Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part I

Front Matter....Pages -
A Cascaded Supervised Learning Approach to Inverse Reinforcement Learning....Pages 1-16
Learning from Demonstrations: Is It Worth Estimating a Reward Function?....Pages 17-32
Recognition of Agents Based on Observation of Their Sequential Behavior....Pages 33-48
Learning Throttle Valve Control Using Policy Search....Pages 49-64
Model-Selection for Non-parametric Function Approximation in Continuous Control Problems: A Case Study in a Smart Energy System....Pages 65-80
Learning Graph-Based Representations for Continuous Reinforcement Learning Domains....Pages 81-96
Regret Bounds for Reinforcement Learning with Policy Advice....Pages 97-112
Exploiting Multi-step Sample Trajectories for Approximate Value Iteration....Pages 113-128
Expectation Maximization for Average Reward Decentralized POMDPs....Pages 129-144
Properly Acting under Partial Observability with Action Feasibility Constraints....Pages 145-161
Iterative Model Refinement of Recommender MDPs Based on Expert Feedback....Pages 162-177
Solving Relational MDPs with Exogenous Events and Additive Rewards....Pages 178-193
Continuous Upper Confidence Trees with Polynomial Exploration – Consistency....Pages 194-209
A Lipschitz Exploration-Exploitation Scheme for Bayesian Optimization....Pages 210-224
Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration....Pages 225-240
Greedy Confidence Pursuit: A Pragmatic Approach to Multi-bandit Optimization....Pages 241-256
A Time and Space Efficient Algorithm for Contextual Linear Bandits....Pages 257-272
Knowledge Transfer for Multi-labeler Active Learning....Pages 273-288
Spectral Learning of Sequence Taggers over Continuous Sequences....Pages 289-304
Fast Variational Bayesian Linear State-Space Model....Pages 305-320
Inhomogeneous Parsimonious Markov Models....Pages 321-336
Explaining Interval Sequences by Randomization....Pages 337-352
Itemset Based Sequence Classification....Pages 353-368
A Relevance Criterion for Sequential Patterns....Pages 369-384
A Fast and Simple Method for Mining Subsequences with Surprising Event Counts....Pages 385-400
Relevant Subsequence Detection with Sparse Dictionary Learning....Pages 401-416
Future Locations Prediction with Uncertain Data....Pages 417-432
Modeling Short-Term Energy Load with Continuous Conditional Random Fields....Pages 433-448
Fault Tolerant Regression for Sensor Data....Pages 449-464
Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them....Pages 465-479
Adaptive Model Rules from Data Streams....Pages 480-492
Fast and Exact Mining of Probabilistic Data Streams....Pages 493-508
Detecting Bicliques in GF[q]....Pages 509-524
As Strong as the Weakest Link:Mining Diverse Cliques in Weighted Graphs....Pages 525-540
How Robust Is the Core of a Network?....Pages 541-556
Community Distribution Outlier Detection in Heterogeneous Information Networks....Pages 557-573
Protein Function Prediction Using Dependence Maximization....Pages 574-589
Improving Relational Classification Using Link Prediction Techniques....Pages 590-605
A Fast Approximation of the Weisfeiler-Lehman Graph Kernel for RDF Data....Pages 606-621
Efficient Frequent Connected Induced Subgraph Mining in Graphs of Bounded Tree-Width....Pages 622-637
Continuous Similarity Computation over Streaming Graphs....Pages 638-653
Trend Mining in Dynamic Attributed Graphs....Pages 654-669
Sparse Relational Topic Models for Document Networks....Pages 670-685
Back Matter....Pages -