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HKU-COMP8053

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  1. ECCV 2014 Visualizing and Understanding Convolutional Networks

  2. TCSVT 2012 Empirical Studies in Information Visualization Seven Scenarios

  3. TCSVT 2013 Feature Driven Visual Analytics of Soccer Data

  4. TCSVT 2013 Perceptually Driven Visibility Optimization for Categorical Data Visualization

  5. TCSVT 2013 Temporal MDS Plots for Anlaysis of Multivariate Data

  6. TCSVT 2013 TimeSeer Scagnositcs for High-Dimensional Time Series

  7. TCSVT 2013 Visualizing Natural Image Statistics

  8. TCSVT 2014 Visual Abstraction and Exploration of Multi-class Scatterplots

  9. TCSVT 2014 Visual Methods for Analyzing Probabilistic Classification Data

  10. TCSVT 2016 Spatial Reasoning and Data Displays

  11. TCSVT 2016 Temporal MDS Plots for Analysis of Multivariate Data

  12. TCSVT 2017 Clustervision Visual Supervision of Unsupervised Clustering

  13. TCSVT 2017 Do Convolutional Neural Networks Learn Class Hierarchy

  14. TCSVT 2017 LDSScanner Exploratory Analysis of Low-Dimensional Structures in High-Dimensional Datasets

  15. TCSVT 2017 Visual Methods for Anlayzing Probabilistic Classification Data

  16. TCSVT 2017 What Would a Graph Look Like in This Layout? A Machine Learning Approach to Large Graph Visualization

  17. VAST 2011 Observation-Level Interaction with Statistical Models for Visual Analytics

  18. VIS 2017 Visual Integration of Data and Model Space in Ensemlbe Learning

  19. VIS 2017 Visualization of Big Spatial Data using Coresets for Kernel Density Estimates

  20. TCSVT 2016 Optimal Sets of Projections of High-Dimensional Data

Assignment 1. Dimension Reduction and Clustering Algorithms

  1. Choose one dimension reduction or clustering algorithm to implement using c/c++, python, matlab

  2. All core algorithms should be written by yourself, except the basic matrix operations, such as SVD decomposition

  3. When submit the assignment, the readme.txt should write what dataset has been used and how to run your codes

  4. Here are some recommaned datasets. http://web.mit.edu/cocosci/isomap/datasets.html and https://drive.google.com/drive/u/1/folders/0B_P65v9k7Nmed2JPVWNlV3hYYVE

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Paper Presentation