experiment design

AAAR-1.0: Assessing AI’s Potential to Assist Research ICML 2025 BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments ICLR 2025 Optimal Experiment Design for Causal Effect Identification JMLR 2025 Doing Experiments and Revising Rules with Natural Language and Probabilistic Reasoning NeurIPS 2024 Fast Proxy Experiment Design for Causal Effect Identification NeurIPS 2024 Federated Experiment Design under Distributed Differential Privacy AISTATS 2024 ABLATOR: Robust Horizontal-Scaling of Machine Learning Ablation Experiments AutoML 2023 Active Exploration via Experiment Design in Markov Chains AISTATS 2023 A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models JMLR 2023 Fixed-Budget Best-Arm Identification with Heterogeneous Reward Variances UAI 2023 Reward Learning as Doubly Nonparametric Bandits: Optimal Design and Scaling Laws AISTATS 2023 Tractable Optimality in Episodic Latent MABs NeurIPS 2022 A/B Testing for Recommender Systems in a Two-sided Marketplace NeurIPS 2021 Design of Experiments for Stochastic Contextual Linear Bandits NeurIPS 2021 Learning How To Learn NLP: Developing Introductory Concepts Through Scaffolded Discovery NAACL 2021 Task-Optimal Exploration in Linear Dynamical Systems ICML 2021 LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments ICML 2020 Optimal Testing in the Experiment-rich Regime AISTATS 2019 Variational Information Planning for Sequential Decision Making AISTATS 2019 Best Arm Identification in Linear Bandits with Linear Dimension Dependency ICML 2018 Budgeted Experiment Design for Causal Structure Learning ICML 2018 On Computationally Tractable Selection of Experiments in Measurement-Constrained Regression Models JMLR 2017 Volumetric Spanners: An Efficient Exploration Basis for Learning JMLR 2016 Hard-Margin Active Linear Regression ICML 2014 Randomized Experimental Design for Causal Graph Discovery NeurIPS 2014