Andreas Krause
Identifiers
- name variant Andreas Krause 0.60 · backfill
Papers (94)
- Constrained Flow Optimization via Sequential Fine Tuning for Molecular Design cs.LG · 2026 · author #5
- Sampling-Based Safe Reinforcement Learning cs.LG · 2026 · author #6
- POETS: Uncertainty-Aware LLM Optimization via Compute-Efficient Policy Ensembles cs.LG · 2026 · author #2
- Bounded Ratio Reinforcement Learning cs.LG · 2026 · author #8
- Majority Voting for Code Generation cs.LG · 2026 · author #5
- ActiveUltraFeedback: Efficient Preference Data Generation using Active Learning cs.LG · 2026 · author #7
- A Theoretical Analysis of Test-Driven Code Generation cs.SE · 2026 · author #3
- Reinforcement Learning via Self-Distillation cs.LG · 2026 · author #11
- Test-time Offline Reinforcement Learning on Goal-related Experience cs.LG · 2025 · author #5
- Scalable Ride-Sourcing Vehicle Rebalancing with Service Accessibility Guarantee: A Constrained Mean-Field Reinforcement Learning Approach cs.LG · 2025 · author #5
- Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning cs.LG · 2019 · author #5
- Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning eess.SY · 2019 · author #5
- Learning Generative Models across Incomparable Spaces cs.LG · 2019 · author #3
- Online Variance Reduction with Mixtures cs.LG · 2019 · author #4
- Bounding Inefficiency of Equilibria in Continuous Actions Games using Submodularity and Curvature cs.GT · 2019 · author #3
- AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs cs.LG · 2019 · author #4
- Multi-Player Bandits: The Adversarial Case cs.LG · 2019 · author #3
- Adaptive Sequence Submodularity cs.LG · 2019 · author #4
- Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces cs.LG · 2019 · author #5
- No-Regret Bayesian Optimization with Unknown Hyperparameters stat.ML · 2019 · author #3
- Information-Directed Exploration for Deep Reinforcement Learning cs.LG · 2018 · author #4
- Learning to Compensate Photovoltaic Power Fluctuations from Images of the Sky by Imitating an Optimal Policy cs.LG · 2018 · author #4
- A Moral Framework for Understanding of Fair ML through Economic Models of Equality of Opportunity cs.LG · 2018 · author #4
- The Lyapunov Neural Network: Adaptive Stability Certification for Safe Learning of Dynamical Systems cs.SY · 2018 · author #3
- Discrete Sampling using Semigradient-based Product Mixtures cs.LG · 2018 · author #3
- Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making cs.AI · 2018 · author #4
- Optimal DR-Submodular Maximization and Applications to Provable Mean Field Inference cs.LG · 2018 · author #3
- Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Map-less Navigation by Leveraging Prior Demonstrations cs.RO · 2018 · author #5
- Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEs stat.ML · 2018 · author #5
- Learning-based Model Predictive Control for Safe Exploration cs.SY · 2018 · author #4
- Differentiable Submodular Maximization stat.ML · 2018 · author #3
- Submodularity on Hypergraphs: From Sets to Sequences cs.DS · 2018 · author #3
- Online Variance Reduction for Stochastic Optimization stat.ML · 2018 · author #2
- Information Directed Sampling and Bandits with Heteroscedastic Noise stat.ML · 2018 · author #2
- Fake News Detection in Social Networks via Crowd Signals cs.SI · 2017 · author #5
- Learning User Preferences to Incentivize Exploration in the Sharing Economy cs.LG · 2017 · author #4
- Information Gathering with Peers: Submodular Optimization with Peer-Prediction Constraints cs.GT · 2017 · author #3
- Stochastic Submodular Maximization: The Case of Coverage Functions cs.LG · 2017 · author #4
- Continuous DR-submodular Maximization: Structure and Algorithms cs.LG · 2017 · author #3
- Learning Implicit Generative Models Using Differentiable Graph Tests stat.ML · 2017 · author #2
- Streaming Non-monotone Submodular Maximization: Personalized Video Summarization on the Fly cs.DS · 2017 · author #3
- An Online Learning Approach to Generative Adversarial Networks cs.LG · 2017 · author #5
- Safe Model-based Reinforcement Learning with Stability Guarantees stat.ML · 2017 · author #4
- Simulation of Charge Transport in Organic Semiconductors: A Time-Dependent Multiscale Method Based on Non-Equilibrium Green's Functions cond-mat.mtrl-sci · 2017 · author #3
- Training Gaussian Mixture Models at Scale via Coresets stat.ML · 2017 · author #3
- Practical Coreset Constructions for Machine Learning stat.ML · 2017 · author #3
- Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting cs.AI · 2017 · author #4
- Guarantees for Greedy Maximization of Non-submodular Functions with Applications cs.DM · 2017 · author #3
- Virtual vs. Real: Trading Off Simulations and Physical Experiments in Reinforcement Learning with Bayesian Optimization cs.RO · 2017 · author #5
- Uniform Deviation Bounds for Unbounded Loss Functions like k-Means stat.ML · 2017 · author #4
- Scalable k-Means Clustering via Lightweight Coresets stat.ML · 2017 · author #3
- Learning to Use Learners' Advice cs.LG · 2017 · author #3
- Coordinated Online Learning With Applications to Learning User Preferences cs.LG · 2017 · author #4
- Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation stat.ML · 2016 · author #3
- Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains cs.LG · 2016 · author #4
- Safe Exploration in Finite Markov Decision Processes with Gaussian Processes cs.LG · 2016 · author #3
- Horizontally Scalable Submodular Maximization stat.ML · 2016 · author #4
- Near-optimal Bayesian Active Learning with Correlated and Noisy Tests cs.LG · 2016 · author #3
- Actively Learning Hemimetrics with Applications to Eliciting User Preferences stat.ML · 2016 · author #3
- Algorithms for Learning Sparse Additive Models with Interactions in High Dimensions cs.LG · 2016 · author #4
- Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning stat.ML · 2016 · author #4
- Linear-time Outlier Detection via Sensitivity stat.ML · 2016 · author #3
- Learning Sparse Additive Models with Interactions in High Dimensions cs.LG · 2016 · author #4
- Safe Learning of Regions of Attraction for Uncertain, Nonlinear Systems with Gaussian Processes cs.SY · 2016 · author #4
- Better safe than sorry: Risky function exploitation through safe optimization stat.AP · 2016 · author #5
- Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization cs.AI · 2015 · author #3
- Safe Controller Optimization for Quadrotors with Gaussian Processes cs.RO · 2015 · author #3
- Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures stat.ML · 2015 · author #3
- Learning to Hire Teams cs.HC · 2015 · author #4
- Crowd Access Path Optimization: Diversity Matters cs.LG · 2015 · author #5
- Discovering Valuable Items from Massive Data cs.LG · 2015 · author #5
- Building Hierarchies of Concepts via Crowdsourcing cs.AI · 2015 · author #4
- Information Gathering in Networks via Active Exploration cs.AI · 2015 · author #5
- Scalable Variational Inference in Log-supermodular Models cs.LG · 2015 · author #2
- Distributed Submodular Maximization cs.LG · 2014 · author #4
- Lazier Than Lazy Greedy cs.LG · 2014 · author #5
- Online Submodular Maximization under a Matroid Constraint with Application to Learning Assignments cs.LG · 2014 · author #2
- Near Optimal Bayesian Active Learning for Decision Making cs.LG · 2014 · author #4
- Near-Optimally Teaching the Crowd to Classify cs.LG · 2014 · author #5
- A Utility-Theoretic Approach to Privacy in Online Services cs.AI · 2014 · author #1
- Optimal Value of Information in Graphical Models cs.AI · 2014 · author #1
- Efficient Informative Sensing using Multiple Robots cs.RO · 2014 · author #2
- Incentives for Privacy Tradeoff in Community Sensing cs.GT · 2013 · author #2
- Near-optimal Nonmyopic Value of Information in Graphical Models cs.AI · 2012 · author #1
- Adaptive Submodular Optimization under Matroid Constraints cs.DS · 2011 · author #2
- Efficient Minimization of Decomposable Submodular Functions cs.LG · 2010 · author #2
- Near-Optimal Bayesian Active Learning with Noisy Observations cs.LG · 2010 · author #2
- Inferring Networks of Diffusion and Influence cs.DS · 2010 · author #3
- Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization cs.LG · 2010 · author #2
- Online Distributed Sensor Selection cs.LG · 2010 · author #3
- Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design cs.LG · 2009 · author #2
- Online Learning of Assignments that Maximize Submodular Functions cs.LG · 2009 · author #2
- Evaluating the performance of adapting trading strategies with different memory lengths q-fin.PM · 2009 · author #1
- Microstructure Effects on Daily Return Volatility in Financial Markets cond-mat.stat-mech · 2000 · author #1
Mentions
- 2603.09692 #7 · arxiv_oai · confidence 0.70 Andreas Krause
- 2503.24183 #5 · arxiv_oai · confidence 0.70 Andreas Krause
- 1411.0541 #4 · backfill · confidence 0.70 Andreas Krause
- 1409.7938 #5 · backfill · confidence 0.70 Andreas Krause
- 2605.30610 #5 · arxiv_oai · confidence 0.70 Andreas Krause
- 1407.1082 #2 · backfill · confidence 0.70 Andreas Krause
- 1402.5886 #4 · backfill · confidence 0.70 Andreas Krause
- 1402.2092 #5 · backfill · confidence 0.70 Andreas Krause
- 1401.3859 #1 · backfill · confidence 0.70 Andreas Krause
- 1401.3474 #1 · backfill · confidence 0.70 Andreas Krause
- 1401.3462 #2 · backfill · confidence 0.70 Andreas Krause
- 1308.4013 #2 · backfill · confidence 0.70 Andreas Krause
- 1207.1394 #1 · backfill · confidence 0.70 Andreas Krause
- 2605.19469 #6 · arxiv_oai · confidence 0.70 Andreas Krause
- 1101.4450 #2 · backfill · confidence 0.70 Andreas Krause
- 1010.5511 #2 · backfill · confidence 0.70 Andreas Krause
- 1010.3091 #2 · backfill · confidence 0.70 Andreas Krause
- 1006.0234 #3 · backfill · confidence 0.70 Andreas Krause
- 1003.3967 #2 · backfill · confidence 0.70 Andreas Krause
- 1002.1782 #3 · backfill · confidence 0.70 Andreas Krause
- 0912.3995 #2 · backfill · confidence 0.70 Andreas Krause
- 0908.0772 #2 · backfill · confidence 0.70 Andreas Krause
- 0901.0447 #1 · backfill · confidence 0.70 Andreas Krause
Frequent Coauthors
- Adish Singla 13 shared papers
- Felix Berkenkamp 11 shared papers
- Mario Lucic 9 shared papers
- Amin Karbasi 7 shared papers
- Sebastian Tschiatschek 7 shared papers
- Daniel Golovin 6 shared papers
- Olivier Bachem 6 shared papers
- Angela P. Schoellig 5 shared papers
- Joachim M. Buhmann 5 shared papers
- Kfir Y. Levy 5 shared papers
- Matteo Turchetta 5 shared papers
- Baharan Mirzasoleiman 4 shared papers
- Carlos Guestrin 3 shared papers
- Eric Horvitz 3 shared papers
- Hamed Hassani 3 shared papers
- Ido Hakimi 3 shared papers
- Johannes Kirschner 3 shared papers
- Jonas H\"ubotter 3 shared papers
- Marco Bagatella 3 shared papers
- Stefanie Jegelka 3 shared papers