Andreas Krause 0001

204 publications

23 venues

H Index 63


ETH Zurich, Switzerland
California Institute of Technology, Pasadena, CA, USA
Carnegie Mellon University, Pittsburgh, PA, USA
Technical University of Munich, Germany


Name Venue Year citations
Fast Projection Onto Convex Smooth Constraints. ICML 2021 1
Bias-Robust Bayesian Optimization via Dueling Bandits. ICML 2021 2
Stochastic Linear Bandits Robust to Adversarial Attacks. AISTATS 2021 24
Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases. AAAI 2021 3
Online Submodular Resource Allocation with Applications to Rebalancing Shared Mobility Systems. ICML 2021 0
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees. ICML 2021 33
Safe and Efficient Model-free Adaptive Control via Bayesian Optimization. ICRA 2021 0
Risk-Averse Offline Reinforcement Learning. ICLR 2021 16
Addressing the Long-term Impact of ML Decisions via Policy Regret. IJCAI 2021 0
PopSkipJump: Decision-Based Attack for Probabilistic Classifiers. ICML 2021 0
Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning. ICML 2021 4
Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation. ICCV 2021 0
A Human-in-the-loop Framework to Construct Context-aware Mathematical Notions of Outcome Fairness. AIES 2021 1
No-regret Algorithms for Capturing Events in Poisson Point Processes. ICML 2021 2
Online Active Model Selection for Pre-trained Classifiers. AISTATS 2021 4
Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator. ICLR 2021 7
Logistic Q-Learning. AISTATS 2021 0
Information Directed Reward Learning for Reinforcement Learning. NIPS/NeurIPS 2021 0
Meta-Learning Reliable Priors in the Function Space. NIPS/NeurIPS 2021 0
Hierarchical Skills for Efficient Exploration. NIPS/NeurIPS 2021 0
Learning Graph Models for Retrosynthesis Prediction. NIPS/NeurIPS 2021 0
Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning. NIPS/NeurIPS 2021 0
Risk-averse Heteroscedastic Bayesian Optimization. NIPS/NeurIPS 2021 0
Misspecified Gaussian Process Bandit Optimization. NIPS/NeurIPS 2021 0
DiBS: Differentiable Bayesian Structure Learning. NIPS/NeurIPS 2021 0
Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models. NIPS/NeurIPS 2021 0
Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems. NIPS/NeurIPS 2021 0
Regret Bounds for Gaussian-Process Optimization in Large Domains. NIPS/NeurIPS 2021 0
Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization. ICRA 2020 16
Learning to Play Sequential Games versus Unknown Opponents. NIPS/NeurIPS 2020 7
Experimental Design for Optimization of Orthogonal Projection Pursuit Models. AAAI 2020 0
Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling. AISTATS 2020 12
Mixed-Variable Bayesian Optimization. IJCAI 2020 19
Corruption-Tolerant Gaussian Process Bandit Optimization. AISTATS 2020 32
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models. ICML 2020 2
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning. NIPS/NeurIPS 2020 22
Gradient Estimation with Stochastic Softmax Tricks. NIPS/NeurIPS 2020 25
Contextual Games: Multi-Agent Learning with Side Information. NIPS/NeurIPS 2020 8
Coresets via Bilevel Optimization for Continual Learning and Streaming. NIPS/NeurIPS 2020 45
Information Directed Sampling for Linear Partial Monitoring. COLT 2020 19
Multi-Player Bandits: The Adversarial Case. JMLR 2020 25
A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models. ICRA 2020 3
ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems. AAAI 2020 22
Distributionally Robust Bayesian Optimization. AISTATS 2020 31
Safe Reinforcement Learning via Curriculum Induction. NIPS/NeurIPS 2020 28
Adaptive Sampling for Stochastic Risk-Averse Learning. NIPS/NeurIPS 2020 23
Mixed Strategies for Robust Optimization of Unknown Objectives. AISTATS 2020 6
Safe Convex Learning under Uncertain Constraints. AISTATS 2019 20
Online Variance Reduction with Mixtures. ICML 2019 9
Stochastic Bandits with Context Distributions. NIPS/NeurIPS 2019 6
Efficiently Learning Fourier Sparse Set Functions. NIPS/NeurIPS 2019 4
Consistent Online Optimization: Convex and Submodular. AISTATS 2019 7
Teaching Multiple Concepts to a Forgetful Learner. NIPS/NeurIPS 2019 22
Adaptive Sequence Submodularity. NIPS/NeurIPS 2019 20
Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning. KDD 2019 85
A Domain Agnostic Measure for Monitoring and Evaluating GANs. NIPS/NeurIPS 2019 21
No-Regret Learning in Unknown Games with Correlated Payoffs. NIPS/NeurIPS 2019 15
Learning Generative Models across Incomparable Spaces. ICML 2019 53
Safe Exploration for Interactive Machine Learning. NIPS/NeurIPS 2019 27
Fast Gaussian process based gradient matching for parameter identification in systems of nonlinear ODEs. AISTATS 2019 27
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces. ICML 2019 66
Optimal Continuous DR-Submodular Maximization and Applications to Provable Mean Field Inference. ICML 2019 15
Mobile Robotic Painting of Texture. ICRA 2019 9
No-Regret Bayesian Optimization with Unknown Hyperparameters. JMLR 2019 28
Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning. IJCAI 2019 17
Bounding Inefficiency of Equilibria in Continuous Actions Games using Submodularity and Curvature. AISTATS 2019 3
Projection Free Online Learning over Smooth Sets. AISTATS 2019 13
AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs. ICML 2019 0
Learning to Interact With Learning Agents. AAAI 2018 9
Streaming Non-Monotone Submodular Maximization: Personalized Video Summarization on the Fly. AAAI 2018 58
Submodularity on Hypergraphs: From Sets to Sequences. AISTATS 2018 12
Scalable k -Means Clustering via Lightweight Coresets. KDD 2018 58
Incentive-Compatible Forecasting Competitions. AAAI 2018 14
Differentiable Submodular Maximization. IJCAI 2018 33
Preventing Disparate Treatment in Sequential Decision Making. IJCAI 2018 23
Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making. NIPS/NeurIPS 2018 71
Discrete Sampling using Semigradient-based Product Mixtures. UAI 2018 2
Information Gathering With Peers: Submodular Optimization With Peer-Prediction Constraints. AAAI 2018 3
Provable Variational Inference for Constrained Log-Submodular Models. NIPS/NeurIPS 2018 3
Learning User Preferences to Incentivize Exploration in the Sharing Economy. AAAI 2018 5
Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features. NIPS/NeurIPS 2018 96
Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Mapless Navigation by Leveraging Prior Demonstrations. IEEE Robotics and Automation Letters 2018 80
Information Directed Sampling and Bandits with Heteroscedastic Noise. COLT 2018 51
Online Variance Reduction for Stochastic Optimization. COLT 2018 17
The Lyapunov Neural Network: Adaptive Stability Certification for Safe Learning of Dynamical Systems. CoRL 2018 0
Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten". ICML 2017 57
Differentially Private Submodular Maximization: Data Summarization in Disguise. ICML 2017 19
Training Gaussian Mixture Models at Scale via Coresets. JMLR 2017 0
Interactive Submodular Bandit. NIPS/NeurIPS 2017 16
Safe Model-based Reinforcement Learning with Stability Guarantees. NIPS/NeurIPS 2017 487
Probabilistic Submodular Maximization in Sub-Linear Time. ICML 2017 22
Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains. AISTATS 2017 111
Near-optimal Bayesian Active Learning with Correlated and Noisy Tests. AISTATS 2017 21
Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting. UAI 2017 9
Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms. NIPS/NeurIPS 2017 11
Improving Optimization-Based Approximate Inference by Clamping Variables. UAI 2017 0
Stochastic Submodular Maximization: The Case of Coverage Functions. NIPS/NeurIPS 2017 42
Guarantees for Greedy Maximization of Non-submodular Functions with Applications. ICML 2017 159
Virtual vs. real: Trading off simulations and physical experiments in reinforcement learning with Bayesian optimization. ICRA 2017 79
Distributed and Provably Good Seedings for k-Means in Constant Rounds. ICML 2017 22
Differentiable Learning of Submodular Functions. NIPS/NeurIPS 2017 2
Proper Proxy Scoring Rules. AAAI 2017 15
Uniform Deviation Bounds for k-Means Clustering. ICML 2017 11
Selecting Sequences of Items via Submodular Maximization. AAAI 2017 34
Approximate K-Means++ in Sublinear Time. AAAI 2016 83
Fast and Provably Good Seedings for k-Means. NIPS/NeurIPS 2016 95
Horizontally Scalable Submodular Maximization. ICML 2016 8
Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation. AISTATS 2016 31
Safe controller optimization for quadrotors with Gaussian processes. ICRA 2016 184
e-PAL: An Active Learning Approach to the Multi-Objective Optimization Problem. JMLR 2016 19
Distributed Submodular Maximization. JMLR 2016 0
Learning and Feature Selection under Budget Constraints in Crowdsourcing. HCOMP 2016 11
Learning Sparse Additive Models with Interactions in High Dimensions. AISTATS 2016 12
Cooperative Graphical Models. NIPS/NeurIPS 2016 1
Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation. NIPS/NeurIPS 2016 51
Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures. AISTATS 2016 64
Variational Inference in Mixed Probabilistic Submodular Models. NIPS/NeurIPS 2016 23
Learning Sparse Combinatorial Representations via Two-stage Submodular Maximization. ICML 2016 21
Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization. AAAI 2016 48
Better safe than sorry: Risky function exploitation through safe optimization. Cognitive Science 2016 9
Evaluating Task-Dependent Taxonomies for Navigation. HCOMP 2016 2
Linear-Time Outlier Detection via Sensitivity. IJCAI 2016 12
Safe Exploration in Finite Markov Decision Processes with Gaussian Processes. NIPS/NeurIPS 2016 111
Actively Learning Hemimetrics with Applications to Eliciting User Preferences. ICML 2016 11
Learning to Hire Teams. HCOMP 2015 9
Higher-Order Inference for Multi-class Log-Supermodular Models. ICCV 2015 18
Building Hierarchies of Concepts via Crowdsourcing. IJCAI 2015 32
Lazier Than Lazy Greedy. AAAI 2015 249
Submodular Surrogates for Value of Information. AAAI 2015 38
Scalable Variational Inference in Log-supermodular Models. ICML 2015 31
Non-Monotone Adaptive Submodular Maximization. IJCAI 2015 20
Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning. AISTATS 2015 16
Discovering Valuable items from Massive Data. KDD 2015 30
Efficient visual exploration and coverage with a micro aerial vehicle in unknown environments. ICRA 2015 90
Crowd Access Path Optimization: Diversity Matters. HCOMP 2015 17
Safe Exploration for Optimization with Gaussian Processes. ICML 2015 203
Sequential Information Maximization: When is Greedy Near-optimal? COLT 2015 44
Information Gathering in Networks via Active Exploration. IJCAI 2015 15
Sampling from Probabilistic Submodular Models. NIPS/NeurIPS 2015 29
Distributed Submodular Cover: Succinctly Summarizing Massive Data. NIPS/NeurIPS 2015 43
Incentivizing Users for Balancing Bike Sharing Systems. AAAI 2015 160
Coresets for Nonparametric Estimation - the Case of DP-Means. ICML 2015 67
Robot navigation in dense human crowds: Statistical models and experimental studies of human-robot cooperation. IJRR 2015 0
Active Detection via Adaptive Submodularity. ICML 2014 42
From MAP to Marginals: Variational Inference in Bayesian Submodular Models. NIPS/NeurIPS 2014 75
Explore-exploit in top-N recommender systems via Gaussian processes. RecSys 2014 68
Fully autonomous focused exploration for robotic environmental monitoring. ICRA 2014 5
Efficient Sampling for Learning Sparse Additive Models in High Dimensions. NIPS/NeurIPS 2014 9
Efficient Partial Monitoring with Prior Information. NIPS/NeurIPS 2014 13
Near-Optimally Teaching the Crowd to Classify. ICML 2014 102
Streaming submodular maximization: massive data summarization on the fly. KDD 2014 262
Contextual Procurement in Online Crowdsourcing Markets. HCOMP 2014 0
Near Optimal Bayesian Active Learning for Decision Making. AISTATS 2014 58
Parallelizing exploration-exploitation tradeoffs in Gaussian process bandit optimization. JMLR 2014 0
Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization. ICML 2013 121
Optimizing waypoints for monitoring spatiotemporal phenomena. IJRR 2013 86
Distributed Submodular Maximization: Identifying Representative Elements in Massive Data. NIPS/NeurIPS 2013 226
Truthful incentives in crowdsourcing tasks using regret minimization mechanisms. WWW 2013 264
Robust landmark selection for mobile robot navigation. IROS 2013 18
Robot navigation in dense human crowds: the case for cooperation. ICRA 2013 126
Active Learning for Multi-Objective Optimization. ICML 2013 117
Active Learning for Level Set Estimation. IJCAI 2013 113
Incentives for Privacy Tradeoff in Community Sensing. HCOMP 2013 73
High-Dimensional Gaussian Process Bandits. NIPS/NeurIPS 2013 138
Learning Fourier Sparse Set Functions. AISTATS 2012 37
Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization. ICML 2012 366
Joint Optimization and Variable Selection of High-dimensional Gaussian Processes. ICML 2012 69
Randomized Sensing in Adversarial Environments. IJCAI 2011 22
Dynamic Resource Allocation in Conservation Planning. AAAI 2011 31
Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization. JAIR 2011 502
Scalable Training of Mixture Models via Coresets. NIPS/NeurIPS 2011 123
Crowdclustering. NIPS/NeurIPS 2011 123
Contextual Gaussian Process Bandit Optimization. NIPS/NeurIPS 2011 283
SFO: A Toolbox for Submodular Function Optimization. JMLR 2010 1
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design. ICML 2010 1580
A Utility-Theoretic Approach to Privacy in Online Services. JAIR 2010 1
Informative path planning for an autonomous underwater vehicle. ICRA 2010 116
Near-Optimal Bayesian Active Learning with Noisy Observations. NIPS/NeurIPS 2010 172
Submodular Dictionary Selection for Sparse Representation. ICML 2010 127
Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization. COLT 2010 114
Unfreezing the robot: Navigation in dense, interacting crowds. IROS 2010 392
Discriminative Clustering by Regularized Information Maximization. NIPS/NeurIPS 2010 230
Efficient Minimization of Decomposable Submodular Functions. NIPS/NeurIPS 2010 125
Budgeted Nonparametric Learning from Data Streams. ICML 2010 100
Inferring networks of diffusion and influence. KDD 2010 0
Efficient Informative Sensing using Multiple Robots. JAIR 2009 296
Nonmyopic Adaptive Informative Path Planning for Multiple Robots. IJCAI 2009 110
Online Learning of Assignments. NIPS/NeurIPS 2009 58
Optimal Value of Information in Graphical Models. JAIR 2009 126
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies. JMLR 2008 143
A Utility-Theoretic Approach to Privacy and Personalization. AAAI 2008 78
Efficient Planning of Informative Paths for Multiple Robots. IJCAI 2007 191
Nonmyopic Informative Path Planning in Spatio-Temporal Models. AAAI 2007 84
Nonmyopic active learning of Gaussian processes: an exploration-exploitation approach. ICML 2007 189
Near-optimal Observation Selection using Submodular Functions. AAAI 2007 320
Selecting Observations against Adversarial Objectives. NIPS/NeurIPS 2007 46
Cost-effective outbreak detection in networks. KDD 2007 2144
Data association for topic intensity tracking. ICML 2006 61
Optimal Nonmyopic Value of Information in Graphical Models - Efficient Algorithms and Theoretical Limits. IJCAI 2005 87
Near-optimal sensor placements in Gaussian processes. ICML 2005 493
Near-optimal Nonmyopic Value of Information in Graphical Models. UAI 2005 409
Trading off Prediction Accuracy and Power Consumption for Context-Aware Wearable Computing. ISWC 2005 149
SenSay: A Context-Aware Mobile Phone. ISWC 2003 368
Unsupervised, Dynamic Identification of Physiological and Activity Context in Wearable Computing. ISWC 2003 179
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