November 24, 2017 UMD Home FabLab AIMLab
MLMR 2017
Machine Learning
for
Materials Research
Bootcamp & Workshop
2017
Machine Learning for Materials Research: Bootcamp
Data Fundamentals
Data Preprocessing
Tue 6/27
Supervised Learning
Theory, Data, Algorithms
Wed 6/28
Unsupervised Learning
Theory & Algorithms
Thu 6/29
Filtering: Noise Smoothing
Background Subtraction
Feature Extraction
  • Cross-correlation Wavelets
  • Edges
  • Closed Boundaries
  • Shapes
Data Handling
  • Cross Validation
  • Prediction
Algorithms
  • Regularized Least Squared
  • Support Vector Machines
  • Neural Networks
  • Decision Trees & Ensemble Learning
  • Genetic Programming
Theory
Similarity Measures
Latent Variable Analysis
Spectral Unmixing
Matrix Factorization
Clustering
Machine Learning for Materials Research: Workshop
Workshop
Fri 6/30

Conference Support

Colleges A. James Clark School of Engineering
The College of Computer, Mathematical, and Natural Sciences

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