IEEE Visualization Conference 2015 – Increasing Influence of Machine Learning

This post is authored by Yiwen Sun, Data Scientist at Microsoft.

I attended the IEEE Visualization Conference 2015 in Chicago recently and jotted down a few points related to machine learning. For those of you who are unfamiliar with this conference, it’s the largest annual gathering of practitioners, academics and researchers looking to make data visually understandable and usable. Conference paper talks are organized into three tracks: Visual Analytics Science and Technology (VAST), Information Visualization (InfoVis), and Scientific Visualization (SciVis). Co-located are three IEEE symposiums: Large Data Analysis and Visualization (LDAV), Visualization for Cyber Security (VizSec), and the very first Symposium of Visualization in Data Science (VDS).

Over 1500 attendees participated this year, including leading companies in Business Intelligence and Advanced Analytics including Bloomberg, Google, IBM, Tableau, and, of course, Microsoft.

One big impression I got is that ML and Data Visualization are getting coupled more tightly. Over half of the papers address ML techniques in their data processing step. For example, the best paper for VAST “Reducing Snapshots to Points: A Visual Analytics Approach to Dynamic Network Exploration” utilizes vectorization, normalization, and dimensionality reduction to project high-dimensional dynamic network data onto two dimensions, then visualize them using two juxtaposed views: one showing network snapshots and the other showing the evolution of the network. This enables users to differentiate regular, stable states from anomalies more easily.  

Below is a summary of ML techniques highlighted in four major application areas:

The VAST Challenge was another highlight – this is an annual contest that began in 2006 and is designed to reflect real-world analytics challenges and encourage research into novel data processing, visualization and interaction methods. This year’s challenge was to analyze individual and group movement in an amusement park over a weekend which involves a criminal investigation. Popular languages used for data processing and ML were Python and R, both of which are currently supported by Azure Machine Learning.

Overall, the conference was a great place to learn about the very latest in all things visualization, and to interact with experts in the domain.