experimental design

Sequential Experimental Design for Transductive Linear Bandits NeurIPS 2019 Size of Interventional Markov Equivalence Classes in random DAG models AISTATS 2019 Submodular Maximization beyond Non-negativity: Guarantees, Fast Algorithms, and Applications ICML 2019 A Robust Approach to Sequential Information Theoretic Planning ICML 2018 Experimental Design for Cost-Aware Learning of Causal Graphs NeurIPS 2018 Experimental Design under the Bradley-Terry Model IJCAI 2018 New Balanced Active Learning Model and Optimization Algorithm IJCAI 2018 The Hitchhiker’s Guide to Testing Statistical Significance in Natural Language Processing ACL 2018 Approximate Supermodularity Bounds for Experimental Design NeurIPS 2017 Experimental Design for Learning Causal Graphs with Latent Variables NeurIPS 2017 Multi-fidelity Bayesian Optimisation with Continuous Approximations ICML 2017 Near-optimal Bayesian Active Learning with Correlated and Noisy Tests AISTATS 2017 Near-Optimal Design of Experiments via Regret Minimization ICML 2017 On Computationally Tractable Selection of Experiments in Measurement-Constrained Regression Models JMLR 2017 Polynomial time algorithms for dual volume sampling NeurIPS 2017 Experimental Design on a Budget for Sparse Linear Models and Applications ICML 2016 A Framework for Testing Identifiability of Bayesian Models of Perception NeurIPS 2014 Bayesian Optimization with Inequality Constraints ICML 2014 Near Optimal Bayesian Active Learning for Decision Making AISTATS 2014 Optimal Data Collection For Informative Rankings Expose Well-Connected Graphs JMLR 2014 Randomized Experimental Design for Causal Graph Discovery NeurIPS 2014 Bayesian Inference and Online Experimental Design for Mapping Neural Microcircuits NeurIPS 2013 Active learning of neural response functions with Gaussian processes NeurIPS 2011 Budgeted Optimization with Concurrent Stochastic-Duration Experiments NeurIPS 2011 Parameter Screening and Optimisation for ILP using Designed Experiments JMLR 2011