NIPS Proceedingsβ

Andreas Krause

20 Papers

  • Cooperative Graphical Models (2016)
  • Fast and Provably Good Seedings for k-Means (2016)
  • Safe Exploration in Finite Markov Decision Processes with Gaussian Processes (2016)
  • Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation (2016)
  • Variational Inference in Mixed Probabilistic Submodular Models (2016)
  • Distributed Submodular Cover: Succinctly Summarizing Massive Data (2015)
  • Sampling from Probabilistic Submodular Models (2015)
  • Efficient Partial Monitoring with Prior Information (2014)
  • Efficient Sampling for Learning Sparse Additive Models in High Dimensions (2014)
  • From MAP to Marginals: Variational Inference in Bayesian Submodular Models (2014)
  • Distributed Submodular Maximization: Identifying Representative Elements in Massive Data (2013)
  • High-Dimensional Gaussian Process Bandits (2013)
  • Contextual Gaussian Process Bandit Optimization (2011)
  • Crowdclustering (2011)
  • Scalable Training of Mixture Models via Coresets (2011)
  • Discriminative Clustering by Regularized Information Maximization (2010)
  • Efficient Minimization of Decomposable Submodular Functions (2010)
  • Near-Optimal Bayesian Active Learning with Noisy Observations (2010)
  • Online Learning of Assignments (2009)
  • Selecting Observations against Adversarial Objectives (2007)