Papers
General Transportability – Synthesizing Observations and Experiments from Heterogeneous Domains
Sanghack Lee, Juan Correa, Elias Bareinboim
Safe Linear Stochastic Bandits
Kia Khezeli, Eilyan Bitar
Error-Correcting and Verifiable Parallel Inference in Graphical Models
Negin Karimi, Petteri Kaski, Mikko Koivisto
Estimating Causal Effects Using Weighting-Based Estimators
Yonghan Jung, Jin Tian, Elias Bareinboim
The Choice Function Framework for Online Policy Improvement
Murugeswari Issakkimuthu, Alan Fern, Prasad Tadepalli
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.