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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
- 2022
[c228]Parnian Kassraie, Andreas Krause:
Neural Contextual Bandits without Regret. AISTATS 2022: 240-278- [c227]Charlotte Bunne, Laetitia Papaxanthos, Andreas Krause, Marco Cuturi:
Proximal Optimal Transport Modeling of Population Dynamics. AISTATS 2022: 6511-6528 - [c226]Mojmir Mutny, Andreas Krause:
Sensing Cox Processes via Posterior Sampling and Positive Bases. AISTATS 2022: 6968-6989 - [c225]Elvis Nava, Mojmir Mutny, Andreas Krause:
Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processes. AISTATS 2022: 7031-7054 - [i165]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) - [i164]Yarden As, Ilnura Usmanova, Sebastian Curi, Andreas Krause:
Constrained Policy Optimization via Bayesian World Models. CoRR abs/2201.09802 (2022) - [i163]Parnian Kassraie, Jonas Rothfuss, Andreas Krause:
Meta-Learning Hypothesis Spaces for Sequential Decision-making. CoRR abs/2202.00602 (2022) - [i162]Ilija Bogunovic, Zihan Li, Andreas Krause, Jonathan Scarlett:
A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits. CoRR abs/2202.01850 (2022) - [i161]Charlotte Bunne, Ya-Ping Hsieh, Marco Cuturi, Andreas Krause:
Recovering Stochastic Dynamics via Gaussian Schrödinger Bridges. CoRR abs/2202.05722 (2022) - [i160]Pier Giuseppe Sessa, Maryam Kamgarpour, Andreas Krause:
Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation. CoRR abs/2203.07322 (2022) - [i159]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) - [i158]Vignesh Ram Somnath, Charlotte Bunne, Andreas Krause:
Multi-Scale Representation Learning on Proteins. CoRR abs/2204.02337 (2022) - [i157]Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf:
Amortized Inference for Causal Structure Learning. CoRR abs/2205.12934 (2022) - [i156]Mojmír Mutný, Andreas Krause:
Experimental Design for Linear Functionals in Reproducing Kernel Hilbert Spaces. CoRR abs/2205.13627 (2022) - [i155]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) - [i154]Christian Toth, Lars Lorch, Christian Knoll, Andreas Krause, Franz Pernkopf, Robert Peharz, Julius von Kügelgen:
Active Bayesian Causal Inference. CoRR abs/2206.02063 (2022) - [i153]David Lindner, Sebastian Tschiatschek, Katja Hofmann, Andreas Krause:
Interactively Learning Preference Constraints in Linear Bandits. CoRR abs/2206.05255 (2022) - [i152]Mohammad Reza Karimi, Ya-Ping Hsieh, Panayotis Mertikopoulos, Andreas Krause:
The Dynamics of Riemannian Robbins-Monro Algorithms. CoRR abs/2206.06795 (2022) - [i151]Mathieu Chevalley, Charlotte Bunne, Andreas Krause, Stefan Bauer:
Invariant Causal Mechanisms through Distribution Matching. CoRR abs/2206.11646 (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 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]Anastasia Makarova, Ilnura Usmanova, Ilija Bogunovic, Andreas Krause:
Risk-averse Heteroscedastic Bayesian Optimization. NeurIPS 2021: 17235-17245 - [c195]Lars Lorch, Jonas Rothfuss, Bernhard Schölkopf, Andreas Krause:
DiBS: Differentiable Bayesian Structure Learning. NeurIPS 2021: 24111-24123 - [c194]Vignesh Ram Somnath, Charlotte Bunne, Andreas Krause:
Multi-Scale Representation Learning on Proteins. NeurIPS 2021: 25244-25255 - [c193]Tobias Sutter, Andreas Krause, Daniel Kuhn:
Robust Generalization despite Distribution Shift via Minimum Discriminating Information. NeurIPS 2021: 29754-29767 - [c192]Lenart Treven, Philippe Wenk, Florian Dörfler, Andreas Krause:
Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models. NeurIPS 2021: 29780-29793 - [i150]Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David M. Pennock, Andreas Krause:
Incentive-Compatible Forecasting Competitions. CoRR abs/2101.01816 (2021) - [i149]Christopher König, Matteo Turchetta, John Lygeros, Alisa Rupenyan, Andreas Krause:
Safe and Efficient Model-free Adaptive Control via Bayesian Optimization. CoRR abs/2101.07825 (2021) - [i148]Marc Jourdan, Mojmír Mutný, Johannes Kirschner, Andreas Krause:
Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback. CoRR abs/2101.08534 (2021) - [i147]Núria Armengol Urpi, Sebastian Curi, Andreas Krause:
Risk-Averse Offline Reinforcement Learning. CoRR abs/2102.05371 (2021) - [i146]David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause:
Information Directed Reward Learning for Reinforcement Learning. CoRR abs/2102.12466 (2021) - [i145]Sebastian Curi, Ilija Bogunovic, Andreas Krause:
Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning. CoRR abs/2103.10369 (2021) - [i144]Anastasia Makarova, Huibin Shen, Valerio Perrone, Aaron Klein, Jean Baptiste Faddoul, Andreas Krause, Matthias W. Seeger, Cédric Archambeau:
Overfitting in Bayesian Optimization: an empirical study and early-stopping solution. CoRR abs/2104.08166 (2021) - [i143]Manuel Wüthrich, Bernhard Schölkopf, Andreas Krause:
Regret Bounds for Gaussian-Process Optimization in Large Domains. CoRR abs/2104.14113 (2021) - [i142]Johannes Kirschner, Andreas Krause:
Bias-Robust Bayesian Optimization via Dueling Bandit. CoRR abs/2105.11802 (2021) - [i141]Lars Lorch, Jonas Rothfuss, Bernhard Schölkopf, Andreas Krause:
DiBS: Differentiable Bayesian Structure Learning. CoRR abs/2105.11839 (2021) - [i140]Scott Sussex, Andreas Krause, Caroline Uhler:
Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning. CoRR abs/2105.14024 (2021) - [i139]Mikhail Usvyatsov, Anastasia Makarova, Rafael Ballester-Ripoll, Maxim Rakhuba, Andreas Krause, Konrad Schindler:
Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation. CoRR abs/2105.14250 (2021) - [i138]David Lindner, Hoda Heidari, Andreas Krause:
Addressing the Long-term Impact of ML Decisions via Policy Regret. CoRR abs/2106.01325 (2021) - [i137]Yatao Bian, Yu Rong, Tingyang Xu, Jiaxiang Wu, Andreas Krause, Junzhou Huang:
Energy-Based Learning for Cooperative Games, with Applications to Feature/Data/Model Valuations. CoRR abs/2106.02938 (2021) - [i136]Jonas Rothfuss, Dominique Heyn, Jinfan Chen, Andreas Krause:
Meta-Learning Reliable Priors in the Function Space. CoRR abs/2106.03195 (2021) - [i135]Tobias Sutter, Andreas Krause, Daniel Kuhn:
Robust Generalization despite Distribution Shift via Minimum Discriminating Information. CoRR abs/2106.04443 (2021) - [i134]Charlotte Bunne, Laetitia Meng-Papaxanthos, Andreas Krause, Marco Cuturi:
JKOnet: Proximal Optimal Transport Modeling of Population Dynamics. CoRR abs/2106.06345 (2021) - [i133]Carl-Johann Simon-Gabriel, Noman Ahmed Sheikh, Andreas Krause:
PopSkipJump: Decision-Based Attack for Probabilistic Classifiers. CoRR abs/2106.07445 (2021) - [i132]Lenart Treven, Philippe Wenk, Florian Dörfler, Andreas Krause:
Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models. CoRR abs/2106.11609 (2021) - [i131]Parnian Kassraie, Andreas Krause:
Neural Contextual Bandits without Regret. CoRR abs/2107.03144 (2021) - [i130]Barna Pásztor, Ilija Bogunovic, Andreas Krause:
Efficient Model-Based Multi-Agent Mean-Field Reinforcement Learning. CoRR abs/2107.04050 (2021) - [i129]Pier Giuseppe Sessa, Ilija Bogunovic, Andreas Krause, Maryam Kamgarpour:
Contextual Games: Multi-Agent Learning with Side Information. CoRR abs/2107.06327 (2021) - [i128]Zalán Borsos, Mojmír Mutný, Marco Tagliasacchi, Andreas Krause:
Data Summarization via Bilevel Optimization. CoRR abs/2109.12534 (2021) - [i127]Jonas Gehring, Gabriel Synnaeve, Andreas Krause, Nicolas Usunier:
Hierarchical Skills for Efficient Exploration. CoRR abs/2110.10809 (2021) - [i126]Mojmír Mutný, Andreas Krause:
Sensing Cox Processes via Posterior Sampling and Positive Bases. CoRR abs/2110.11181 (2021) - [i125]Elvis Nava, Mojmír Mutný, Andreas Krause:
Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processes. CoRR abs/2110.11665 (2021) - [i124]Andreas Schlaginhaufen, Philippe Wenk, Andreas Krause, Florian Dörfler:
Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems. CoRR abs/2110.14296 (2021) - [i123]Anastasia Makarova, Ilnura Usmanova, Ilija Bogunovic, Andreas Krause:
Risk-averse Heteroscedastic Bayesian Optimization. CoRR abs/2111.03637 (2021) - [i122]Ilija Bogunovic, Andreas Krause:
Misspecified Gaussian Process Bandit Optimization. CoRR abs/2111.05008 (2021) - [i121]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. CoRR abs/2111.07786 (2021) - 2020
- [j30]Pragnya Alatur, Kfir Y. Levy, Andreas Krause:
Multi-Player Bandits: The Adversarial Case. J. Mach. Learn. Res. 21: 77:1-77:23 (2020) - [c191]Philippe Wenk, Gabriele Abbati, Michael A. Osborne, Bernhard Schölkopf, Andreas Krause, Stefan Bauer:
ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems. AAAI 2020: 6364-6371 - [c190]Mojmir Mutny, Johannes Kirschner, Andreas Krause:
Experimental Design for Optimization of Orthogonal Projection Pursuit Models. AAAI 2020: 10235-10242 - [c189]Ilija Bogunovic, Andreas Krause, Jonathan Scarlett:
Corruption-Tolerant Gaussian Process Bandit Optimization. AISTATS 2020: 1071-1081 - [c188]Johannes Kirschner, Ilija Bogunovic, Stefanie Jegelka, Andreas Krause:
Distributionally Robust Bayesian Optimization. AISTATS 2020: 2174-2184 - [c187]Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause:
Mixed Strategies for Robust Optimization of Unknown Objectives. AISTATS 2020: 2970-2980 - [c186]Mojmir Mutny, Michal Derezinski, Andreas Krause:
Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling. AISTATS 2020: 3110-3120 - [c185]Johannes Kirschner, Tor Lattimore, Andreas Krause:
Information Directed Sampling for Linear Partial Monitoring. COLT 2020: 2328-2369 - [c184]Ankit Dhall, Anastasia Makarova, Octavian Ganea, Dario Pavllo, Michael Greeff, Andreas Krause:
Hierarchical Image Classification using Entailment Cone Embeddings. CVPR Workshops 2020: 3649-3658 - [c183]Aytunc Sahin, Yatao Bian, Joachim M. Buhmann, Andreas Krause:
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models. ICML 2020: 8388-8397 - [c182]Diego Agudelo-España, Andrii Zadaianchuk, Philippe Wenk, Aditya Garg, Joel Akpo, Felix Grimminger, Julian Viereck, Maximilien Naveau, Ludovic Righetti, Georg Martius, Andreas Krause, Bernhard Schölkopf, Stefan Bauer, Manuel Wüthrich:
A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models. ICRA 2020: 8151-8157 - [c181]Matteo Turchetta, Andreas Krause, Sebastian Trimpe:
Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization. ICRA 2020: 10702-10708 - [c180]Erik A. Daxberger, Anastasia Makarova, Matteo Turchetta, Andreas Krause:
Mixed-Variable Bayesian Optimization. IJCAI 2020: 2633-2639 - [c179]Sebastian Curi, Silvan Melchior, Felix Berkenkamp, Andreas Krause:
Structured Variational Inference in Partially Observable UnstableGaussian Process State Space Models. L4DC 2020: 147-157 - [c178]Ilnura Usmanova, Andreas Krause, Maryam Kamgarpour:
Safe non-smooth black-box optimization with application to policy search. L4DC 2020: 980-989 - [c177]Zalán Borsos, Mojmir Mutny, Andreas Krause:
Coresets via Bilevel Optimization for Continual Learning and Streaming. NeurIPS 2020 - [c176]Sebastian Curi, Felix Berkenkamp, Andreas Krause:
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning. NeurIPS 2020 - [c175]Sebastian Curi, Kfir Y. Levy, Stefanie Jegelka, Andreas Krause:
Adaptive Sampling for Stochastic Risk-Averse Learning. NeurIPS 2020 - [c174]Max B. Paulus, Dami Choi, Daniel Tarlow, Andreas Krause, Chris J. Maddison:
Gradient Estimation with Stochastic Softmax Tricks. NeurIPS 2020 - [c173]Pier Giuseppe Sessa, Ilija Bogunovic, Andreas Krause, Maryam Kamgarpour:
Contextual Games: Multi-Agent Learning with Side Information. NeurIPS 2020 - [c172]Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause:
Learning to Play Sequential Games versus Unknown Opponents. NeurIPS 2020 - [c171]Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal:
Safe Reinforcement Learning via Curriculum Induction. NeurIPS 2020 - [i120]Jonas Rothfuss, Vincent Fortuin, Andreas Krause:
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees. CoRR abs/2002.05551 (2020) - [i119]Johannes Kirschner, Ilija Bogunovic, Stefanie Jegelka, Andreas Krause:
Distributionally Robust Bayesian Optimization. CoRR abs/2002.09038 (2020) - [i118]Johannes Kirschner, Tor Lattimore, Andreas Krause:
Information Directed Sampling for Linear Partial Monitoring. CoRR abs/2002.11182 (2020) - [i117]Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause:
Mixed Strategies for Robust Optimization of Unknown Objectives. CoRR abs/2002.12613 (2020) - [i116]Ilija Bogunovic, Andreas Krause, Jonathan Scarlett:
Corruption-Tolerant Gaussian Process Bandit Optimization. CoRR abs/2003.01971 (2020) - [i115]Emmanouil Angelis, Philippe Wenk, Bernhard Schölkopf, Stefan Bauer, Andreas Krause:
SLEIPNIR: Deterministic and Provably Accurate Feature Expansion for Gaussian Process Regression with Derivatives. CoRR abs/2003.02658 (2020) - [i114]Ankit Dhall, Anastasia Makarova, Octavian Ganea, Dario Pavllo, Michael Greeff, Andreas Krause:
Hierarchical Image Classification using Entailment Cone Embeddings. CoRR abs/2004.03459 (2020) - [i113]Aytunc Sahin, Yatao Bian, Joachim M. Buhmann, Andreas Krause:
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models. CoRR abs/2006.01293 (2020) - [i112]Zalán Borsos, Mojmír Mutný, Andreas Krause:
Coresets via Bilevel Optimization for Continual Learning and Streaming. CoRR abs/2006.03875 (2020) - [i111]Vignesh Ram Somnath, Charlotte Bunne, Connor W. Coley, Andreas Krause, Regina Barzilay:
Learning Graph Models for Template-Free Retrosynthesis. CoRR abs/2006.07038 (2020) - [i110]Max B. Paulus, Dami Choi, Daniel Tarlow, Andreas Krause, Chris J. Maddison:
Gradient Estimation with Stochastic Softmax Tricks. CoRR abs/2006.08063 (2020) - [i109]Sebastian Curi, Felix Berkenkamp, Andreas Krause:
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning. CoRR abs/2006.08684 (2020) - [i108]Lenart Treven, Sebastian Curi, Mojmir Mutny, Andreas Krause:
Learning Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory. CoRR abs/2006.11022 (2020) - [i107]Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal:
Safe Reinforcement Learning via Curriculum Induction. CoRR abs/2006.12136 (2020) - [i106]Yatao Bian, Joachim M. Buhmann, Andreas Krause:
Continuous Submodular Function Maximization. CoRR abs/2006.13474 (2020) - [i105]Ilija Bogunovic, Arpan Losalka, Andreas Krause, Jonathan Scarlett:
Stochastic Linear Bandits Robust to Adversarial Attacks. CoRR abs/2007.03285 (2020) - [i104]Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause:
Learning to Play Sequential Games versus Unknown Opponents. CoRR abs/2007.05271 (2020) - [i103]Chris Wendler, Andisheh Amrollahi, Bastian Seifert, Andreas Krause, Markus Püschel:
Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases. CoRR abs/2010.00439 (2020) - [i102]Max B. Paulus, Chris J. Maddison, Andreas Krause:
Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator. CoRR abs/2010.04838 (2020) - [i101]Zalán Borsos, Marco Tagliasacchi, Andreas Krause:
Semi-supervised Batch Active Learning via Bilevel Optimization. CoRR abs/2010.09654 (2020) - [i100]Mohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlas, Johannes Rausch, Ce Zhang, Andreas Krause:
Online Active Model Selection for Pre-trained Classifiers. CoRR abs/2010.09818 (2020) - [i99]Joan Bas-Serrano, Sebastian Curi, Andreas Krause, Gergely Neu:
Logistic $Q$-Learning. CoRR abs/2010.11151 (2020)
2010 – 2019
- 2019
- [j29]Veselin Raychev, Martin T. Vechev, Andreas Krause:
Predicting program properties from 'big code'. Commun. ACM 62(3): 99-107 (2019) - [j28]Felix Berkenkamp, Angela P. Schoellig, Andreas Krause:
No-Regret Bayesian Optimization with Unknown Hyperparameters. J. Mach. Learn. Res. 20: 50:1-50:24 (2019) - [c170]Philippe Wenk, Alkis Gotovos, Stefan Bauer, Nico S. Gorbach, Andreas Krause, Joachim M. Buhmann:
Fast Gaussian process based gradient matching for parameter identification in systems of nonlinear ODEs. AISTATS 2019: 1351-1360 - [c169]Kfir Y. Levy, Andreas Krause:
Projection Free Online Learning over Smooth Sets. AISTATS 2019: 1458-1466 - [c168]Pier Giuseppe Sessa, Maryam Kamgarpour, Andreas Krause:
Bounding Inefficiency of Equilibria in Continuous Actions Games using Submodularity and Curvature. AISTATS 2019: 2017-2027 - [c167]