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Machine Learning and Knowledge Discovery in Databases [2013]

1
A Cascaded Supervised Learning Approach to Inverse Reinforcement Learning
1
AR-Boost: Reducing Overfitting by a Robust Data-Driven Regularization Strategy
1
Incremental Local Evolutionary Outlier Detection for Dynamic Social Networks
16
How Long Will She Call Me? Distribution, Social Theory and Duration Prediction
17
Learning from Demonstrations: Is It Worth Estimating a Reward Function?
17
Parallel Boosting with Momentum
32
Discovering Nested Communities
33
Inner Ensembles: Using Ensemble Methods Inside the Learning Algorithm
33
Recognition of Agents Based on Observation of Their Sequential Behavior
48
CSI: Community-Level Social Influence Analysis
49
Learning Discriminative Sufficient Statistics Score Space for Classification
49
Learning Throttle Valve Control Using Policy Search
64
Supervised Learning of Syntactic Contexts for Uncovering Definitions and Extracting Hypernym Relations in Text Databases
65
Model-Selection for Non-parametric Function Approximation in Continuous Control Problems: A Case Study in a Smart Energy System
65
The Stochastic Gradient Descent for the Primal L1-SVM Optimization Revisited
80
Error Prediction with Partial Feedback
81
Bundle CDN: A Highly Parallelized Approach for Large-Scale ℓ<Subscript>1</Subscript>-Regularized Logistic Regression
81
Learning Graph-Based Representations for Continuous Reinforcement Learning Domains
95
Boot-Strapping Language Identifiers for Short Colloquial Postings
96
MORD: Multi-class Classifier for Ordinal Regression
97
Regret Bounds for Reinforcement Learning with Policy Advice
112
A Pairwise Label Ranking Method with Imprecise Scores and Partial Predictions
112
Identifiability of Model Properties in Over-Parameterized Model Classes
113
Exploiting Multi-step Sample Trajectories for Approximate Value Iteration
128
Exploratory Learning
128
Learning Socially Optimal Information Systems from Egoistic Users
129
Expectation Maximization for Average Reward Decentralized POMDPs
144
Semi-supervised Gaussian Process Ordinal Regression
145
Properly Acting under Partial Observability with Action Feasibility Constraints
145
Socially Enabled Preference Learning from Implicit Feedback Data
160
Influence of Graph Construction on Semi-supervised Learning
161
Cross-Domain Recommendation via Cluster-Level Latent Factor Model
162
Iterative Model Refinement of Recommender MDPs Based on Expert Feedback
176
Tractable Semi-supervised Learning of Complex Structured Prediction Models
177
Minimal Shrinkage for Noisy Data Recovery Using Schatten-<Emphasis Type="Italic">p</Emphasis> Norm Objective
178
Solving Relational MDPs with Exogenous Events and Additive Rewards
192
PSSDL: Probabilistic Semi-supervised Dictionary Learning
194
Continuous Upper Confidence Trees with Polynomial Exploration – Consistency
194
Noisy Matrix Completion Using Alternating Minimization
208
Embedding with Autoencoder Regularization
210
A Lipschitz Exploration-Exploitation Scheme for Bayesian Optimization
210
A Nearly Unbiased Matrix Completion Approach
224
Reduced-Rank Local Distance Metric Learning
225
Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration
226
A Counterexample for the Validity of Using Nuclear Norm as a Convex Surrogate of Rank
240
Learning Exemplar-Represented Manifolds in Latent Space for Classification
241
Greedy Confidence Pursuit: A Pragmatic Approach to Multi-bandit Optimization
242
Efficient Rank-one Residue Approximation Method for Graph Regularized Non-negative Matrix Factorization
256
Locally Linear Landmarks for Large-Scale Manifold Learning
256
Maximum Entropy Models for Iteratively Identifying Subjectively Interesting Structure in Real-Valued Data
257
A Time and Space Efficient Algorithm for Contextual Linear Bandits
272
An Analysis of Tensor Models for Learning on Structured Data
272
Discovering Skylines of Subgroup Sets
273
Knowledge Transfer for Multi-labeler Active Learning
288
Difference-Based Estimates for Generalization-Aware Subgroup Discovery
288
Learning Modewise Independent Components from Tensor Data Using Multilinear Mixing Model
289
Spectral Learning of Sequence Taggers over Continuous Sequences
304
Local Outlier Detection with Interpretation
304
Taxonomic Prediction with Tree-Structured Covariances
305
Fast Variational Bayesian Linear State-Space Model
320
Position Preserving Multi-Output Prediction
321
Anomaly Detection in Vertically Partitioned Data by Distributed Core Vector Machines
321
Inhomogeneous Parsimonious Markov Models
336
Structured Output Learning with Candidate Labels for Local Parts
337
Explaining Interval Sequences by Randomization
337
Mining Outlier Participants: Insights Using Directional Distributions in Latent Models
353
Anonymizing Data with Relational and Transaction Attributes
353
Itemset Based Sequence Classification
353
Shared Structure Learning for Multiple Tasks with Multiple Views
369
A Relevance Criterion for Sequential Patterns
369
Using Both Latent and Supervised Shared Topics for Multitask Learning
370
Privacy-Preserving Mobility Monitoring Using Sketches of Stationary Sensor Readings
385
A Fast and Simple Method for Mining Subsequences with Surprising Event Counts
385
Probabilistic Clustering for Hierarchical Multi-Label Classification of Protein Functions
387
Evasion Attacks against Machine Learning at Test Time
401
Multi-core Structural SVM Training
401
Relevant Subsequence Detection with Sparse Dictionary Learning
403
The Top-<Emphasis Type="Italic">k</Emphasis> Frequent Closed Itemset Mining Using Top-<Emphasis Type="Italic">k</Emphasis> SAT Problem
417
Future Locations Prediction with Uncertain Data
417
Multi-label Classification with Output Kernels
419
A Declarative Framework for Constrained Clustering
433
Boosting for Unsupervised Domain Adaptation
433
Modeling Short-Term Energy Load with Continuous Conditional Random Fields
435
SNNAP: Solver-Based Nearest Neighbor for Algorithm Portfolios
449
Automatically Mapped Transfer between Reinforcement Learning Tasks via Three-Way Restricted Boltzmann Machines
449
Fault Tolerant Regression for Sensor Data
451
Area under the Precision-Recall Curve: Point Estimates and Confidence Intervals
465
A Layered Dirichlet Process for Hierarchical Segmentation of Sequential Grouped Data
465
Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them
467
Incremental Sensor Placement Optimization on Water Network
480
Adaptive Model Rules from Data Streams
483
A Bayesian Classifier for Learning from Tensorial Data
483
Detecting Marionette Microblog Users for Improved Information Credibility
493
Fast and Exact Mining of Probabilistic Data Streams
499
Prediction with Model-Based Neutrality
499
Will My Question Be Answered? Predicting “Question Answerability” in Community Question-Answering Sites
509
Detecting Bicliques in GF[q]
515
Decision-Theoretic Sparsification for Gaussian Process Preference Learning
515
Learning to Detect Patterns of Crime
525
As Strong as the Weakest Link:Mining Diverse Cliques in Weighted Graphs
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