Papers
Probabilistic Reasoning Across the Causal Hierarchy
Duligur Ibeling, Thomas Icard
Introducing Probabilistic Bézier Curves for N-Step Sequence Prediction
Ronny Hug, Wolfgang Hübner, Michael Arens
Causal Discovery from Multiple Data Sets with Non-Identical Variable Sets
Biwei Huang, Kun Zhang, Mingming Gong et al.
A MaxSAT-Based Framework for Group Testing
Lorenzo Ciampiconi, Bishwamittra Ghosh, Jonathan Scarlett et al.
Low-Variance Black-Box Gradient Estimates for the Plackett-Luce Distribution
Artyom Gadetsky, Kirill Struminsky, Christopher Robinson et al.
Causal Transfer for Imitation Learning and Decision Making under Sensor-Shift
Jalal Etesami, Philipp Geiger
Deception through Half-Truths
Andrew Estornell, Sanmay Das, Yevgeniy Vorobeychik
Reliable and Efficient Anytime Skeleton Learning
Rui Ding, Yanzhi Liu, Jingjing Tian et al.
A Calculus for Stochastic Interventions:Causal Effect Identification and Surrogate Experiments
Juan Correa, Elias Bareinboim
Regret Minimisation in Multi-Armed Bandits Using Bounded Arm Memory
Arghya Roy Chaudhuri, Shivaram Kalyanakrishnan
Learning Fair Naive Bayes Classifiers by Discovering and Eliminating Discrimination Patterns
YooJung Choi, Golnoosh Farnadi, Behrouz Babaki et al.
Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes
Maxime Bouton, Jana Tumova, Mykel J. Kochenderfer
Exchangeable Generative Models with Flow Scans
Christopher Bender, Kevin O'Connor, Yang Li et al.
Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization
Syrine Belakaria, Aryan Deshwal, Nitthilan Kannappan Jayakodi et al.
Multi-Fidelity Multi-Objective Bayesian Optimization: An Output Space Entropy Search Approach
Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa
Deep Bayesian Nonparametric Learning of Rules and Plans from Demonstrations with a Learned Automaton Prior
Brandon Araki, Kiran Vodrahalli, Thomas Leech et al.
Computing Superior Counter-Examples for Conformant Planning
Xiaodi Zhang, Alban Grastien, Enrico Scala
Refining HTN Methods via Task Insertion with Preferences
Zhanhao Xiao, Hai Wan, Hankui Hankz Zhuo et al.
NeoNav: Improving the Generalization of Visual Navigation via Generating Next Expected Observations
Qiaoyun Wu, Dinesh Manocha, Jun Wang et al.
Planning with Abstract Learned Models While Learning Transferable Subtasks
John Winder, Stephanie Milani, Matthew Landen et al.
Neural Architecture Search Using Deep Neural Networks and Monte Carlo Tree Search
Linnan Wang, Yiyang Zhao, Yuu Jinnai et al.
Temporal Planning with Intermediate Conditions and Effects
Alessandro Valentini, Andrea Micheli, Alessandro Cimatti
Symbolic Top-k Planning
David Speck, Robert Mattmüller, Bernhard Nebel
Active Goal Recognition
Maayan Shvo, Sheila A. McIlraith