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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
- 2021
[i123]Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David M. Pennock, Andreas Krause:
Incentive-Compatible Forecasting Competitions. CoRR abs/2101.01816 (2021)- [i122]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) - [i121]Marc Jourdan, Mojmír Mutný, Johannes Kirschner, Andreas Krause:
Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback. CoRR abs/2101.08534 (2021) - [i120]Núria Armengol Urpi, Sebastian Curi, Andreas Krause:
Risk-Averse Offline Reinforcement Learning. CoRR abs/2102.05371 (2021) - [i119]David Lindner, Matteo Turchetta, Sebastian Tschiatschek, Kamil Ciosek, Andreas Krause:
Information Directed Reward Learning for Reinforcement Learning. CoRR abs/2102.12466 (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) - [c190]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 - [c189]Mojmir Mutny, Johannes Kirschner, Andreas Krause:
Experimental Design for Optimization of Orthogonal Projection Pursuit Models. AAAI 2020: 10235-10242 - [c188]Ilija Bogunovic, Andreas Krause, Jonathan Scarlett:
Corruption-Tolerant Gaussian Process Bandit Optimization. AISTATS 2020: 1071-1081 - [c187]Johannes Kirschner, Ilija Bogunovic, Stefanie Jegelka, Andreas Krause:
Distributionally Robust Bayesian Optimization. AISTATS 2020: 2174-2184 - [c186]Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause:
Mixed Strategies for Robust Optimization of Unknown Objectives. AISTATS 2020: 2970-2980 - [c185]Mojmir Mutny, Michal Derezinski, Andreas Krause:
Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling. AISTATS 2020: 3110-3120 - [c184]Johannes Kirschner, Tor Lattimore, Andreas Krause:
Information Directed Sampling for Linear Partial Monitoring. COLT 2020: 2328-2369 - [c183]Ankit Dhall, Anastasia Makarova, Octavian Ganea, Dario Pavllo, Michael Greeff, Andreas Krause:
Hierarchical Image Classification using Entailment Cone Embeddings. CVPR Workshops 2020: 3649-3658 - [c182]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 - [c181]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 - [c180]Matteo Turchetta, Andreas Krause, Sebastian Trimpe:
Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization. ICRA 2020: 10702-10708 - [c179]Erik A. Daxberger, Anastasia Makarova, Matteo Turchetta, Andreas Krause:
Mixed-Variable Bayesian Optimization. IJCAI 2020: 2633-2639 - [c178]Sebastian Curi, Silvan Melchior, Felix Berkenkamp, Andreas Krause:
Structured Variational Inference in Partially Observable UnstableGaussian Process State Space Models. L4DC 2020: 147-157 - [c177]Ilnura Usmanova, Andreas Krause, Maryam Kamgarpour:
Safe non-smooth black-box optimization with application to policy search. L4DC 2020: 980-989 - [c176]Zalán Borsos, Mojmir Mutny, Andreas Krause:
Coresets via Bilevel Optimization for Continual Learning and Streaming. NeurIPS 2020 - [c175]Sebastian Curi, Felix Berkenkamp, Andreas Krause:
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning. NeurIPS 2020 - [c174]Sebastian Curi, Kfir Y. Levy, Stefanie Jegelka, Andreas Krause:
Adaptive Sampling for Stochastic Risk-Averse Learning. NeurIPS 2020 - [c173]Max B. Paulus, Dami Choi, Daniel Tarlow, Andreas Krause, Chris J. Maddison:
Gradient Estimation with Stochastic Softmax Tricks. NeurIPS 2020 - [c172]Pier Giuseppe Sessa, Ilija Bogunovic, Andreas Krause, Maryam Kamgarpour:
Contextual Games: Multi-Agent Learning with Side Information. NeurIPS 2020 - [c171]Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause:
Learning to Play Sequential Games versus Unknown Opponents. NeurIPS 2020 - [c170]Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal:
Safe Reinforcement Learning via Curriculum Induction. NeurIPS 2020 - [i118]Johannes Kirschner, Ilija Bogunovic, Stefanie Jegelka, Andreas Krause:
Distributionally Robust Bayesian Optimization. CoRR abs/2002.09038 (2020) - [i117]Johannes Kirschner, Tor Lattimore, Andreas Krause:
Information Directed Sampling for Linear Partial Monitoring. CoRR abs/2002.11182 (2020) - [i116]Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause:
Mixed Strategies for Robust Optimization of Unknown Objectives. CoRR abs/2002.12613 (2020) - [i115]Ilija Bogunovic, Andreas Krause, Jonathan Scarlett:
Corruption-Tolerant Gaussian Process Bandit Optimization. CoRR abs/2003.01971 (2020) - [i114]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) - [i113]Ankit Dhall, Anastasia Makarova, Octavian Ganea, Dario Pavllo, Michael Greeff, Andreas Krause:
Hierarchical Image Classification using Entailment Cone Embeddings. CoRR abs/2004.03459 (2020) - [i112]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) - [i111]Zalán Borsos, Mojmír Mutný, Andreas Krause:
Coresets via Bilevel Optimization for Continual Learning and Streaming. CoRR abs/2006.03875 (2020) - [i110]Vignesh Ram Somnath, Charlotte Bunne, Connor W. Coley, Andreas Krause, Regina Barzilay:
Learning Graph Models for Template-Free Retrosynthesis. CoRR abs/2006.07038 (2020) - [i109]Max B. Paulus, Dami Choi, Daniel Tarlow, Andreas Krause, Chris J. Maddison:
Gradient Estimation with Stochastic Softmax Tricks. CoRR abs/2006.08063 (2020) - [i108]Sebastian Curi, Felix Berkenkamp, Andreas Krause:
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning. CoRR abs/2006.08684 (2020) - [i107]Lenart Treven, Sebastian Curi, Mojmir Mutny, Andreas Krause:
Learning Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory. CoRR abs/2006.11022 (2020) - [i106]Matteo Turchetta, Andrey Kolobov, Shital Shah, Andreas Krause, Alekh Agarwal:
Safe Reinforcement Learning via Curriculum Induction. CoRR abs/2006.12136 (2020) - [i105]Yatao Bian, Joachim M. Buhmann, Andreas Krause:
Continuous Submodular Function Maximization. CoRR abs/2006.13474 (2020) - [i104]Ilija Bogunovic, Arpan Losalka, Andreas Krause, Jonathan Scarlett:
Stochastic Linear Bandits Robust to Adversarial Attacks. CoRR abs/2007.03285 (2020) - [i103]Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause:
Learning to Play Sequential Games versus Unknown Opponents. CoRR abs/2007.05271 (2020) - [i102]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) - [i101]Max B. Paulus, Chris J. Maddison, Andreas Krause:
Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator. CoRR abs/2010.04838 (2020) - [i100]Zalán Borsos, Marco Tagliasacchi, Andreas Krause:
Semi-supervised Batch Active Learning via Bilevel Optimization. CoRR abs/2010.09654 (2020) - [i99]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) - [i98]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) - [c169]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 - [c168]Kfir Y. Levy, Andreas Krause:
Projection Free Online Learning over Smooth Sets. AISTATS 2019: 1458-1466 - [c167]Pier Giuseppe Sessa, Maryam Kamgarpour, Andreas Krause:
Bounding Inefficiency of Equilibria in Continuous Actions Games using Submodularity and Curvature. AISTATS 2019: 2017-2027 - [c166]Ilnura Usmanova, Andreas Krause, Maryam Kamgarpour:
Safe Convex Learning under Uncertain Constraints. AISTATS 2019: 2106-2114 - [c165]Mohammad Reza Karimi Jaghargh, Andreas Krause, Silvio Lattanzi, Sergei Vassilvitskii:
Consistent Online Optimization: Convex and Submodular. AISTATS 2019: 2241-2250 - [c164]Sebastian Curi, Kfir Y. Levy, Andreas Krause:
Adaptive Input Estimation in Linear Dynamical Systems with Applications to Learning-from-Observations. CDC 2019: 4115-4120 - [c163]Robin Spiess, Felix Berkenkamp, Andreas Krause, Jan Poland:
Learning to Compensate Photovoltaic Power Fluctuations from Images of the Sky by Imitating an Optimal Policy. ECC 2019: 9-15 - [c162]Hoda Heidari, Michele Loi, Krishna P. Gummadi, Andreas Krause:
A Moral Framework for Understanding Fair ML through Economic Models of Equality of Opportunity. FAT 2019: 181-190 - [c161]Nikolay Nikolov, Johannes Kirschner, Felix Berkenkamp, Andreas Krause:
Information-Directed Exploration for Deep Reinforcement Learning. ICLR (Poster) 2019 - [c160]Gabriele Abbati, Philippe Wenk, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf, Stefan Bauer:
AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs. ICML 2019: 1-10 - [c159]Yatao An Bian, Joachim M. Buhmann, Andreas Krause:
Optimal Continuous DR-Submodular Maximization and Applications to Provable Mean Field Inference. ICML 2019: 644-653 - [c158]Zalán Borsos, Sebastian Curi, Kfir Yehuda Levy, Andreas Krause:
Online Variance Reduction with Mixtures. ICML 2019: 705-714 - [c157]Charlotte Bunne, David Alvarez-Melis, Andreas Krause, Stefanie Jegelka:
Learning Generative Models across Incomparable Spaces. ICML 2019: 851-861 - [c156]Johannes Kirschner, Mojmir Mutny, Nicole Hiller, Rasmus Ischebeck, Andreas Krause:
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces. ICML 2019: 3429-3438 - [c155]Marcello Fiducioso, Sebastian Curi, Benedikt Schumacher, Markus Gwerder, Andreas Krause:
Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning. IJCAI 2019: 5850-5856 - [c154]Megha Srivastava, Hoda Heidari, Andreas Krause:
Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning. KDD 2019: 2459-2468 - [c153]Matteo Turchetta, Felix Berkenkamp, Andreas Krause:
Safe Exploration for Interactive Machine Learning. NeurIPS 2019: 2887-2897 - [c152]Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla:
Teaching Multiple Concepts to a Forgetful Learner. NeurIPS 2019: 4050-4060 - [c151]Marko Mitrovic, Ehsan Kazemi, Moran Feldman, Andreas Krause, Amin Karbasi:
Adaptive Sequence Submodularity. NeurIPS 2019: 5353-5364 - [c150]Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Nathanaël Perraudin, Ian Goodfellow, Thomas Hofmann, Andreas Krause:
A Domain Agnostic Measure for Monitoring and Evaluating GANs. NeurIPS 2019: 12069-12079 - [c149]Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause:
No-Regret Learning in Unknown Games with Correlated Payoffs. NeurIPS 2019: 13602-13611 - [c148]Johannes Kirschner, Andreas Krause:
Stochastic Bandits with Context Distributions. NeurIPS 2019: 14090-14099 - [c147]Andisheh Amrollahi, Amir Zandieh, Michael Kapralov, Andreas Krause:
Efficiently Learning Fourier Sparse Set Functions. NeurIPS 2019: 15094-15103 - [i97]Felix Berkenkamp, Angela P. Schoellig, Andreas Krause:
No-regret Bayesian Optimization with Unknown Hyperparameters. CoRR abs/1901.03357 (2019) - [i96]Johannes Kirschner, Mojmír Mutný, Nicole Hiller, Rasmus Ischebeck, Andreas Krause:
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces. CoRR abs/1902.03229 (2019) - [i95]Megha Srivastava, Hoda Heidari, Andreas Krause:
Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning. CoRR abs/1902.04783 (2019) - [i94]Marko Mitrovic, Ehsan Kazemi, Moran Feldman, Andreas Krause, Amin Karbasi:
Adaptive Sequence Submodularity. CoRR abs/1902.05981 (2019) - [i93]Philippe Wenk, Gabriele Abbati, Stefan Bauer, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf:
ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems. CoRR abs/1902.06278 (2019) - [i92]Pragnya Alatur, Kfir Y. Levy, Andreas Krause:
Multi-Player Bandits: The Adversarial Case. CoRR abs/1902.08036 (2019) - [i91]Gabriele Abbati, Philippe Wenk, Stefan Bauer, Michael A. Osborne, Andreas Krause, Bernhard Schölkopf:
AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs. CoRR abs/1902.08480 (2019) - [i90]Pier Giuseppe Sessa, Maryam Kamgarpour, Andreas Krause:
Bounding Inefficiency of Equilibria in Continuous Actions Games using Submodularity and Curvature. CoRR abs/1903.00950 (2019) - [i89]Zalán Borsos, Sebastian Curi, Kfir Y. Levy, Andreas Krause:
Online Variance Reduction with Mixtures. CoRR abs/1903.12416 (2019) - [i88]Charlotte Bunne, David Alvarez-Melis, Andreas Krause, Stefanie Jegelka:
Learning Generative Models across Incomparable Spaces. CoRR abs/1905.05461 (2019) - [i87]Johannes Kirschner, Andreas Krause:
Stochastic Bandits with Context Distributions. CoRR abs/1906.02685 (2019) - [i86]Marcello Fiducioso, Sebastian Curi, Benedikt Schumacher, Markus Gwerder, Andreas Krause:
Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning. CoRR abs/1906.12086 (2019) - [i85]Torsten Koller, Felix Berkenkamp, Matteo Turchetta, Joschka Boedecker, Andreas Krause:
Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning. CoRR abs/1906.12189 (2019) - [i84]Erik A. Daxberger, Anastasia Makarova, Matteo Turchetta, Andreas Krause:
Mixed-Variable Bayesian Optimization. CoRR abs/1907.01329 (2019) - [i83]Silvan Melchior, Felix Berkenkamp, Sebastian Curi, Andreas Krause:
Structured Variational Inference in Unstable Gaussian Process State Space Models. CoRR abs/1907.07035 (2019) - [i82]Pier Giuseppe Sessa, Ilija Bogunovic, Maryam Kamgarpour, Andreas Krause:
No-Regret Learning in Unknown Games with Correlated Payoffs. CoRR abs/1909.08540 (2019) - [i81]Mojmír Mutný, Michal Derezinski, Andreas Krause:
Convergence Analysis of the Randomized Newton Method with Determinantal Sampling. CoRR abs/1910.11561 (2019) - [i80]Sebastian Curi, Kfir Y. Levy, Stefanie Jegelka, Andreas Krause:
Adaptive Sampling for Stochastic Risk-Averse Learning. CoRR abs/1910.12511 (2019) - [i79]Matteo Turchetta, Andreas Krause, Sebastian Trimpe:
Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization. CoRR abs/1910.13399 (2019) - [i78]Matteo Turchetta, Felix Berkenkamp, Andreas Krause:
Safe Exploration for Interactive Machine Learning. CoRR abs/1910.13726 (2019) - [i77]Mohammad Yaghini, Hoda Heidari, Andreas Krause:
A Human-in-the-loop Framework to Construct Context-dependent Mathematical Formulations of Fairness. CoRR abs/1911.03020 (2019) - [i76]Ilnura Usmanova, Andreas Krause, Maryam Kamgarpour:
Safe non-smooth black-box optimization with application to policy search. CoRR abs/1912.09466 (2019) - [i75]Ilnura Usmanova, Andreas Krause, Maryam Kamgarpour:
Log Barriers for Safe Non-convex Black-box Optimization. CoRR abs/1912.09478 (2019) - 2018
- [j27]Eric Schulz, Charley M. Wu, Quentin J. M. Huys, Andreas Krause, Maarten Speekenbrink:
Generalization and Search in Risky Environments. Cogn. Sci. 42(8): 2592-2620 (2018) - [j26]Mark Pfeiffer, Samarth Shukla, Matteo Turchetta, Cesar Cadena, Andreas Krause, Roland Siegwart, Juan I. Nieto:
Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Mapless Navigation by Leveraging Prior Demonstrations. IEEE Robotics Autom. Lett. 3(4): 4423-4430 (2018) - [c146]Jens Witkowski, Rupert Freeman, Jennifer Wortman Vaughan, David M. Pennock, Andreas Krause:
Incentive-Compatible Forecasting Competitions. AAAI 2018: 1282-1289 - [c145]Baharan Mirzasoleiman, Stefanie Jegelka, Andreas Krause:
Streaming Non-Monotone Submodular Maximization: Personalized Video Summarization on the Fly. AAAI 2018: 1379-1386 - [c144]Goran Radanovic, Adish Singla, Andreas Krause, Boi Faltings:
Information Gathering With Peers: Submodular Optimization With Peer-Prediction Constraints. AAAI 2018: 1603-1610 - [c143]Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek, Andreas Krause:
Learning User Preferences to Incentivize Exploration in the Sharing Economy. AAAI 2018: 2248-2256 - [c142]Adish Singla, Seyed Hamed Hassani, Andreas Krause:
Learning to Interact With Learning Agents. AAAI 2018: 4083-4090 - [c141]Marko Mitrovic, Moran Feldman, Andreas Krause, Amin Karbasi:
Submodularity on Hypergraphs: From Sets to Sequences. AISTATS 2018: 1177-1184 - [c140]Torsten Koller, Felix Berkenkamp, Matteo Turchetta, Andreas Krause:
Learning-Based Model Predictive Control for Safe Exploration. CDC 2018: 6059-6066 - [c139]Zalan Borsos, Andreas Krause, Kfir Y. Levy:
Online Variance Reduction for Stochastic Optimization. COLT 2018: 324-357 - [c138]Johannes Kirschner, Andreas Krause:
Information Directed Sampling and Bandits with Heteroscedastic Noise. COLT 2018: 358-384 - [c137]Spencer M. Richards, Felix Berkenkamp, Andreas Krause:
The Lyapunov Neural Network: Adaptive Stability Certification for Safe Learning of Dynamical Systems. CoRL 2018: 466-476 - [c136]Paulina Grnarova, Kfir Y. Levy, Aurélien Lucchi, Thomas Hofmann, Andreas Krause:
An Online Learning Approach to Generative Adversarial Networks. ICLR (Poster) 2018 - [c135]Hoda Heidari, Andreas Krause:
Preventing Disparate Treatment in Sequential Decision Making. IJCAI 2018: 2248-2254 - [c134]Sebastian Tschiatschek, Aytunc Sahin, Andreas Krause:
Differentiable Submodular Maximization. IJCAI 2018: 2731-2738 - [c133]Olivier Bachem, Mario Lucic, Andreas Krause:
Scalable k -Means Clustering via Lightweight Coresets. KDD 2018: 1119-1127 - [c132]Hoda Heidari, Claudio Ferrari, Krishna P. Gummadi, Andreas Krause:
Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making. NeurIPS 2018: 1273-1283 - [c131]Josip Djolonga, Stefanie Jegelka, Andreas Krause:
Provable Variational Inference for Constrained Log-Submodular Models. NeurIPS 2018: 2702-2712 - [c130]Mojmir Mutny, Andreas Krause:
Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features. NeurIPS 2018: 9019-9030 - [c129]Alkis Gotovos, S. Hamed Hassani, Andreas Krause, Stefanie Jegelka:
Discrete Sampling using Semigradient-based Product Mixtures. UAI 2018: 229-237 - [c128]Sebastian Tschiatschek, Adish Singla, Manuel Gomez-Rodriguez, Arpit Merchant, Andreas Krause:
Fake News Detection in Social Networks via Crowd Signals. WWW (Companion Volume) 2018: 517-524 - [e1]Jennifer G. Dy, Andreas Krause:
Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholmsmässan, Stockholm, Sweden, July 10-15, 2018. Proceedings of Machine Learning Research 80, PMLR 2018 [contents] - [i74]Zalán Borsos, Andreas Krause, Kfir Y. Levy:
Online Variance Reduction for Stochastic Optimization. CoRR abs/1802.04715 (2018) - [i73]Marko Mitrovic, Moran Feldman, Andreas Krause, Amin Karbasi:
Submodularity on Hypergraphs: From Sets to Sequences. CoRR abs/1802.09110 (2018) - [i72]Sebastian Tschiatschek, Aytunc Sahin, Andreas Krause:
Differentiable Submodular Maximization. CoRR abs/1803.01785 (2018) - [i71]Torsten Koller, Felix Berkenkamp, Matteo Turchetta, Andreas Krause:
Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning. CoRR abs/1803.08287 (2018) - [i70]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. CoRR abs/1804.04378 (2018) - [i69]Mark Pfeiffer, Samarth Shukla, Matteo Turchetta, Cesar Cadena, Andreas Krause, Roland Siegwart, Juan I. Nieto:
Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Map-less Navigation by Leveraging Prior Demonstrations. CoRR abs/1805.07095 (2018) - [i68]An Bian, Joachim M. Buhmann, Andreas Krause:
Optimal DR-Submodular Maximization and Applications to Provable Mean Field Inference. CoRR abs/1805.07482 (2018) - [i67]Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez-Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla:
Teaching Multiple Concepts to Forgetful Learners. CoRR abs/1805.08322 (2018) - [i66]Hoda Heidari, Claudio Ferrari, Krishna P. Gummadi, Andreas Krause:
Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making. CoRR abs/1806.04959 (2018) - [i65]Sebastian Curi, Kfir Y. Levy, Andreas Krause:
Unsupervised Imitation Learning. CoRR abs/1806.07200 (2018) - [i64]Alkis Gotovos, S. Hamed Hassani, Andreas Krause, Stefanie Jegelka:
Discrete Sampling using Semigradient-based Product Mixtures. CoRR abs/1807.01808 (2018) - [i63]Spencer M. Richards, Felix Berkenkamp, Andreas Krause:
The Lyapunov Neural Network: Adaptive Stability Certification for Safe Learning of Dynamic Systems. CoRR abs/1808.00924 (2018) - [i62]Hoda Heidari, Michele Loi, Krishna P. Gummadi, Andreas Krause:
A Moral Framework for Understanding of Fair ML through Economic Models of Equality of Opportunity. CoRR abs/1809.03400 (2018) - [i61]