Papers
Importance Sampling for Fair Policy Selection
Shayan Doroudi, Philip S. Thomas, Emma Brunskill
Combinatorial Cost Sharing
Shahar Dobzinski, Shahar Ovadia
The Finite Model Theory of Bayesian Networks: Descriptive Complexity
Fabio Gagliardi Cozman, Denis Deratani Mauá
Dynamic Dependency Awareness for QBF
Joshua Blinkhorn, Olaf Beyersdorff
Learning with Sparse and Biased Feedback for Personal Search
Michael Bendersky, Xuanhui Wang, Marc Najork et al.
Improving Information Extraction from Images with Learned Semantic Models
Stephan Baier, Yunpu Ma, Volker Tresp
Reduced Cost Fixing for Maximum Satisfiability
Fahiem Bacchus, Antti Hyttinen, Matti Järvisalo et al.
A Unifying View of Geometry, Semantics, and Data Association in SLAM
Nikolay Atanasov, Sean L. Bowman, Kostas Daniilidis et al.
TensorCast: Forecasting Time-Evolving Networks with Contextual Information
Miguel Araújo, Pedro Ribeiro, Christos Faloutsos
Weighted Bipolar Argumentation Graphs: Axioms and Semantics
Leila Amgoud, Jonathan Ben-Naim
Finite Controllability of Conjunctive Query Answering with Existential Rules: Two Steps Forward
Giovanni Amendola, Nicola Leone, Marco Manna
The Facets of Artificial Intelligence: A Framework to Track the Evolution of AI
Fernando Martínez-Plumed, Bao Sheng Loe, Peter Flach et al.
Evolving AI from Research to Real Life – Some Challenges and Suggestions
Sandya Mannarswamy, Shourya Roy
Quantifying Algorithmic Improvements over Time
Lars Kotthoff, Alexandre Fréchette, Tomasz Michalak et al.
Artificial Intelligence Conferences Closeness
Sébastien Konieczny, Emmanuel Lonca
Towards Consumer-Empowering Artificial Intelligence
Giuseppe Contissa, Francesca Lagioia, Marco Lippi et al.
On a Scientific Discipline (Once) Named AI
Wolfgang Bibel
A Savage-style Utility Theory for Belief Functions
Chunlai Zhou, Biao Qin, Xiaoyong Du
Mixed Causal Structure Discovery with Application to Prescriptive Pricing
Wei Wenjuan, Feng Lu, Liu Chunchen
A Scalable Scheme for Counting Linear Extensions
Topi Talvitie, Kustaa Kangas, Teppo Niinimäki et al.
Scalable Probabilistic Causal Structure Discovery
Dhanya Sridhar, Jay Pujara, Lise Getoor
A Symbolic Approach to Explaining Bayesian Network Classifiers
Andy Shih, Arthur Choi, Adnan Darwiche
Algorithms for the Nearest Assignment Problem
Sara Rouhani, Tahrima Rahman, Vibhav Gogate
Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty
Vu-Linh Nguyen, Sébastien Destercke, Marie-Hélène Masson et al.
Estimation with Incomplete Data: The Linear Case
Karthika Mohan, Felix Thoemmes, Judea Pearl