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ORCIDAndreas Krause 0001
Person information
- affiliation: ETH Zurich, Switzerland
- affiliation: California Institute of Technology, Pasadena, CA, USA
- affiliation: Carnegie Mellon University, Pittsburgh, PA, USA
- affiliation: Technical University of Munich, Germany
Other persons with the same name
- Andreas Krause — disambiguation page
- Andreas Krause 0002
![[0000-0002-4509-9775]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-4509-9775")
— University of Bath, School of Management, UK - Andreas Krause 0003 — European Research Center for Information Systems, Münster, Germany
- Andreas Krause 0004 — Immanuel Hospital Berlin, Germany (and 1 more)
- Andreas Krause 0005 — IPH Hannover, Germany
- Andreas Krause 0006 — Idorsia Pharmaceuticals Ltd, Allschwil, Switzerland (and 4 more)
- Andreas Krause 0007 — Philips Semiconductors, Hamburg, Germany
- Andreas Krause 0008 — University of Göttingen, Germany
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2020 – today
- 2023
[j35]Bhavya Sukhija, Matteo Turchetta, David Lindner, Andreas Krause, Sebastian Trimpe, Dominik Baumann:
GoSafeOpt: Scalable safe exploration for global optimization of dynamical systems. Artif. Intell. 320: 103922 (2023)- [j34]Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David M. Pennock, Andreas Krause:
Incentive-Compatible Forecasting Competitions. Manag. Sci. 69(3): 1354-1374 (2023) - [j33]Felix Berkenkamp, Andreas Krause, Angela P. Schoellig:
Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics. Mach. Learn. 112(10): 3713-3747 (2023) - [j32]Jonas Gehring, Deepak Gopinath, Jungdam Won, Andreas Krause, Gabriel Synnaeve, Nicolas Usunier:
Leveraging Demonstrations with Latent Space Priors. Trans. Mach. Learn. Res. 2023 (2023) - [j31]Barna Pásztor, Andreas Krause, Ilija Bogunovic:
Efficient Model-Based Multi-Agent Mean-Field Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c263]Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause:
BaCaDI: Bayesian Causal Discovery with Unknown Interventions. AISTATS 2023: 1411-1436 - [c262]Viacheslav Borovitskiy, Mohammad Reza Karimi, Vignesh Ram Somnath, Andreas Krause:
Isotropic Gaussian Processes on Finite Spaces of Graphs. AISTATS 2023: 4556-4574 - [c261]Charlotte Bunne, Ya-Ping Hsieh, Marco Cuturi, Andreas Krause:
The Schrödinger Bridge between Gaussian Measures has a Closed Form. AISTATS 2023: 5802-5833 - [c260]Mojmir Mutny, Tadeusz Janik, Andreas Krause:
Active Exploration via Experiment Design in Markov Chains. AISTATS 2023: 7349-7374 - [c259]Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni, Grigoris Velegkas:
Replicable Bandits. ICLR 2023 - [c258]Xiang Li, Viraj Mehta, Johannes Kirschner, Ian Char, Willie Neiswanger, Jeff Schneider, Andreas Krause, Ilija Bogunovic:
Near-optimal Policy Identification in Active Reinforcement Learning. ICLR 2023 - [c257]Krunoslav Lehman Pavasovic, Jonas Rothfuss, Andreas Krause:
MARS: Meta-learning as Score Matching in the Function Space. ICLR 2023 - [c256]Scott Sussex, Anastasia Makarova, Andreas Krause:
Model-based Causal Bayesian Optimization. ICLR 2023 - [c255]Bhavya Sukhija, Nathanael Köhler, Miguel Zamora, Simon Zimmermann, Sebastian Curi, Andreas Krause, Stelian Coros:
Gradient-Based Trajectory Optimization With Learned Dynamics. ICRA 2023: 1011-1018 - [c254]Ali Gorji, Andisheh Amrollahi, Andreas Krause:
A scalable Walsh-Hadamard regularizer to overcome the low-degree spectral bias of neural networks. UAI 2023: 723-733 - [c253]Jonas Rothfuss, Bhavya Sukhija, Tobias Birchler, Parnian Kassraie, Andreas Krause:
Hallucinated adversarial control for conservative offline policy evaluation. UAI 2023: 1774-1784 - [c252]Felix Schur, Parnian Kassraie, Jonas Rothfuss, Andreas Krause:
Lifelong bandit optimization: no prior and no regret. UAI 2023: 1847-1857 - [c251]Vignesh Ram Somnath, Matteo Pariset, Ya-Ping Hsieh, María Rodríguez Martínez, Andreas Krause, Charlotte Bunne:
Aligned Diffusion Schrödinger Bridges. UAI 2023: 1985-1995 - [e2]Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, Jonathan Scarlett:
International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA. Proceedings of Machine Learning Research 202, PMLR 2023 [contents] - [i203]Max B. Paulus, Andreas Krause:
Learning To Dive In Branch And Bound. CoRR abs/2301.09943 (2023) - [i202]Johannes Kirschner, Tor Lattimore, Andreas Krause:
Linear Partial Monitoring for Sequential Decision-Making: Algorithms, Regret Bounds and Applications. CoRR abs/2302.03683 (2023) - [i201]Vignesh Ram Somnath, Matteo Pariset, Ya-Ping Hsieh, María Rodríguez Martínez, Andreas Krause, Charlotte Bunne:
Aligned Diffusion Schrödinger Bridges. CoRR abs/2302.11419 (2023) - [i200]Jonas Rothfuss, Bhavya Sukhija, Tobias Birchler, Parnian Kassraie, Andreas Krause:
Hallucinated Adversarial Control for Conservative Offline Policy Evaluation. CoRR abs/2303.01076 (2023) - [i199]Yunke Ao, Hooman Esfandiari, Fabio Carrillo, Yarden As, Mazda Farshad, Benjamin F. Grewe, Andreas Krause, Philipp Fürnstahl:
Safe Deep RL for Intraoperative Planning of Pedicle Screw Placement. CoRR abs/2305.05354 (2023) - [i198]Ali Gorji, Andisheh Amrollahi, Andreas Krause:
A Scalable Walsh-Hadamard Regularizer to Overcome the Low-degree Spectral Bias of Neural Networks. CoRR abs/2305.09779 (2023) - [i197]David Lindner, Xin Chen, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause:
Learning Safety Constraints from Demonstrations with Unknown Rewards. CoRR abs/2305.16147 (2023) - [i196]Daniel Widmer, Dongho Kang, Bhavya Sukhija, Jonas Hübotter, Andreas Krause, Stelian Coros:
Tuning Legged Locomotion Controllers via Safe Bayesian Optimization. CoRR abs/2306.07092 (2023) - [i195]Pragnya Alatur, Giorgia Ramponi, Niao He, Andreas Krause:
Provably Learning Nash Policies in Constrained Markov Potential Games. CoRR abs/2306.07749 (2023) - [i194]Matteo Pariset, Ya-Ping Hsieh, Charlotte Bunne, Andreas Krause, Valentin De Bortoli:
Unbalanced Diffusion Schrödinger Bridge. CoRR abs/2306.09099 (2023) - [i193]Bhavya Sukhija, Lenart Treven, Cansu Sancaktar, Sebastian Blaes, Stelian Coros, Andreas Krause:
Optimistic Active Exploration of Dynamical Systems. CoRR abs/2306.12371 (2023) - [i192]Christopher Koenig, Miks Ozols, Anastasia Makarova, Efe C. Balta, Andreas Krause, Alisa Rupenyan:
Safe Risk-averse Bayesian Optimization for Controller Tuning. CoRR abs/2306.13479 (2023) - [i191]Matej Jusup, Barna Pásztor, Tadeusz Janik, Kenan Zhang, Francesco Corman, Andreas Krause, Ilija Bogunovic:
Safe Model-Based Multi-Agent Mean-Field Reinforcement Learning. CoRR abs/2306.17052 (2023) - [i190]Parnian Kassraie, Aldo Pacchiano, Nicolas Emmenegger, Andreas Krause:
Anytime Model Selection in Linear Bandits. CoRR abs/2307.12897 (2023) - [i189]Manish Prajapat, Mojmír Mutný, Melanie N. Zeilinger, Andreas Krause:
Submodular Reinforcement Learning. CoRR abs/2307.13372 (2023) - [i188]Scott Sussex, Pier Giuseppe Sessa, Anastasiia Makarova, Andreas Krause:
Model-based Causal Bayesian Optimization. CoRR abs/2307.16625 (2023) - [i187]Pier Giuseppe Sessa, Pierre Laforgue, Nicolò Cesa-Bianchi, Andreas Krause:
Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning. CoRR abs/2308.01744 (2023) - [i186]Shyam Sundhar Ramesh, Pier Giuseppe Sessa, Yifan Hu, Andreas Krause, Ilija Bogunovic:
Distributionally Robust Model-based Reinforcement Learning with Large State Spaces. CoRR abs/2309.02236 (2023) - 2022
- [c250]Parnian Kassraie, Andreas Krause:
Neural Contextual Bandits without Regret. AISTATS 2022: 240-278 - [c249]Charlotte Bunne, Laetitia Papaxanthos, Andreas Krause, Marco Cuturi:
Proximal Optimal Transport Modeling of Population Dynamics. AISTATS 2022: 6511-6528 - [c248]Mojmir Mutny, Andreas Krause:
Sensing Cox Processes via Posterior Sampling and Positive Bases. AISTATS 2022: 6968-6989 - [c247]Elvis Nava, Mojmir Mutny, Andreas Krause:
Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processes. AISTATS 2022: 7031-7054 - [c246]Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias W. Seeger, Cédric Archambeau:
Automatic Termination for Hyperparameter Optimization. AutoML 2022: 7/1-21 - [c245]Sebastian Curi, Armin Lederer, Sandra Hirche, Andreas Krause:
Safe Reinforcement Learning via Confidence-Based Filters. CDC 2022: 3409-3415 - [c244]Mohammad Reza Karimi, Ya-Ping Hsieh, Panayotis Mertikopoulos, Andreas Krause:
The Dynamics of Riemannian Robbins-Monro Algorithms. COLT 2022: 3503 - [c243]Jonas Rothfuss, Christopher Koenig, Alisa Rupenyan, Andreas Krause:
Meta-Learning Priors for Safe Bayesian Optimization. CoRL 2022: 237-265 - [c242]Yarden As, Ilnura Usmanova, Sebastian Curi, Andreas Krause:
Constrained Policy Optimization via Bayesian World Models. ICLR 2022 - [c241]Yatao Bian, Yu Rong, Tingyang Xu, Jiaxiang Wu, Andreas Krause, Junzhou Huang:
Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning. ICLR 2022 - [c240]Octavian-Eugen Ganea, Xinyuan Huang, Charlotte Bunne, Yatao Bian, Regina Barzilay, Tommi S. Jaakkola, Andreas Krause:
Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking. ICLR 2022 - [c239]Edoardo Caldarelli, Philippe Wenk, Stefan Bauer, Andreas Krause:
Adaptive Gaussian Process Change Point Detection. ICML 2022: 2542-2571 - [c238]Parnian Kassraie, Jonas Rothfuss, Andreas Krause:
Meta-Learning Hypothesis Spaces for Sequential Decision-making. ICML 2022: 10802-10824 - [c237]David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause:
Interactively Learning Preference Constraints in Linear Bandits. ICML 2022: 13505-13527 - [c236]Max B. Paulus, Giulia Zarpellon, Andreas Krause, Laurent Charlin, Chris J. Maddison:
Learning to Cut by Looking Ahead: Cutting Plane Selection via Imitation Learning. ICML 2022: 17584-17600 - [c235]Pier Giuseppe Sessa, Maryam Kamgarpour, Andreas Krause:
Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation. ICML 2022: 19580-19597 - [c234]Ilija Bogunovic, Zihan Li, Andreas Krause, Jonathan Scarlett:
A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits. NeurIPS 2022 - [c233]Charlotte Bunne, Andreas Krause, Marco Cuturi:
Supervised Training of Conditional Monge Maps. NeurIPS 2022 - [c232]Parnian Kassraie, Andreas Krause, Ilija Bogunovic:
Graph Neural Network Bandits. NeurIPS 2022 - [c231]David Lindner, Andreas Krause, Giorgia Ramponi:
Active Exploration for Inverse Reinforcement Learning. NeurIPS 2022 - [c230]Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf:
Amortized Inference for Causal Structure Learning. NeurIPS 2022 - [c229]Mojmir Mutny, Andreas Krause:
Experimental Design for Linear Functionals in Reproducing Kernel Hilbert Spaces. NeurIPS 2022 - [c228]Manish Prajapat, Matteo Turchetta, Melanie N. Zeilinger, Andreas Krause:
Near-Optimal Multi-Agent Learning for Safe Coverage Control. NeurIPS 2022 - [c227]Shyam Sundhar Ramesh, Pier Giuseppe Sessa, Andreas Krause, Ilija Bogunovic:
Movement Penalized Bayesian Optimization with Application to Wind Energy Systems. NeurIPS 2022 - [c226]Christian Toth, Lars Lorch, Christian Knoll, Andreas Krause, Franz Pernkopf, Robert Peharz, Julius von Kügelgen:
Active Bayesian Causal Inference. NeurIPS 2022 - [c225]Matteo Turchetta, Luca Corinzia, Scott Sussex, Amanda Burton, Juan Herrera, Ioannis Athanasiadis, Joachim M. Buhmann, Andreas Krause:
Learning Long-Term Crop Management Strategies with CyclesGym. NeurIPS 2022 - [i185]Bhavya Sukhija, Matteo Turchetta, David Lindner, Andreas Krause, Sebastian Trimpe, Dominik Baumann:
Scalable Safe Exploration for Global Optimization of Dynamical Systems. CoRR abs/2201.09562 (2022) - [i184]Yarden As, Ilnura Usmanova, Sebastian Curi, Andreas Krause:
Constrained Policy Optimization via Bayesian World Models. CoRR abs/2201.09802 (2022) - [i183]Parnian Kassraie, Jonas Rothfuss, Andreas Krause:
Meta-Learning Hypothesis Spaces for Sequential Decision-making. CoRR abs/2202.00602 (2022) - [i182]Ilija Bogunovic, Zihan Li, Andreas Krause, Jonathan Scarlett:
A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits. CoRR abs/2202.01850 (2022) - [i181]Charlotte Bunne, Ya-Ping Hsieh, Marco Cuturi, Andreas Krause:
Recovering Stochastic Dynamics via Gaussian Schrödinger Bridges. CoRR abs/2202.05722 (2022) - [i180]Pier Giuseppe Sessa, Maryam Kamgarpour, Andreas Krause:
Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation. CoRR abs/2203.07322 (2022) - [i179]Johannes Kirschner, Mojmír Mutný, Andreas Krause, Jaime Coello de Portugal, Nicole Hiller, Jochem Snuverink:
Tuning Particle Accelerators with Safety Constraints using Bayesian Optimization. CoRR abs/2203.13968 (2022) - [i178]Vignesh Ram Somnath, Charlotte Bunne, Andreas Krause:
Multi-Scale Representation Learning on Proteins. CoRR abs/2204.02337 (2022) - [i177]Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf:
Amortized Inference for Causal Structure Learning. CoRR abs/2205.12934 (2022) - [i176]Mojmír Mutný, Andreas Krause:
Experimental Design for Linear Functionals in Reproducing Kernel Hilbert Spaces. CoRR abs/2205.13627 (2022) - [i175]Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause:
BaCaDI: Bayesian Causal Discovery with Unknown Interventions. CoRR abs/2206.01665 (2022) - [i174]Christian Toth, Lars Lorch, Christian Knoll, Andreas Krause, Franz Pernkopf, Robert Peharz, Julius von Kügelgen:
Active Bayesian Causal Inference. CoRR abs/2206.02063 (2022) - [i173]David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause:
Interactively Learning Preference Constraints in Linear Bandits. CoRR abs/2206.05255 (2022) - [i172]Mohammad Reza Karimi, Ya-Ping Hsieh, Panayotis Mertikopoulos, Andreas Krause:
The Dynamics of Riemannian Robbins-Monro Algorithms. CoRR abs/2206.06795 (2022) - [i171]Mathieu Chevalley, Charlotte Bunne, Andreas Krause, Stefan Bauer:
Invariant Causal Mechanisms through Distribution Matching. CoRR abs/2206.11646 (2022) - [i170]Max B. Paulus, Giulia Zarpellon, Andreas Krause, Laurent Charlin, Chris J. Maddison:
Learning To Cut By Looking Ahead: Cutting Plane Selection via Imitation Learning. CoRR abs/2206.13414 (2022) - [i169]Charlotte Bunne, Andreas Krause, Marco Cuturi:
Supervised Training of Conditional Monge Maps. CoRR abs/2206.14262 (2022) - [i168]Mojmír Mutný, Tadeusz Janik, Andreas Krause:
Active Exploration via Experiment Design in Markov Chains. CoRR abs/2206.14332 (2022) - [i167]Sebastian Curi, Armin Lederer, Sandra Hirche, Andreas Krause:
Safe Reinforcement Learning via Confidence-Based Filters. CoRR abs/2207.01337 (2022) - [i166]Parnian Kassraie, Andreas Krause, Ilija Bogunovic:
Graph Neural Network Bandits. CoRR abs/2207.06456 (2022) - [i165]David Lindner, Andreas Krause, Giorgia Ramponi:
Active Exploration for Inverse Reinforcement Learning. CoRR abs/2207.08645 (2022) - [i164]Ilnura Usmanova, Yarden As, Maryam Kamgarpour, Andreas Krause:
Log Barriers for Safe Black-box Optimization with Application to Safe Reinforcement Learning. CoRR abs/2207.10415 (2022) - [i163]Jonas Rothfuss, Christopher Koenig, Alisa Rupenyan, Andreas Krause:
Meta-Learning Priors for Safe Bayesian Optimization. CoRR abs/2210.00762 (2022) - [i162]Hossein Esfandiari, Alkis Kalavasis, Amin Karbasi, Andreas Krause, Vahab Mirrokni, Grigoris Velegkas:
Reproducible Bandits. CoRR abs/2210.01898 (2022) - [i161]Manish Prajapat, Matteo Turchetta, Melanie N. Zeilinger, Andreas Krause:
Near-Optimal Multi-Agent Learning for Safe Coverage Control. CoRR abs/2210.06380 (2022) - [i160]Shyam Sundhar Ramesh, Pier Giuseppe Sessa, Andreas Krause, Ilija Bogunovic:
Movement Penalized Bayesian Optimization with Application to Wind Energy Systems. CoRR abs/2210.08087 (2022) - [i159]Krunoslav Lehman Pavasovic, Jonas Rothfuss, Andreas Krause:
MARS: Meta-Learning as Score Matching in the Function Space. CoRR abs/2210.13319 (2022) - [i158]Mohammad Reza Karimi, Ya-Ping Hsieh, Andreas Krause:
A Dynamical System View of Langevin-Based Non-Convex Sampling. CoRR abs/2210.13867 (2022) - [i157]Jonas Gehring, Deepak Gopinath, Jungdam Won, Andreas Krause, Gabriel Synnaeve, Nicolas Usunier:
Leveraging Demonstrations with Latent Space Priors. CoRR abs/2210.14685 (2022) - [i156]Felix Schur, Parnian Kassraie, Jonas Rothfuss, Andreas Krause:
Lifelong Bandit Optimization: No Prior and No Regret. CoRR abs/2210.15513 (2022) - [i155]Songyan Hou, Parnian Kassraie, Anastasis Kratsios, Jonas Rothfuss, Andreas Krause:
Instance-Dependent Generalization Bounds via Optimal Transport. CoRR abs/2211.01258 (2022) - [i154]Viacheslav Borovitskiy, Mohammad Reza Karimi, Vignesh Ram Somnath, Andreas Krause:
Isotropic Gaussian Processes on Finite Spaces of Graphs. CoRR abs/2211.01689 (2022) - [i153]Jonas Rothfuss, Martin Josifoski, Vincent Fortuin, Andreas Krause:
PAC-Bayesian Meta-Learning: From Theory to Practice. CoRR abs/2211.07206 (2022) - [i152]Scott Sussex, Anastasiia Makarova, Andreas Krause:
Model-based Causal Bayesian Optimization. CoRR abs/2211.10257 (2022) - [i151]Xiang Li, Viraj Mehta, Johannes Kirschner, Ian Char, Willie Neiswanger, Jeff Schneider, Andreas Krause, Ilija Bogunovic:
Near-optimal Policy Identification in Active Reinforcement Learning. CoRR abs/2212.09510 (2022) - 2021
- [c224]Chris Wendler, Andisheh Amrollahi, Bastian Seifert, Andreas Krause, Markus Püschel:
Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases. AAAI 2021: 10283-10292 - [c223]Mohammad Yaghini, Andreas Krause, Hoda Heidari:
A Human-in-the-loop Framework to Construct Context-aware Mathematical Notions of Outcome Fairness. AIES 2021: 1023-1033 - [c222]Mohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlas, Johannes Rausch, Ce Zhang, Andreas Krause:
Online Active Model Selection for Pre-trained Classifiers. AISTATS 2021: 307-315 - [c221]Ilija Bogunovic, Arpan Losalka, Andreas Krause, Jonathan Scarlett:
Stochastic Linear Bandits Robust to Adversarial Attacks. AISTATS 2021: 991-999 - [c220]Joan Bas-Serrano, Sebastian Curi, Andreas Krause, Gergely Neu:
Logistic Q-Learning. AISTATS 2021: 3610-3618 - [c219]Marc Jourdan, Mojmír Mutný, Johannes Kirschner, Andreas Krause:
Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback. ALT 2021: 805-849 - [c218]Zalán Borsos, Marco Tagliasacchi, Andreas Krause:
Semi-Supervised Batch Active Learning Via Bilevel Optimization. ICASSP 2021: 3495-3499 - [c217]Mikhail Usvyatsov, Anastasia Makarova, Rafael Ballester-Ripoll, Maxim V. Rakhuba, Andreas Krause, Konrad Schindler:
Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation. ICCV 2021: 11406-11415 - [c216]Max B. Paulus, Chris J. Maddison, Andreas Krause:
Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator. ICLR 2021 - [c215]Núria Armengol Urpí, Sebastian Curi, Andreas Krause:
Risk-Averse Offline Reinforcement Learning. ICLR 2021 - [c214]Sebastian Curi, Ilija Bogunovic, Andreas Krause:
Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning. ICML 2021: 2254-2264 - [c213]Johannes Kirschner, Andreas Krause:
Bias-Robust Bayesian Optimization via Dueling Bandits. ICML 2021: 5595-5605 - [c212]Mojmir Mutny, Andreas Krause:
No-regret Algorithms for Capturing Events in Poisson Point Processes. ICML 2021: 7894-7904 - [c211]Jonas Rothfuss, Vincent Fortuin, Martin Josifoski, Andreas Krause:
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees. ICML 2021: 9116-9126 - [c210]Pier Giuseppe Sessa, Ilija Bogunovic, Andreas Krause, Maryam Kamgarpour:
Online Submodular Resource Allocation with Applications to Rebalancing Shared Mobility Systems. ICML 2021: 9455-9464 - [c209]Carl-Johann Simon-Gabriel, Noman Ahmed Sheikh, Andreas Krause:
PopSkipJump: Decision-Based Attack for Probabilistic Classifiers. ICML 2021: 9712-9721 - [c208]Ilnura Usmanova, Maryam Kamgarpour, Andreas Krause, Kfir Y. Levy:
Fast Projection Onto Convex Smooth Constraints. ICML 2021: 10476-10486 - [c207]Christopher König, Matteo Turchetta, John Lygeros, Alisa Rupenyan, Andreas Krause:
Safe and Efficient Model-free Adaptive Control via Bayesian Optimization. ICRA 2021: 9782-9788 - [c206]David Lindner, Hoda Heidari, Andreas Krause:
Addressing the Long-term Impact of ML Decisions via Policy Regret. IJCAI 2021: 537-544 - [c205]Lenart Treven, Sebastian Curi, Mojmír Mutný, Andreas Krause:
Learning Stabilizing Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory. L4DC 2021: 664-676 - [c204]Jonas Rothfuss, Dominique Heyn, Jinfan Chen, Andreas Krause:
Meta-Learning Reliable Priors in the Function Space. NeurIPS 2021: 280-293 - [c203]Scott Sussex, Caroline Uhler, Andreas Krause:
Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning. NeurIPS 2021: 777-788 - [c202]Ilija Bogunovic, Andreas Krause:
Misspecified Gaussian Process Bandit Optimization. NeurIPS 2021: 3004-3015 - [c201]David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause:
Information Directed Reward Learning for Reinforcement Learning. NeurIPS 2021: 3850-3862 - [c200]Manuel Wüthrich, Bernhard Schölkopf, Andreas Krause:
Regret Bounds for Gaussian-Process Optimization in Large Domains. NeurIPS 2021: 7385-7396 - [c199]Vignesh Ram Somnath, Charlotte Bunne, Connor W. Coley, Andreas Krause, Regina Barzilay:
Learning Graph Models for Retrosynthesis Prediction. NeurIPS 2021: 9405-9415 - [c198]Jonas Gehring, Gabriel Synnaeve, Andreas Krause, Nicolas Usunier:
Hierarchical Skills for Efficient Exploration. NeurIPS 2021: 11553-11564 - [c197]Andreas Schlaginhaufen, Philippe Wenk, Andreas Krause, Florian Dörfler:
Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems. NeurIPS 2021: 11870-11882 - [c196]