CS 8395-03 - Visual Analytics & Machine Learning

Overview Syllabus Schedule Assignments Project Papers Resources


All the VAML

This is the course webpage for Visual Analytics & Machine Learning.

Instructor

Matthew Berger

email: matthew.berger@vanderbilt.edu

office hours: TR 2:00-3:00, JH 379

Lectures

MW, 2:10-3:25, FGH 258

Syllabus

Go here for the syllabus.

Schedule

Week 1 (January 6): Introduction to Visual Analytics
Monday: Course Introduction, Visual Analytics? (slides, pdf, notebook)
 Required Reading: Visual Analytics: Definition, Process and Challenges
Wednesday: Fundamentals of Data Visualization: Visual Encodings, Perceptual Principles (slides, pdf, notebook)
— Assignment 1 Posted
 Required Reading: A Layered Grammar of Graphics, Vega-Lite, Which Visualization?
Week 2 (January 13): Authoring Visualizations with D3
Monday: Basics of D3, Observable Notebooks (notebook)
 Required Reading: see Resources
Wednesday: Designing visualizations with D3 (notebook)
 Required Reading: see Resources
Week 3 (January 20): Interactive Machine Learning
Monday: Martin Luther King Jr. Day: No Class
Wednesday: Interactive Machine Learning (slides, pdf)
— Assignment 1 Due, Assignment 2.1 Posted
 Required Reading: The Role of Humans in Interactive Machine Learning, Human-Centered Machine Learning
Week 4 (January 27): Mixed-Initiative Visual Exploration, Pt. 1
Monday: Steerable Dimensionality Reduction, Pt. 1 (slides, pdf, notebook)
 Required Reading: Visual Dimensionality Reduction, iPCA, Contrastive Learning, Brushing Dimensions
Wednesday: Steerable Dimensionality Reduction, Pt. 2 (slides, pdf)
 Required Reading: Spatialization Semantics, InterAxis, AxiSketcher, Steerable tSNE
Week 5 (February 3): Mixed-Initiative Visual Exploration, Pt. 2
Monday: Exploring Topic Models, Pt. 1 (slides, pdf)
— Assignment 2.1 Due, Assignment 2.2 Posted
 Required Reading: ParallelTopics, HierarchicalTopics, TopicPanorama, Serendip
Wednesday: Exploring Topic Models, Pt. 2
 Required Reading: VAiRoma, , Comparative Exploration, ConToVi
Week 6 (February 10): Mixed-Initiative Visual Exploration, Pt. 3
Monday: Presentations: Nhung (PhenoLines), Roza (SAX Navigator)
Wednesday: Presentations: Matthew (Clustervision), Geoffrey (Spatiotemporal Social Media Analytics)
— Assignment 2.2 Due, Assignment 3 Posted
Week 7 (February 17): Visual Analytics for Model Understanding, Pt. 1
Monday: Presentations: Ziqi (RegressionExplorer), Yuan (Instance-Level Visual Explanations) (slides, pdf)
Wednesday: Deep Learning: Dataflows, Training
 Required Reading: Visualizing Deep Network Graphs, DeepTracker, Generative Model Training
Week 8 (February 24): Visual Analytics for Model Understanding, Pt. 2
Monday: Presentation: Jason (DeepEyes), Understanding Generative Models (slides, pdf)
 Required Reading: GANViz, GAN Lab
Wednesday: Presentations: Yayan (CNNs and Hierarchies), Congnin (The What-If Tool)
Week 9 (March 2): Spring Break
Week 10 (March 9): Visual Analytics for Model Understanding, Pt. 3
Monday: Understanding Language Models, Pt. 1 (slides, pdf)
 Required Reading: Semantics in Word Embeddings, Interactions with Word Embeddings, NLIZE
Wednesday: Class cancelled
— Assignment 3 Due
Week 11 (March 16): Project Proposals, Model Understanding
Monday: Project Proposal Presentations
— Project Proposals Due
Wednesday: Project Proposals Continued, Presentation: Kyle (Hidden Memories of RNNs)
Week 12 (March 23): Visual Analytics for Model Training, Pt. 1
Monday: Interactive Model Training (slides, pdf)
 Required Reading: iVisClassifier, Visual Document Classifier, Video Classifiers, Incremental Visual Data Classification
Wednesday: Presentation: Jiayao (SEQ2SEQ-VIS), (Inter-)Active Learning of Classifiers (slides, pdf)
 Required Reading: VIAL, User-Centered AL, Experimental Comparison of Visual AL, Visual Bootstrapping
Week 13 (March 30): Visual Analytics for Model Training, Pt. 2
Monday: Presentations: Cailey (BaobabView), Kim (ProtoSteer)
Wednesday: Ensembles (slides, pdf)
— Project Prototypes Due
 Required Reading: BEAMES, Data-Model Ensemble, Visual Architecture Search
Week 14 (April 6): Visual Analytics for Model Training, Pt. 3
Monday: Constructing Topic Models, Pt. 1 (slides, pdf)
 Required Reading: UTOPIAN, Progressively Learning Topic Models, Speculative Execution
Wednesday: Constructing Topic Models, Pt. 2 (slides, pdf)
 Required Reading: LTMA, HitL Topic Modeling, ALTO
Week 15 (April 13): Learning for Vis
Monday: (Semi-)automatically generating statistical graphics (slides, pdf)
 Required Reading: Show Me, Draco, Data2Vis, VizML
Wednesday: (Semi-)automatically generating infographics and graph layouts (slides, pdf)
 Required Reading: Generating Infographics, Deep Drawing, Graph Latent Spaces
Week 16 (April 20): Project Presentations
Monday: Project Presentations
Friday: Final Project Submissions Due