Discovery Science

Table of Contents

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   Book Overview
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   Chapter 1 Declarative Modeling for Machine Learning and Data Mining
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   Chapter 2 Recent Developments in Pattern Mining
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   Chapter 3 Exploring Sequential Data
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   Chapter 4 Large Scale Spectral Clustering Using Resistance Distance and Spielman-Teng Solvers
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   Chapter 5 Prediction of Quantiles by Statistical Learning and Application to GDP Forecasting
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   Chapter 6 Policy Search in a Space of Simple Closed-form Formulas: Towards Interpretability of Reinforcement Learning
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   Chapter 7 Towards Finding Relational Redescriptions
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   Chapter 8 Descriptive Modeling of Systemic Banking Crises
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    Chapter 9 A Trim Distance between Positions in Nucleotide Sequences
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    Chapter 10 Data Squashing for HSV Subimages by an Autonomous Mobile Robot
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    Chapter 11 Cohesive Co-evolution Patterns in Dynamic Attributed Graphs
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    Chapter 12 Efficient Redundancy Reduced Subgroup Discovery via Quadratic Programming
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    Chapter 13 HCAC: Semi-supervised Hierarchical Clustering Using Confidence-Based Active Learning
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    Chapter 14 LF-CARS: A Loose Fragment-Based Consensus Clustering Algorithm with a Robust Similarity
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    Chapter 15 Fast Approximation Algorithm for the 1-Median Problem
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    Chapter 16 Online Co-regularized Algorithms
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    Chapter 17 Fast Progressive Training of Mixture Models for Model Selection
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    Chapter 18 Including Spatial Relations and Scales within Sequential Pattern Extraction
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    Chapter 19 Predicting Ramp Events with a Stream-Based HMM Framework
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    Chapter 20 Burst Detection in a Sequence of Tweets Based on Information Diffusion Model
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    Chapter 21 Error-Correcting Output Codes as a Transformation from Multi-Class to Multi-Label Prediction
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    Chapter 22 An Assessment on Loan Performance from Combined Quantitative and Qualitative Data in XML
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    Chapter 23 Structural Change Pattern Mining Based on Constrained Maximal k -Plex Search
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    Chapter 24 Enhancing Patent Expertise through Automatic Matching with Scientific Papers
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    Chapter 25 Soft Threshold Constraints for Pattern Mining