRR abs/2010.08155 (2020)
2010 – 2019
- 2019
- [j7]Alvitta Ottley, Roman Garnett, Ran Wan:
Follow The Clicks: Learning and Anticipating Mouse Interactions During Exploratory Data Analysis. Comput. Graph. Forum 38(3): 41-52 (2019) - [c34]Henry R. Chai, Roman Garnett:
Improving Quadrature for Constrained Integrands. AISTATS 2019: 2751-2759 - [c33]Henry Chai, Jean-Francois Ton, Michael A. Osborne, Roman Garnett:
Automated Model Selection with Bayesian Quadrature. ICML 2019: 931-940 - [c32]Muhan Zhang, Shali Jiang, Zhicheng Cui, Roman Garnett, Yixin Chen:
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs. NeurIPS 2019: 1586-1598 - [c31]Shali Jiang, Roman Garnett, Benjamin Moseley:
Cost Effective Active Search. NeurIPS 2019: 4881-4890 - [e5]Hanna M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d'Alché-Buc, Emily B. Fox, Roman Garnett:
Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada. 2019 [contents] - [i11]Henry Chai, Jean-Francois Ton, Roman Garnett, Michael A. Osborne:
Automated Model Selection with Bayesian Quadrature. CoRR abs/1902.09724 (2019) - [i10]Muhan Zhang, Shali Jiang, Zhicheng Cui, Roman Garnett, Yixin Chen:
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs. CoRR abs/1904.11088 (2019) - [i9]Shali Jiang, Henry Chai, Javier Gonzalez, Roman Garnett:
Efficient nonmyopic Bayesian optimization and quadrature. CoRR abs/1909.04568 (2019) - 2018
- [c30]Shali Jiang, Gustavo Malkomes, Matthew Abbott, Benjamin Moseley, Roman Garnett:
Efficient nonmyopic batch active search. NeurIPS 2018: 1107-1117 - [c29]Gustavo Malkomes, Roman Garnett:
Automating Bayesian optimization with Bayesian optimization. NeurIPS 2018: 5988-5997 - [e4]Samy Bengio, Hanna M. Wallach, Hugo Larochelle, Kristen Grauman, Nicolò Cesa-Bianchi, Roman Garnett:
Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada. 2018 [contents] - [i8]Henry Chai, Roman Garnett:
An Improved Bayesian Framework for Quadrature of Constrained Integrands. CoRR abs/1802.04782 (2018) - [i7]Ran Wan, Roman Garnett, Alvitta Ottley:
Learning and Anticipating Future Actions During Exploratory Data Analysis. CoRR abs/1809.09664 (2018) - [i6]Shali Jiang, Gustavo Malkomes, Benjamin Moseley, Roman Garnett:
Efficient nonmyopic active search with applications in drug and materials discovery. CoRR abs/1811.08871 (2018) - 2017
- [c28]Yifei Ma, Roman Garnett, Jeff G. Schneider:
Active Search for Sparse Signals with Region Sensing. AAAI 2017: 2315-2321 - [c27]Dino Oglic, Roman Garnett, Thomas Gärtner:
Active Search in Intensionally Specified Structured Spaces. AAAI 2017: 2443-2449 - [c26]Jacob R. Gardner, Chuan Guo, Kilian Q. Weinberger, Roman Garnett, Roger B. Grosse:
Discovering and Exploiting Additive Structure for Bayesian Optimization. AISTATS 2017: 1311-1319 - [c25]Gustavo Malkomes, Kefu Lu, Blakeley Hoffman, Roman Garnett, Benjamin Moseley, Richard P. Mann:
Cooperative Set Function Optimization Without Communication or Coordination. AAMAS 2017: 1109-1118 - [c24]Shali Jiang, Gustavo Malkomes, Geoff Converse, Alyssa Shofner, Benjamin Moseley, Roman Garnett:
Efficient Nonmyopic Active Search. ICML 2017: 1714-1723 - [e3]Isabelle Guyon, Ulrike von Luxburg, Samy Bengio, Hanna M. Wallach, Rob Fergus, S. V. N. Vishwanathan, Roman Garnett:
Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA. 2017 [contents] - 2016
- [j6]Marion Neumann, Roman Garnett, Christian Bauckhage, Kristian Kersting:
Propagation kernels: efficient graph kernels from propagated information. Mach. Learn. 102(2): 209-245 (2016) - [c23]Gustavo Malkomes, Chip Schaff, Roman Garnett:
Bayesian optimization for automated model selection. AutoML@ICML 2016: 41-47 - [c22]Shane Carr, Roman Garnett, Cynthia Lo:
BASC: Applying Bayesian Optimization to the Search for Global Minima on Potential Energy Surfaces. ICML 2016: 898-907 - [c21]Gustavo Malkomes, Chip Schaff, Roman Garnett:
Bayesian optimization for automated model selection. NIPS 2016: 2892-2900 - [e2]Daniel D. Lee, Masashi Sugiyama, Ulrike von Luxburg, Isabelle Guyon, Roman Garnett:
Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain. 2016 [contents] - [i5]Philipp Hennig, Roman Garnett:
Exact Sampling from Determinantal Point Processes. CoRR abs/1609.06840 (2016) - [i4]Yifei Ma, Roman Garnett, Jeff G. Schneider:
Active Search for Sparse Signals with Region Sensing. CoRR abs/1612.00583 (2016) - 2015
- [j5]Roman Garnett, Thomas Gärtner, Martin Vogt, Jürgen Bajorath:
Introducing the 'active search' method for iterative virtual screening. J. Comput. Aided Mol. Des. 29(4): 305-314 (2015) - [c20]Yifei Ma, Danica J. Sutherland, Roman Garnett, Jeff G. Schneider:
Active Pointillistic Pattern Search. AISTATS 2015 - [c19]Matt J. Kusner, Jacob R. Gardner, Roman Garnett, Kilian Q. Weinberger:
Differentially Private Bayesian Optimization. ICML 2015: 918-927 - [c18]Roman Garnett, Shirley Ho, Jeff G. Schneider:
Finding Galaxies in the Shadows of Quasars with Gaussian Processes. ICML 2015: 1025-1033 - [c17]Jacob R. Gardner, Gustavo Malkomes, Roman Garnett, Kilian Q. Weinberger, Dennis L. Barbour, John P. Cunningham:
Bayesian Active Model Selection with an Application to Automated Audiometry. NIPS 2015: 2386-2394 - [e1]Corinna Cortes, Neil D. Lawrence, Daniel D. Lee, Masashi Sugiyama, Roman Garnett:
Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, December 7-12, 2015, Montreal, Quebec, Canada. 2015 [contents] - 2014
- [c16]Kristian Kersting, Martin Mladenov, Roman Garnett, Martin Grohe:
Power Iterated Color Refinement. AAAI 2014: 1904-1910 - [c15]Yifei Ma, Roman Garnett, Jeff G. Schneider:
Active Area Search via Bayesian Quadrature. AISTATS 2014: 595-603 - [c14]Roman Garnett, Thomas Gärtner, Timothy Ellersiek, Eyjolfur Gudmondsson, Petur Oskarsson:
Predicting unexpected influxes of players in EVE online. CIG 2014: 1-8 - [c13]Tom Gunter, Michael A. Osborne, Roman Garnett, Philipp Hennig, Stephen J. Roberts:
Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature. NIPS 2014: 2789-2797 - [c12]Roman Garnett, Michael A. Osborne, Philipp Hennig:
Active Learning of Linear Embeddings for Gaussian Processes. UAI 2014: 230-239 - [i3]Marion Neumann, Roman Garnett, Christian Bauckhage, Kristian Kersting:
Propagation Kernels. CoRR abs/1410.3314 (2014) - 2013
- [j4]Richard P. Mann, Andrea Perna, Daniel Strömbom, Roman Garnett, James E. Herbert-Read, David J. T. Sumpter, Ashley J. W. Ward:
Multi-scale Inference of Interaction Rules in Animal Groups Using Bayesian Model Selection. PLoS Comput. Biol. 9(3) (2013) - [c11]Marion Neumann, Roman Garnett, Kristian Kersting:
Coinciding Walk Kernels: Parallel Absorbing Random Walks for Learning with Graphs and Few Labels. ACML 2013: 357-372 - [c10]Xuezhi Wang, Roman Garnett, Jeff G. Schneider:
Active search on graphs. KDD 2013: 731-738 - [c9]Yifei Ma, Roman Garnett, Jeff G. Schneider:
Σ-Optimality for Active Learning on Gaussian Random Fields. NIPS 2013: 2751-2759 - [i2]Roman Garnett, Michael A. Osborne, Philipp Hennig:
Active Learning of Linear Embeddings for Gaussian Processes. CoRR abs/1310.6740 (2013) - 2012
- [c8]Michael A. Osborne, Roman Garnett, Kevin Swersky, Nando de Freitas:
Prediction and Fault Detection of Environmental Signals with Uncharacterised Faults. AAAI 2012: 349-355 - [c7]Roman Garnett, Yamuna Krishnamurthy, Xuehan Xiong, Jeff G. Schneider, Richard P. Mann:
Bayesian Optimal Active Search and Surveying. ICML 2012 - [c6]Michael A. Osborne, David Duvenaud, Roman Garnett, Carl E. Rasmussen, Stephen J. Roberts, Zoubin Ghahramani:
Active Learning of Model Evidence Using Bayesian Quadrature. NIPS 2012: 46-54 - [c5]Marion Neumann, Novi Patricia, Roman Garnett, Kristian Kersting:
Efficient Graph Kernels by Randomization. ECML/PKDD (1) 2012: 378-393 - [c4]Michael A. Osborne, Roman Garnett, Stephen J. Roberts, Christopher Hart, Suzanne Aigrain, Neale Gibson:
Bayesian Quadrature for Ratios. AISTATS 2012: 832-840 - [i1]Yifei Ma, Roman Garnett, Jeff G. Schneider:
Submodularity in Batch Active Learning and Survey Problems on Gaussian Random Fields. CoRR abs/1209.3694 (2012) - 2010
- [b1]Roman Garnett:
Learning from data streams with concept drift. University of Oxford, UK, 2010 - [j3]Roman Garnett, Michael A. Osborne, Steven Reece, Alex Rogers, Stephen J. Roberts:
Sequential Bayesian Prediction in the Presence of Changepoints and Faults. Comput. J. 53(9): 1430-1446 (2010) - [j2]D. R. Lowne, Stephen J. Roberts, Roman Garnett:
Sequential non-stationary dynamic classification with sparse feedback. Pattern Recognit. 43(3): 897-905 (2010) - [c3]Michael A. Osborne, Roman Garnett, Stephen J. Roberts:
Active Data Selection for Sensor Networks with Faults and Changepoints. AINA 2010: 533-540 - [c2]Roman Garnett, Michael A. Osborne, Stephen J. Roberts:
Bayesian optimization for sensor set selection. IPSN 2010: 209-219
2000 – 2009
- 2009
- [c1]Roman Garnett, Michael A. Osborne, Stephen J. Roberts:
Sequential Bayesian prediction in the presence of changepoints. ICML 2009: 345-352 - 2005
- [j1]Roman Garnett, Timothy Huegerich, Charles K. Chui, Wenjie He:
A universal noise removal algorithm with an impulse detector. IEEE Trans. Image Process. 14(11): 1747-1754 (2005)
Coauthor Index
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