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Machine Learning and Knowledge Discovery in Databases

Overview of attention for book
Cover of 'Machine Learning and Knowledge Discovery in Databases'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 A Cascaded Supervised Learning Approach to Inverse Reinforcement Learning
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    Chapter 2 Learning from Demonstrations: Is It Worth Estimating a Reward Function?
  4. Altmetric Badge
    Chapter 3 Recognition of Agents Based on Observation of Their Sequential Behavior
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    Chapter 4 Learning Throttle Valve Control Using Policy Search
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    Chapter 5 Model-Selection for Non-parametric Function Approximation in Continuous Control Problems: A Case Study in a Smart Energy System
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    Chapter 6 Learning Graph-Based Representations for Continuous Reinforcement Learning Domains
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    Chapter 7 Regret Bounds for Reinforcement Learning with Policy Advice
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    Chapter 8 Exploiting Multi-step Sample Trajectories for Approximate Value Iteration
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    Chapter 9 Expectation Maximization for Average Reward Decentralized POMDPs
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    Chapter 10 Properly Acting under Partial Observability with Action Feasibility Constraints
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    Chapter 11 Iterative Model Refinement of Recommender MDPs Based on Expert Feedback
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    Chapter 12 Solving Relational MDPs with Exogenous Events and Additive Rewards
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    Chapter 13 Continuous Upper Confidence Trees with Polynomial Exploration – Consistency
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    Chapter 14 A Lipschitz Exploration-Exploitation Scheme for Bayesian Optimization
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    Chapter 15 Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration
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    Chapter 16 Greedy Confidence Pursuit: A Pragmatic Approach to Multi-bandit Optimization
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    Chapter 17 A Time and Space Efficient Algorithm for Contextual Linear Bandits
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    Chapter 18 Knowledge Transfer for Multi-labeler Active Learning
  20. Altmetric Badge
    Chapter 19 Spectral Learning of Sequence Taggers over Continuous Sequences
  21. Altmetric Badge
    Chapter 20 Fast Variational Bayesian Linear State-Space Model
  22. Altmetric Badge
    Chapter 21 Machine Learning and Knowledge Discovery in Databases
  23. Altmetric Badge
    Chapter 22 Explaining Interval Sequences by Randomization
  24. Altmetric Badge
    Chapter 23 Itemset Based Sequence Classification
  25. Altmetric Badge
    Chapter 24 A Relevance Criterion for Sequential Patterns
  26. Altmetric Badge
    Chapter 25 A Fast and Simple Method for Mining Subsequences with Surprising Event Counts
  27. Altmetric Badge
    Chapter 26 Relevant Subsequence Detection with Sparse Dictionary Learning
  28. Altmetric Badge
    Chapter 27 Future Locations Prediction with Uncertain Data
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    Chapter 28 Modeling Short-Term Energy Load with Continuous Conditional Random Fields
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    Chapter 29 Fault Tolerant Regression for Sensor Data
  31. Altmetric Badge
    Chapter 30 Pitfalls in Benchmarking Data Stream Classification and How to Avoid Them
  32. Altmetric Badge
    Chapter 31 Adaptive Model Rules from Data Streams
  33. Altmetric Badge
    Chapter 32 Fast and Exact Mining of Probabilistic Data Streams
  34. Altmetric Badge
    Chapter 33 Detecting Bicliques in GF[q]
  35. Altmetric Badge
    Chapter 34 As Strong as the Weakest Link:Mining Diverse Cliques in Weighted Graphs
  36. Altmetric Badge
    Chapter 35 How Robust Is the Core of a Network?
  37. Altmetric Badge
    Chapter 36 Community Distribution Outlier Detection in Heterogeneous Information Networks
  38. Altmetric Badge
    Chapter 37 Protein Function Prediction Using Dependence Maximization
  39. Altmetric Badge
    Chapter 38 Improving Relational Classification Using Link Prediction Techniques
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    Chapter 39 A Fast Approximation of the Weisfeiler-Lehman Graph Kernel for RDF Data
  41. Altmetric Badge
    Chapter 40 Efficient Frequent Connected Induced Subgraph Mining in Graphs of Bounded Tree-Width
  42. Altmetric Badge
    Chapter 41 Continuous Similarity Computation over Streaming Graphs
  43. Altmetric Badge
    Chapter 42 Trend Mining in Dynamic Attributed Graphs
  44. Altmetric Badge
    Chapter 43 Sparse Relational Topic Models for Document Networks
Attention for Chapter 31: Adaptive Model Rules from Data Streams
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

wikipedia
1 Wikipedia page

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
24 Mendeley
Summary Wikipedia Dimensions citations
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
Adaptive Model Rules from Data Streams
Chapter number 31
Book title
Machine Learning and Knowledge Discovery in Databases
Published in
Lecture notes in computer science, September 2013
DOI 10.1007/978-3-642-40988-2_31
Book ISBNs
978-3-64-240987-5, 978-3-64-240988-2
Authors

Ezilda Almeida, Carlos Ferreira, João Gama

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 33%
Student > Master 4 17%
Other 2 8%
Professor 1 4%
Lecturer 1 4%
Other 2 8%
Unknown 6 25%
Readers by discipline Count As %
Computer Science 12 50%
Engineering 2 8%
Business, Management and Accounting 1 4%
Economics, Econometrics and Finance 1 4%
Mathematics 1 4%
Other 0 0%
Unknown 7 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 26 February 2014.
All research outputs
#7,454,951
of 22,792,160 outputs
Outputs from Lecture notes in computer science
#2,487
of 8,127 outputs
Outputs of similar age
#68,000
of 202,867 outputs
Outputs of similar age from Lecture notes in computer science
#42
of 154 outputs
Altmetric has tracked 22,792,160 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,127 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 55% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 202,867 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 154 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.

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