Andreas Krause 0001

253 publications

25 venues

H Index 62


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
Gradient-Based Trajectory Optimization With Learned Dynamics. ICRA 2023 0
Hallucinated adversarial control for conservative offline policy evaluation. UAI 2023 0
A scalable Walsh-Hadamard regularizer to overcome the low-degree spectral bias of neural networks. UAI 2023 0
Lifelong bandit optimization: no prior and no regret. UAI 2023 0
Aligned Diffusion Schrödinger Bridges. UAI 2023 0
Tuning Legged Locomotion Controllers via Safe Bayesian Optimization. CoRL 2023 0
The Schrödinger Bridge between Gaussian Measures has a Closed Form. AISTATS 2023 0
Active Exploration via Experiment Design in Markov Chains. AISTATS 2023 0
BaCaDI: Bayesian Causal Discovery with Unknown Interventions. AISTATS 2023 0
Isotropic Gaussian Processes on Finite Spaces of Graphs. AISTATS 2023 0
Efficient Exploration in Continuous-time Model-based Reinforcement Learning. NIPS/NeurIPS 2023 0
A Dynamical System View of Langevin-Based Non-Convex Sampling. NIPS/NeurIPS 2023 0
Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning. NIPS/NeurIPS 2023 0
Stochastic Approximation Algorithms for Systems of Interacting Particles. NIPS/NeurIPS 2023 0
Optimistic Active Exploration of Dynamical Systems. NIPS/NeurIPS 2023 0
Implicit Manifold Gaussian Process Regression. NIPS/NeurIPS 2023 0
Learning To Dive In Branch And Bound. NIPS/NeurIPS 2023 0
Riemannian stochastic optimization methods avoid strict saddle points. NIPS/NeurIPS 2023 0
Anytime Model Selection in Linear Bandits. NIPS/NeurIPS 2023 0
Likelihood Ratio Confidence Sets for Sequential Decision Making. NIPS/NeurIPS 2023 0
Contextual Stochastic Bilevel Optimization. NIPS/NeurIPS 2023 0
Replicable Bandits. ICLR 2023 0
Model-based Causal Bayesian Optimization. ICLR 2023 0
Near-optimal Policy Identification in Active Reinforcement Learning. ICLR 2023 0
MARS: Meta-learning as Score Matching in the Function Space. ICLR 2023 0
Safe Risk-Averse Bayesian Optimization for Controller Tuning. IEEE Robotics and Automation Letters 2023 0
Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics. MLJ 2023 0
GoSafeOpt: Scalable safe exploration for global optimization of dynamical systems. Artificial Intelligence 2023 0
Adaptive Gaussian Process Change Point Detection. ICML 2022 0
Learning Long-Term Crop Management Strategies with CyclesGym. NIPS/NeurIPS 2022 0
Constrained Policy Optimization via Bayesian World Models. ICLR 2022 12
Meta-Learning Hypothesis Spaces for Sequential Decision-making. ICML 2022 3
Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation. ICML 2022 0
The Dynamics of Riemannian Robbins-Monro Algorithms. COLT 2022 1
Learning to Cut by Looking Ahead: Cutting Plane Selection via Imitation Learning. ICML 2022 8
Interactively Learning Preference Constraints in Linear Bandits. ICML 2022 0
Meta-Learning Priors for Safe Bayesian Optimization. CoRL 2022 0
Neural Contextual Bandits without Regret. AISTATS 2022 0
Sensing Cox Processes via Posterior Sampling and Positive Bases. AISTATS 2022 0
Proximal Optimal Transport Modeling of Population Dynamics. AISTATS 2022 0
Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processes. AISTATS 2022 0
Amortized Inference for Causal Structure Learning. NIPS/NeurIPS 2022 0
Near-Optimal Multi-Agent Learning for Safe Coverage Control. NIPS/NeurIPS 2022 0
Active Bayesian Causal Inference. NIPS/NeurIPS 2022 0
Movement Penalized Bayesian Optimization with Application to Wind Energy Systems. NIPS/NeurIPS 2022 0
Experimental Design for Linear Functionals in Reproducing Kernel Hilbert Spaces. NIPS/NeurIPS 2022 0
Supervised Training of Conditional Monge Maps. NIPS/NeurIPS 2022 0
Active Exploration for Inverse Reinforcement Learning. NIPS/NeurIPS 2022 0
Graph Neural Network Bandits. NIPS/NeurIPS 2022 0
A Robust Phased Elimination Algorithm for Corruption-Tolerant Gaussian Process Bandits. NIPS/NeurIPS 2022 0
Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning. ICLR 2022 0
Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking. ICLR 2022 0
Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning. NIPS/NeurIPS 2021 8
DiBS: Differentiable Bayesian Structure Learning. NIPS/NeurIPS 2021 30
PopSkipJump: Decision-Based Attack for Probabilistic Classifiers. ICML 2021 1
Cherry-Picking Gradients: Learning Low-Rank Embeddings of Visual Data via Differentiable Cross-Approximation. ICCV 2021 5
Bias-Robust Bayesian Optimization via Dueling Bandits. ICML 2021 6
Addressing the Long-term Impact of ML Decisions via Policy Regret. IJCAI 2021 4
Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning. ICML 2021 8
Risk-averse Heteroscedastic Bayesian Optimization. NIPS/NeurIPS 2021 8
Online Submodular Resource Allocation with Applications to Rebalancing Shared Mobility Systems. ICML 2021 0
Hierarchical Skills for Efficient Exploration. NIPS/NeurIPS 2021 15
Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models. NIPS/NeurIPS 2021 1
Regret Bounds for Gaussian-Process Optimization in Large Domains. NIPS/NeurIPS 2021 3
Fast Projection Onto Convex Smooth Constraints. ICML 2021 2
Meta-Learning Reliable Priors in the Function Space. NIPS/NeurIPS 2021 15
Information Directed Reward Learning for Reinforcement Learning. NIPS/NeurIPS 2021 5
No-regret Algorithms for Capturing Events in Poisson Point Processes. ICML 2021 3
Robust Generalization despite Distribution Shift via Minimum Discriminating Information. NIPS/NeurIPS 2021 4
Learning Stable Deep Dynamics Models for Partially Observed or Delayed Dynamical Systems. NIPS/NeurIPS 2021 6
Misspecified Gaussian Process Bandit Optimization. NIPS/NeurIPS 2021 13
Safe and Efficient Model-free Adaptive Control via Bayesian Optimization. ICRA 2021 10
Risk-Averse Offline Reinforcement Learning. ICLR 2021 38
Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases. AAAI 2021 0
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees. ICML 2021 0
Logistic Q-Learning. AISTATS 2021 0
Online Active Model Selection for Pre-trained Classifiers. AISTATS 2021 0
Stochastic Linear Bandits Robust to Adversarial Attacks. AISTATS 2021 0
A Human-in-the-loop Framework to Construct Context-aware Mathematical Notions of Outcome Fairness. AIES 2021 0
Multi-Scale Representation Learning on Proteins. NIPS/NeurIPS 2021 0
Learning Graph Models for Retrosynthesis Prediction. NIPS/NeurIPS 2021 0
Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator. ICLR 2021 0
Mixed-Variable Bayesian Optimization. IJCAI 2020 29
Gradient Estimation with Stochastic Softmax Tricks. NIPS/NeurIPS 2020 54
Safe Reinforcement Learning via Curriculum Induction. NIPS/NeurIPS 2020 45
Corruption-Tolerant Gaussian Process Bandit Optimization. AISTATS 2020 41
A Real-Robot Dataset for Assessing Transferability of Learned Dynamics Models. ICRA 2020 5
Experimental Design for Optimization of Orthogonal Projection Pursuit Models. AAAI 2020 2
Learning to Play Sequential Games versus Unknown Opponents. NIPS/NeurIPS 2020 13
Coresets via Bilevel Optimization for Continual Learning and Streaming. NIPS/NeurIPS 2020 93
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning. NIPS/NeurIPS 2020 38
Distributionally Robust Bayesian Optimization. AISTATS 2020 51
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models. ICML 2020 4
Mixed Strategies for Robust Optimization of Unknown Objectives. AISTATS 2020 8
Information Directed Sampling for Linear Partial Monitoring. COLT 2020 27
ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems. AAAI 2020 0
Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization. ICRA 2020 0
Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling. AISTATS 2020 0
Adaptive Sampling for Stochastic Risk-Averse Learning. NIPS/NeurIPS 2020 0
Contextual Games: Multi-Agent Learning with Side Information. NIPS/NeurIPS 2020 0
Multi-Player Bandits: The Adversarial Case. JMLR 2020 0
Adaptive Sequence Submodularity. NIPS/NeurIPS 2019 23
Safe Convex Learning under Uncertain Constraints. AISTATS 2019 32
Mobile Robotic Painting of Texture. ICRA 2019 11
Projection Free Online Learning over Smooth Sets. AISTATS 2019 20
Bounding Inefficiency of Equilibria in Continuous Actions Games using Submodularity and Curvature. AISTATS 2019 8
No-Regret Bayesian Optimization with Unknown Hyperparameters. JMLR 2019 37
Stochastic Bandits with Context Distributions. NIPS/NeurIPS 2019 12
Safe Exploration for Interactive Machine Learning. NIPS/NeurIPS 2019 45
Learning Generative Models across Incomparable Spaces. ICML 2019 76
Optimal Continuous DR-Submodular Maximization and Applications to Provable Mean Field Inference. ICML 2019 19
Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning. KDD 2019 111
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces. ICML 2019 94
Efficiently Learning Fourier Sparse Set Functions. NIPS/NeurIPS 2019 9
No-Regret Learning in Unknown Games with Correlated Payoffs. NIPS/NeurIPS 2019 22
Consistent Online Optimization: Convex and Submodular. AISTATS 2019 10
Online Variance Reduction with Mixtures. ICML 2019 11
Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning. IJCAI 2019 33
AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs. ICML 2019 0
Fast Gaussian process based gradient matching for parameter identification in systems of nonlinear ODEs. AISTATS 2019 0
Teaching Multiple Concepts to a Forgetful Learner. NIPS/NeurIPS 2019 0
A Domain Agnostic Measure for Monitoring and Evaluating GANs. NIPS/NeurIPS 2019 0
Incentive-Compatible Forecasting Competitions. AAAI 2018 17
Provable Variational Inference for Constrained Log-Submodular Models. NIPS/NeurIPS 2018 3
Learning to Interact With Learning Agents. AAAI 2018 9
Submodularity on Hypergraphs: From Sets to Sequences. AISTATS 2018 17
Preventing Disparate Treatment in Sequential Decision Making. IJCAI 2018 34
Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features. NIPS/NeurIPS 2018 126
Information Directed Sampling and Bandits with Heteroscedastic Noise. COLT 2018 76
Online Variance Reduction for Stochastic Optimization. COLT 2018 19
Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Mapless Navigation by Leveraging Prior Demonstrations. IEEE Robotics and Automation Letters 2018 112
Discrete Sampling using Semigradient-based Product Mixtures. UAI 2018 2
Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making. NIPS/NeurIPS 2018 100
Differentiable Submodular Maximization. IJCAI 2018 40
Streaming Non-Monotone Submodular Maximization: Personalized Video Summarization on the Fly. AAAI 2018 0
Information Gathering With Peers: Submodular Optimization With Peer-Prediction Constraints. AAAI 2018 0
Learning User Preferences to Incentivize Exploration in the Sharing Economy. AAAI 2018 0
The Lyapunov Neural Network: Adaptive Stability Certification for Safe Learning of Dynamical Systems. CoRL 2018 0
Scalable k -Means Clustering via Lightweight Coresets. KDD 2018 0
Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting. UAI 2017 11
Uniform Deviation Bounds for k-Means Clustering. ICML 2017 13
Deletion-Robust Submodular Maximization: Data Summarization with "the Right to be Forgotten". ICML 2017 68
Probabilistic Submodular Maximization in Sub-Linear Time. ICML 2017 28
Proper Proxy Scoring Rules. AAAI 2017 17
Training Gaussian Mixture Models at Scale via Coresets. JMLR 2017 0
Distributed and Provably Good Seedings for k-Means in Constant Rounds. ICML 2017 27
Selecting Sequences of Items via Submodular Maximization. AAAI 2017 43
Differentiable Learning of Submodular Functions. NIPS/NeurIPS 2017 2
Stochastic Submodular Maximization: The Case of Coverage Functions. NIPS/NeurIPS 2017 45
Differentially Private Submodular Maximization: Data Summarization in Disguise. ICML 2017 26
Safe Model-based Reinforcement Learning with Stability Guarantees. NIPS/NeurIPS 2017 609
Interactive Submodular Bandit. NIPS/NeurIPS 2017 20
Virtual vs. real: Trading off simulations and physical experiments in reinforcement learning with Bayesian optimization. ICRA 2017 91
Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms. NIPS/NeurIPS 2017 15
Improving Optimization-Based Approximate Inference by Clamping Variables. UAI 2017 0
Guarantees for Greedy Maximization of Non-submodular Functions with Applications. ICML 2017 198
Near-optimal Bayesian Active Learning with Correlated and Noisy Tests. AISTATS 2017 0
Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains. AISTATS 2017 0
Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation. AISTATS 2016 34
Horizontally Scalable Submodular Maximization. ICML 2016 8
Better safe than sorry: Risky function exploitation through safe optimization. Cognitive Science 2016 8
Variational Inference in Mixed Probabilistic Submodular Models. NIPS/NeurIPS 2016 23
Actively Learning Hemimetrics with Applications to Eliciting User Preferences. ICML 2016 11
Safe Exploration in Finite Markov Decision Processes with Gaussian Processes. NIPS/NeurIPS 2016 141
Linear-Time Outlier Detection via Sensitivity. IJCAI 2016 12
Learning Sparse Additive Models with Interactions in High Dimensions. AISTATS 2016 15
Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation. NIPS/NeurIPS 2016 64
Learning Sparse Combinatorial Representations via Two-stage Submodular Maximization. ICML 2016 22
Fast and Provably Good Seedings for k-Means. NIPS/NeurIPS 2016 115
e-PAL: An Active Learning Approach to the Multi-Objective Optimization Problem. JMLR 2016 22
Approximate K-Means++ in Sublinear Time. AAAI 2016 104
Cooperative Graphical Models. NIPS/NeurIPS 2016 1
Distributed Submodular Maximization. JMLR 2016 0
Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization. AAAI 2016 0
Safe controller optimization for quadrotors with Gaussian processes. ICRA 2016 0
Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures. AISTATS 2016 0
Coresets for Nonparametric Estimation - the Case of DP-Means. ICML 2015 81
Efficient visual exploration and coverage with a micro aerial vehicle in unknown environments. ICRA 2015 109
Discovering Valuable items from Massive Data. KDD 2015 32
Distributed Submodular Cover: Succinctly Summarizing Massive Data. NIPS/NeurIPS 2015 47
Higher-Order Inference for Multi-class Log-Supermodular Models. ICCV 2015 19
Information Gathering in Networks via Active Exploration. IJCAI 2015 16
Sampling from Probabilistic Submodular Models. NIPS/NeurIPS 2015 31
Building Hierarchies of Concepts via Crowdsourcing. IJCAI 2015 38
Non-Monotone Adaptive Submodular Maximization. IJCAI 2015 28
Submodular Surrogates for Value of Information. AAAI 2015 44
Safe Exploration for Optimization with Gaussian Processes. ICML 2015 250
Scalable Variational Inference in Log-supermodular Models. ICML 2015 32
Sequential Information Maximization: When is Greedy Near-optimal? COLT 2015 51
Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning. AISTATS 2015 15
Incentivizing Users for Balancing Bike Sharing Systems. AAAI 2015 182
Lazier Than Lazy Greedy. AAAI 2015 0
Robot navigation in dense human crowds: Statistical models and experimental studies of human-robot cooperation. IJRR 2015 0
From MAP to Marginals: Variational Inference in Bayesian Submodular Models. NIPS/NeurIPS 2014 76
Efficient Partial Monitoring with Prior Information. NIPS/NeurIPS 2014 15
Explore-exploit in top-N recommender systems via Gaussian processes. RecSys 2014 78
Active Detection via Adaptive Submodularity. ICML 2014 44
Fully autonomous focused exploration for robotic environmental monitoring. ICRA 2014 58
Near-Optimally Teaching the Crowd to Classify. ICML 2014 109
Streaming submodular maximization: massive data summarization on the fly. KDD 2014 305
Near Optimal Bayesian Active Learning for Decision Making. AISTATS 2014 56
Efficient Sampling for Learning Sparse Additive Models in High Dimensions. NIPS/NeurIPS 2014 11
Parallelizing exploration-exploitation tradeoffs in Gaussian process bandit optimization. JMLR 2014 0
Near-optimal Batch Mode Active Learning and Adaptive Submodular Optimization. ICML 2013 132
Distributed Submodular Maximization: Identifying Representative Elements in Massive Data. NIPS/NeurIPS 2013 253
Truthful incentives in crowdsourcing tasks using regret minimization mechanisms. WWW 2013 278
Active Learning for Multi-Objective Optimization. ICML 2013 134
Active Learning for Level Set Estimation. IJCAI 2013 125
High-Dimensional Gaussian Process Bandits. NIPS/NeurIPS 2013 158
Optimizing waypoints for monitoring spatiotemporal phenomena. IJRR 2013 94
Robot navigation in dense human crowds: the case for cooperation. ICRA 2013 140
Robust landmark selection for mobile robot navigation. IROS 2013 18
Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization. ICML 2012 401
Learning Fourier Sparse Set Functions. AISTATS 2012 48
Joint Optimization and Variable Selection of High-dimensional Gaussian Processes. ICML 2012 79
Crowdclustering. NIPS/NeurIPS 2011 127
Contextual Gaussian Process Bandit Optimization. NIPS/NeurIPS 2011 324
Scalable Training of Mixture Models via Coresets. NIPS/NeurIPS 2011 134
Dynamic Resource Allocation in Conservation Planning. AAAI 2011 35
Randomized Sensing in Adversarial Environments. IJCAI 2011 23
Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization. JAIR 2011 0
Efficient Minimization of Decomposable Submodular Functions. NIPS/NeurIPS 2010 130
Near-Optimal Bayesian Active Learning with Noisy Observations. NIPS/NeurIPS 2010 181
A Utility-Theoretic Approach to Privacy in Online Services. JAIR 2010 2
Inferring networks of diffusion and influence. KDD 2010 58
Unfreezing the robot: Navigation in dense, interacting crowds. IROS 2010 456
SFO: A Toolbox for Submodular Function Optimization. JMLR 2010 104
Submodular Dictionary Selection for Sparse Representation. ICML 2010 129
Discriminative Clustering by Regularized Information Maximization. NIPS/NeurIPS 2010 283
Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization. COLT 2010 124
Informative path planning for an autonomous underwater vehicle. ICRA 2010 128
Budgeted Nonparametric Learning from Data Streams. ICML 2010 112
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design. ICML 2010 0
Optimal Value of Information in Graphical Models. JAIR 2009 129
Online Learning of Assignments. NIPS/NeurIPS 2009 62
Nonmyopic Adaptive Informative Path Planning for Multiple Robots. IJCAI 2009 123
Efficient Informative Sensing using Multiple Robots. JAIR 2009 0
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies. JMLR 2008 197
A Utility-Theoretic Approach to Privacy and Personalization. AAAI 2008 82
Selecting Observations against Adversarial Objectives. NIPS/NeurIPS 2007 46
Nonmyopic Informative Path Planning in Spatio-Temporal Models. AAAI 2007 88
Robust, low-cost, non-intrusive sensing and recognition of seated postures. UIST 2007 124
Near-optimal Observation Selection using Submodular Functions. AAAI 2007 333
Cost-effective outbreak detection in networks. KDD 2007 2317
Nonmyopic active learning of Gaussian processes: an exploration-exploitation approach. ICML 2007 205
Efficient Planning of Informative Paths for Multiple Robots. IJCAI 2007 0
Data association for topic intensity tracking. ICML 2006 64
Near-optimal Nonmyopic Value of Information in Graphical Models. UAI 2005 443
Trading off Prediction Accuracy and Power Consumption for Context-Aware Wearable Computing. ISWC 2005 156
Optimal Nonmyopic Value of Information in Graphical Models - Efficient Algorithms and Theoretical Limits. IJCAI 2005 88
Near-optimal sensor placements in Gaussian processes. ICML 2005 513
Unsupervised, Dynamic Identification of Physiological and Activity Context in Wearable Computing. ISWC 2003 190
SenSay: A Context-Aware Mobile Phone. ISWC 2003 372
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