Abstract is missing.
- A Cascaded Supervised Learning Approach to Inverse Reinforcement LearningEdouard Klein, Bilal Piot, Matthieu Geist, Olivier Pietquin. 1-16 [doi]
- Learning from Demonstrations: Is It Worth Estimating a Reward Function?Bilal Piot, Matthieu Geist, Olivier Pietquin. 17-32 [doi]
- Recognition of Agents Based on Observation of Their Sequential BehaviorQifeng Qiao, Peter A. Beling. 33-48 [doi]
- Learning Throttle Valve Control Using Policy SearchBastian Bischoff, Duy Nguyen-Tuong, Torsten Koller, Heiner Markert, Alois Knoll. 49-64 [doi]
- Model-Selection for Non-parametric Function Approximation in Continuous Control Problems: A Case Study in a Smart Energy SystemDaniel Urieli, Peter Stone. 65-80 [doi]
- Learning Graph-Based Representations for Continuous Reinforcement Learning DomainsJan Hendrik Metzen. 81-96 [doi]
- Regret Bounds for Reinforcement Learning with Policy AdviceMohammad Gheshlaghi Azar, Alessandro Lazaric, Emma Brunskill. 97-112 [doi]
- Exploiting Multi-step Sample Trajectories for Approximate Value IterationRobert Wright, Steven Loscalzo, Philip Dexter, Lei Yu. 113-128 [doi]
- Expectation Maximization for Average Reward Decentralized POMDPsJoni Pajarinen, Jaakko Peltonen. 129-144 [doi]
- Properly Acting under Partial Observability with Action Feasibility ConstraintsCaroline Ponzoni Carvalho Chanel, Florent Teichteil-Königsbuch. 145-161 [doi]
- Iterative Model Refinement of Recommender MDPs Based on Expert FeedbackOmar Zia Khan, Pascal Poupart, John Mark Agosta. 162-177 [doi]
- Solving Relational MDPs with Exogenous Events and Additive RewardsSaket Joshi, Roni Khardon, Prasad Tadepalli, Aswin Raghavan, Alan Fern. 178-193 [doi]
- Continuous Upper Confidence Trees with Polynomial Exploration - ConsistencyDavid Auger, Adrien Couëtoux, Olivier Teytaud. 194-209 [doi]
- A Lipschitz Exploration-Exploitation Scheme for Bayesian OptimizationAli Jalali, Javad Azimi, Xiaoli Fern, Ruofei Zhang. 210-224 [doi]
- Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure ExplorationEmile Contal, David Buffoni, Alexandre Robicquet, Nicolas Vayatis. 225-240 [doi]
- Greedy Confidence Pursuit: A Pragmatic Approach to Multi-bandit OptimizationPhilip Bachman, Doina Precup. 241-256 [doi]
- A Time and Space Efficient Algorithm for Contextual Linear BanditsJosé Bento, Stratis Ioannidis, S. Muthukrishnan, Jinyun Yan. 257-272 [doi]
- Knowledge Transfer for Multi-labeler Active LearningMeng Fang, Jie Yin, Xingquan Zhu. 273-288 [doi]
- Spectral Learning of Sequence Taggers over Continuous SequencesAdrià Recasens, Ariadna Quattoni. 289-304 [doi]
- Fast Variational Bayesian Linear State-Space ModelJaakko Luttinen. 305-320 [doi]
- Inhomogeneous Parsimonious Markov ModelsRalf Eggeling, André Gohr, Pierre-Yves Bourguignon, Edgar Wingender, Ivo Grosse. 321-336 [doi]
- Explaining Interval Sequences by RandomizationAndreas Henelius, Jussi Korpela, Kai Puolamäki. 337-352 [doi]
- Itemset Based Sequence ClassificationCheng Zhou, Boris Cule, Bart Goethals. 353-368 [doi]
- A Relevance Criterion for Sequential PatternsHenrik Grosskreutz, Bastian Lang, Daniel Trabold. 369-384 [doi]
- A Fast and Simple Method for Mining Subsequences with Surprising Event CountsJefrey Lijffijt. 385-400 [doi]
- Relevant Subsequence Detection with Sparse Dictionary LearningSam Blasiak, Huzefa Rangwala, Kathryn B. Laskey. 401-416 [doi]
- Future Locations Prediction with Uncertain DataDisheng Qiu, Paolo Papotti, Lorenzo Blanco. 417-432 [doi]
- Modeling Short-Term Energy Load with Continuous Conditional Random FieldsHongyu Guo. 433-448 [doi]
- Fault Tolerant Regression for Sensor DataIndre Zliobaite, Jaakko Hollmén. 449-464 [doi]
- Pitfalls in Benchmarking Data Stream Classification and How to Avoid ThemAlbert Bifet, Jesse Read, Indre Zliobaite, Bernhard Pfahringer, Geoff Holmes. 465-479 [doi]
- Adaptive Model Rules from Data StreamsEzilda Almeida, Carlos Abreu Ferreira, João Gama. 480-492 [doi]
- Fast and Exact Mining of Probabilistic Data StreamsReza Akbarinia, Florent Masseglia. 493-508 [doi]
- Detecting Bicliques in GF[q]Jan Ramon, Pauli Miettinen, Jilles Vreeken. 509-524 [doi]
- As Strong as the Weakest Link: Mining Diverse Cliques in Weighted GraphsPetko Bogdanov, Ben Baumer, Prithwish Basu, Amotz Bar-Noy, Ambuj K. Singh. 525-540 [doi]
- How Robust Is the Core of a Network?Abhijin Adiga, Anil Kumar S. Vullikanti. 541-556 [doi]
- Community Distribution Outlier Detection in Heterogeneous Information NetworksManish Gupta, Jing Gao, Jiawei Han. 557-573 [doi]
- Protein Function Prediction Using Dependence MaximizationGuo-Xian Yu, Carlotta Domeniconi, Huzefa Rangwala, Guoji Zhang. 574-589 [doi]
- Improving Relational Classification Using Link Prediction TechniquesCristina Pérez-Solà, Jordi Herrera-Joancomartí. 590-605 [doi]
- A Fast Approximation of the Weisfeiler-Lehman Graph Kernel for RDF DataGerben Klaas Dirk de Vries. 606-621 [doi]
- Efficient Frequent Connected Induced Subgraph Mining in Graphs of Bounded Tree-WidthTamás Horváth, Keisuke Otaki, Jan Ramon. 622-637 [doi]
- Continuous Similarity Computation over Streaming GraphsElena Valari, Apostolos N. Papadopoulos. 638-653 [doi]
- Trend Mining in Dynamic Attributed GraphsElise Desmier, Marc Plantevit, Céline Robardet, Jean-François Boulicaut. 654-669 [doi]
- Sparse Relational Topic Models for Document NetworksAonan Zhang, Jun Zhu, Bo Zhang. 670-685 [doi]