Machine Learning, Optimization, and Big Data

Machine Learning, Optimization, and Big Data Front Cover
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2018-01-26
600 pages

Book Description

Machine Learning, Optimization, and : Third International Conference, MOD 2017, Volterra, Italy, September 14–17, 2017, Revised Selected Papers (Lecture Notes in )

This book constitutes the post-conference proceedings of the Third International Workshop on Machine Learning, Optimization, and Big Data, MOD 2017, held in Volterra, Italy, in September 2017.

The 50 full papers presented were carefully reviewed and selected from 126 submissions. The papers cover topics in the field of machine learning, artificial intelligence, computational optimization and data science presenting a substantial array of ideas, technologies, algorithms, methods and applications.

Table of Contents

Chapter 1. Recipes for Translating Big Data Machine Reading to Executable Cellular Signaling Models
Chapter 2. Improving Support Vector Machines Performance Using Local Search
Chapter 3. Projective Approximation Based Quasi-Newton Methods
Chapter 4. Intra-feature Random Forest Clustering
Chapter 5. Dolphin Pod Optimization
Chapter 6. Contraction Clustering (RASTER)
Chapter 7. Deep Statistical Comparison Applied on Quality Indicators to Compare Multi-objective Stochastic Optimization Algorithms
Chapter 8. On the Explicit Use of Enzyme-Substrate Reactions in Metabolic Pathway Analysis
Chapter 9. A Comparative Study on Term Weighting Schemes for Text Classification
Chapter 10. Dual Convergence Estimates for a Family of Greedy Algorithms in Banach Spaces
Chapter 11. Nonlinear Methods for Design-Space Dimensionality Reduction in Shape Optimization
Chapter 12. A Differential Evolution Algorithm to Develop Strategies for the Iterated Prisoner's Dilemma
Chapter 13. Automatic Creation of a Large and Polished Training Set for Sentiment Analysis on Twitter
Chapter 14. Forecasting Natural Gas Flows in Large Networks
Chapter 15. A Differential Evolution Algorithm to Semivectorial Bilevel Problems
Chapter 16. Evolving Training Sets for Improved Transfer Learning in Brain Computer Interfaces
Chapter 17. Hybrid Global/Local Derivative-Free Multi-objective Optimization via Deterministic Particle Swarm with Local Linesearch
Chapter 18. Artificial Bee Colony Optimization to Reallocate Personnel to Tasks Improving Workplace Safety
Chapter 19. Multi-objective Genetic Algorithm for Interior Lighting Design
Chapter 20. An Elementary Approach to the Problem of Column Selection in a Rectangular Matrix
Chapter 21. A Simple and Effective Lagrangian-Based Combinatorial Algorithm for S3VMs
Chapter 22. A Heuristic Based on Fuzzy Inference Systems for Multiobjective IMRT Treatment Planning
Chapter 23. Data-Driven Machine Learning Approach for Predicting Missing Values in Large Data Sets: A Comparison ...
Chapter 24. Mineral: Multi-modal Representation Learning
Chapter 25. Visual Perception of Mixed Homogeneous Textures in Flying Pigeons
Chapter 26. Estimating Dynamics of Honeybee Population Densities with Machine Learning Algorithms
Chapter 27. SQG-Differential Evolution for Difficult Optimization Problems under a Tight Function Evaluation Budget
Chapter 28. Age and Gender Classification of Tweets Using Convolutional Neural Networks
Chapter 29. Approximate Dynamic Programming with Combined Policy Functions for Solving Multi-stage Nurse Rostering Problem
Chapter 30. A Data Mining Tool for Water Uses Classification Based on Multiple Classifier Systems
Chapter 31. Parallelized Preconditioned Model Building Algorithm for Matrix Factorization
Chapter 32. A Quantitative Analysis on Required Network Bandwidth for Large-Scale Machine Learning
Chapter 33. Can Differential Evolution Be an Efficient Engine to Optimize Neural Networks?
Chapter 34. BRKGA-VNS for Parallel-Batching Scheduling on a Single Machine with Step-Deteriorating Jobs and Release Times
Chapter 35. Petersen Graph is Uniformly Most-Reliable
Chapter 36. GRASP Heuristics for a Generalized Capacitated Ring Tree Problem
Chapter 37. Data-Driven Job Dispatching in HPC Systems
Chapter 38. AbstractNet: A Generative Model for High Density Inputs
Chapter 39. A Parallel for Multi-Population Cultural Algorithm and Its Applications in TSP
Chapter 40. Honey Yield Forecast Using Radial Basis Functions
Chapter 41. Graph Fragmentation Problem for Natural Disaster Management
Chapter 42. Job Sequencing with One Common and Multiple Secondary Resources: A Problem Motivated from Particle Therapy for Cancer Treatment
Chapter 43. Robust Reinforcement Learning with a Stochastic Value Function
Chapter 44. Finding Smooth Graphs with Small Independence Numbers
Chapter 45. BioHIPI: Biomedical Hadoop Interface
Chapter 46. Evaluating the Dispatching Policies for a Regional Network of Emergency Departments Exploiting Health Care Big Data
Chapter 47. Refining Partial Invalidations for Indexed Algebraic Dynamic Programming
Chapter 48. Subject Recognition Using Wrist-Worn Triaxial Accelerometer Data
Chapter 49. Detection of Age-Related Changes in Networks of B Cells by Multivariate Time-Series Analysis

Book Details

  • Title: Machine Learning, Optimization, and Big Data
  • Length: 600 pages
  • Edition: 1st ed. 2018
  • Language: English
  • Publisher:
  • Publication Date: 2018-01-26
  • ISBN-10: 331972925X
  • ISBN-13: 9783319729251
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