Publications (79)
Training Gaussian Mixture Models at Scale via Coresets
Mario Lucic, Matthew Faulkner, Andreas Krause +1
Incentives for Privacy Tradeoff in Community Sensing
Adish Singla, Andreas Krause
Near Optimal Bayesian Active Learning for Decision Making
Shervin Javdani, Yuxin Chen, Amin Karbasi +3
Evaluating the performance of adapting trading strategies with different memory lengths
Andreas Krause
Tradeoffs for Space, Time, Data and Risk in Unsupervised Learning
Mario Lucic, Mesrob I. Ohannessian, Amin Karbasi +1
Submodularity on Hypergraphs: From Sets to Sequences
Marko Mitrovic, Moran Feldman, Andreas Krause +1
Inferring Networks of Diffusion and Influence
Manuel Gomez-Rodriguez, Jure Leskovec, Andreas Krause
Crowd Access Path Optimization: Diversity Matters
Besmira Nushi, Adish Singla, Anja Gruenheid +3
Safe Controller Optimization for Quadrotors with Gaussian Processes
Felix Berkenkamp, Angela P. Schoellig, Andreas Krause
Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization
Thomas Desautels, Andreas Krause, Joel Burdick
Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization
Adish Singla, Sebastian Tschiatschek, Andreas Krause
Joint Optimization and Variable Selection of High-dimensional Gaussian Processes
Bo Chen, Rui Castro, Andreas Krause
Strong Coresets for Hard and Soft Bregman Clustering with Applications to Exponential Family Mixtures
Mario Lucic, Olivier Bachem, Andreas Krause
No-Regret Bayesian Optimization with Unknown Hyperparameters
Felix Berkenkamp, Angela P. Schoellig, Andreas Krause
Fake News Detection in Social Networks via Crowd Signals
Sebastian Tschiatschek, Adish Singla, Manuel Gomez Rodriguez +2
Learning Implicit Generative Models Using Differentiable Graph Tests
Josip Djolonga, Andreas Krause
Distributed Submodular Maximization
Baharan Mirzasoleiman, Amin Karbasi, Rik Sarkar +1
Continuous DR-submodular Maximization: Structure and Algorithms
An Bian, Kfir Y. Levy, Andreas Krause +1
Information Gathering with Peers: Submodular Optimization with Peer-Prediction Constraints
Goran Radanovic, Adish Singla, Andreas Krause +1
Discovering Valuable Items from Massive Data
Hastagiri P. Vanchinathan, Andreas Marfurt, Charles-Antoine Robelin +2
Optimal DR-Submodular Maximization and Applications to Provable Mean Field Inference
An Bian, Joachim M. Buhmann, Andreas Krause
Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Map-less Navigation by Leveraging Prior Demonstrations
Mark Pfeiffer, Samarth Shukla, Matteo Turchetta +4
Adaptive Submodular Optimization under Matroid Constraints
Daniel Golovin, Andreas Krause
Online Submodular Maximization under a Matroid Constraint with Application to Learning Assignments
Daniel Golovin, Andreas Krause, Matthew Streeter
Adaptive Sequence Submodularity
Marko Mitrovic, Ehsan Kazemi, Moran Feldman +2
Learning to Use Learners' Advice
Adish Singla, Hamed Hassani, Andreas Krause
Streaming Non-monotone Submodular Maximization: Personalized Video Summarization on the Fly
Baharan Mirzasoleiman, Stefanie Jegelka, Andreas Krause
Simulation of Charge Transport in Organic Semiconductors: A Time-Dependent Multiscale Method Based on Non-Equilibrium Green's Functions
Susanne Leitherer, Christof M. Jäger, Andreas Krause +3
Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation
Ilija Bogunovic, Jonathan Scarlett, Andreas Krause +1
Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning
Marcello Fiducioso, Sebastian Curi, Benedikt Schumacher +2
Information Gathering in Networks via Active Exploration
Adish Singla, Eric Horvitz, Pushmeet Kohli +2
Microstructure Effects on Daily Return Volatility in Financial Markets
Andreas Krause
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces
Johannes Kirschner, MojmÃr Mutný, Nicole Hiller +2
Learning Generative Models across Incomparable Spaces
Charlotte Bunne, David Alvarez-Melis, Andreas Krause +1
An Online Learning Approach to Generative Adversarial Networks
Paulina Grnarova, Kfir Y. Levy, Aurelien Lucchi +2
Scalable Variational Inference in Log-supermodular Models
Josip Djolonga, Andreas Krause
Online Variance Reduction for Stochastic Optimization
Zalán Borsos, Andreas Krause, Kfir Y. Levy
Efficient Online Learning for Optimizing Value of Information: Theory and Application to Interactive Troubleshooting
Yuxin Chen, Jean-Michel Renders, Morteza Haghir Chehreghani +1
Multi-Player Bandits: The Adversarial Case
Pragnya Alatur, Kfir Y. Levy, Andreas Krause
Discrete Sampling using Semigradient-based Product Mixtures
Alkis Gotovos, Hamed Hassani, Andreas Krause +1
Lazier Than Lazy Greedy
Baharan Mirzasoleiman, Ashwinkumar Badanidiyuru, Amin Karbasi +2
Near-optimal Nonmyopic Value of Information in Graphical Models
Andreas Krause, Carlos E. Guestrin
Adaptive Submodularity: Theory and Applications in Active Learning and Stochastic Optimization
Daniel Golovin, Andreas Krause
Scalable k-Means Clustering via Lightweight Coresets
Olivier Bachem, Mario Lucic, Andreas Krause
Safe Exploration in Finite Markov Decision Processes with Gaussian Processes
Matteo Turchetta, Felix Berkenkamp, Andreas Krause
Near-optimal Bayesian Active Learning with Correlated and Noisy Tests
Yuxin Chen, S. Hamed Hassani, Andreas Krause
Optimal Value of Information in Graphical Models
Andreas Krause, Carlos Guestrin
Stochastic Submodular Maximization: The Case of Coverage Functions
Mohammad Reza Karimi, Mario Lucic, Hamed Hassani +1
AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs
Gabriele Abbati, Philippe Wenk, Michael A Osborne +3
Information Directed Sampling and Bandits with Heteroscedastic Noise
Johannes Kirschner, Andreas Krause
Fairness Behind a Veil of Ignorance: A Welfare Analysis for Automated Decision Making
Hoda Heidari, Claudio Ferrari, Krishna P. Gummadi +1
Learning Sparse Additive Models with Interactions in High Dimensions
Hemant Tyagi, Anastasios Kyrillidis, Bernd Gärtner +1
Practical Coreset Constructions for Machine Learning
Olivier Bachem, Mario Lucic, Andreas Krause
A Moral Framework for Understanding of Fair ML through Economic Models of Equality of Opportunity
Hoda Heidari, Michele Loi, Krishna P. Gummadi +1
Guarantees for Greedy Maximization of Non-submodular Functions with Applications
Andrew An Bian, Joachim M. Buhmann, Andreas Krause +1
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design
Niranjan Srinivas, Andreas Krause, Sham M. Kakade +1
Actively Learning Hemimetrics with Applications to Eliciting User Preferences
Adish Singla, Sebastian Tschiatschek, Andreas Krause
Efficient Informative Sensing using Multiple Robots
Amarjeet Singh, Andreas Krause, Carlos Guestrin +1
Uniform Deviation Bounds for Unbounded Loss Functions like k-Means
Olivier Bachem, Mario Lucic, S. Hamed Hassani +1
Near-Optimally Teaching the Crowd to Classify
Adish Singla, Ilija Bogunovic, Gábor Bartók +2
Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEs
Philippe Wenk, Alkis Gotovos, Stefan Bauer +3
Efficient Minimization of Decomposable Submodular Functions
Peter Stobbe, Andreas Krause
Online Learning of Assignments that Maximize Submodular Functions
Daniel Golovin, Andreas Krause, Matthew Streeter
Learning User Preferences to Incentivize Exploration in the Sharing Economy
Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek +1
Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains
Andrew An Bian, Baharan Mirzasoleiman, Joachim M. Buhmann +1
Building Hierarchies of Concepts via Crowdsourcing
Yuyin Sun, Adish Singla, Dieter Fox +1
Online Variance Reduction with Mixtures
Zalán Borsos, Sebastian Curi, Kfir Y. Levy +1
Bounding Inefficiency of Equilibria in Continuous Actions Games using Submodularity and Curvature
Pier Giuseppe Sessa, Maryam Kamgarpour, Andreas Krause
Learning to Hire Teams
Adish Singla, Eric Horvitz, Pushmeet Kohli +1
Better safe than sorry: Risky function exploitation through safe optimization
Eric Schulz, Quentin J. M. Huys, Dominik R. Bach +2
Coordinated Online Learning With Applications to Learning User Preferences
Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek +1
A Utility-Theoretic Approach to Privacy in Online Services
Andreas Krause, Eric Horvitz
Near-Optimal Bayesian Active Learning with Noisy Observations
Daniel Golovin, Andreas Krause, Debajyoti Ray
Online Distributed Sensor Selection
Daniel Golovin, Matthew Faulkner, Andreas Krause
Differentiable Submodular Maximization
Sebastian Tschiatschek, Aytunc Sahin, Andreas Krause
Horizontally Scalable Submodular Maximization
Mario Lucic, Olivier Bachem, Morteza Zadimoghaddam +1
Information-Directed Exploration for Deep Reinforcement Learning
Nikolay Nikolov, Johannes Kirschner, Felix Berkenkamp +1
Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning
Torsten Koller, Felix Berkenkamp, Matteo Turchetta +2
Linear-time Outlier Detection via Sensitivity
Mario Lucic, Olivier Bachem, Andreas Krause