Andreas Krause

Latest

• Sequential Experimental Design and Optimization with Structural Assumptions: Additivity and Subspaces
• Transition Constrained Bayesian Optimization via Markov Decision Processes
• Active Exploration via Experiment Design in Markov Chains
• Enhanced Sequence-Activity Mapping and Evolution of Artificial Metalloenzymes by Active Learning
• Likelihood Ratio Confidence Sets for Sequential Decision Making
• Optimistic Games for Combinatorial Bayesian Optimization with Applications to Protein Design
• Submodular Reinforcement Learning
• Experimental Design of Linear Functionals in Reproducing Kernel Hilbert Spaces
• Tuning particle accelerators with safety constraints using Bayesian optimization
• Diversified Sampling for Batched Bayesian Optimization with Determinantal Point Processes
• Sensing Cox Processes via Posterior Sampling and Positive Bases
• Data Summarization via Bilevel Optimization
• Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback
• Learning Controllers for Unstable Linear Quadratic Regulators from a Single Trajectory
• No-regret Algorithms for Capturing Events in Poisson Point Processes
• Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling
• Coresets via Bilevel Optimization for Continual Learning and Streaming
• Experimental Design for Optimization of Orthogonal Projection Pursuit Models
• Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces
• Bayesian Optimization for Fast and Safe Parameter Tuning of SwissFEL
• Efficient High Dimensional Bayesian Optimization with Additivity and Quadrature Fourier Features