Artificial Intelligence

Learning End-to-end Multimodal Sensor Policies for Autonomous Navigation CoRL 2017 Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis ICML 2017 Learning from Data Heterogeneity: Algorithms and Applications IJCAI 2017 Learning from Demonstrations with High-Level Side Information IJCAI 2017 Learning from uncertain curves: The 2-Wasserstein metric for Gaussian processes NeurIPS 2017 Learning Heuristic Search via Imitation CoRL 2017 Learning how to Active Learn: A Deep Reinforcement Learning Approach EMNLP 2017 Learning Human Utility from Video Demonstrations for Deductive Planning in Robotics CoRL 2017 Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity NeurIPS 2017 Learning Important Features Through Propagating Activation Differences ICML 2017 Learning in POMDPs with Monte Carlo Tree Search ICML 2017 Learning Instrumental Variables with Structural and Non-Gaussianity Assumptions JMLR 2017 Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition NeurIPS 2017 Learning Language Representations for Typology Prediction EMNLP 2017 Learning Lexico-Functional Patterns for First-Person Affect ACL 2017 Learning Local Dependence In Ordered Data JMLR 2017 Learning Lyapunov (Potential) Functions from Counterexamples and Demonstrations RSS 2017 Learning Models for Shared Control of Human-Machine Systems with Unknown Dynamics RSS 2017 Learning Multiple Tasks with Multilinear Relationship Networks NeurIPS 2017 Learning Nash Equilibrium for General-Sum Markov Games from Batch Data AISTATS 2017 Learning Neural Representations of Human Cognition across Many fMRI Studies NeurIPS 2017 Learning Non-Discriminatory Predictors COLT 2017 Learning Nonparametric Forest Graphical Models with Prior Information AISTATS 2017 Learning Optimal Interventions AISTATS 2017 Learning Partially Contracting Dynamical Systems from Demonstrations CoRL 2017