Tag: machine learning
Machine learning uses algorithms to build analytical models, helping computers “learn” from data. It can now be applied to huge quantities of data to create exciting new applications. Researchers at WID are developing new methodology and theory for extracting useful information from data which may be noisy or high-dimensional, contain missing elements, or come from a variety of different sensors or streaming input.
Machine learning at WID plays a key role in problems as diverse as understanding the immune system, finding the funniest cartoon captions, and developing driverless cars.
Machine learning is an important component of WID’s Data Science Hub.
Deciphering Gene Regulatory Networks
Systems Biology researcher Sushmita Roy is leading an effort putting computational methods to work characterizing the gene regulatory networks responsible for cell differentiation.
Learning Like Humans, Machines Extend the Reach of Research
WID Optimization researchers have partnered with faculty across campus to work on ways to use computers to make better use of human brain power.
Understanding the Immune System with Machine Learning
Systems Biology researchers Deborah Chasman and Sushmita Roy are using machine learning to identify virus and pathogenicity-specific regulatory networks which may guide the design of effective therapeutics for infectious diseases. The work is described in a recent paper in PLOS Computational Biology.
Big Data: Madison visionaries turn tiny pieces of data into big ideas
The big data phenomenon also begun to take hold in and around the city, from institutions like state and city government to the health care industry.
Finding Meaning in Big Data
Discovery fellows Rebecca Willett and Rob Nowak are creating algorithms to make sense of big data and help machines learn.
How New Yorker Cartoons Could Teach Computers to be Funny
The magazine is using crowdsourcing algorithms developed by WID researchers to find the funniest cartoon captions
The Science of Funny: Active Machine Learning & Cartoons
The New Yorker is using a machine learning system developed by WID Optimization researchers to sort through captions for their weekly cartoon caption contest.
Celebrate Summer and Raise Your App…Um…Glass!
With the aid of entrepreneur Joe Sheahan ’04, Discovery Fellow Rob Nowak, ’90, MS’91, PhD’95 and Kevin Jamieson, PhD ’15 poured their thought experiment into the iPhone marketplace.
Discovery Fellow Aims to Predict Healthcare Outcomes
David Page tackles relational databases and algorithms to predict and improve patient health.
Catalyzing UW-Madison’s neuroengineering community
Discovery Fellow Rebecca Willett co-organizes first ever UW-Madison Neuroimaging, Computational Neuroscience, and Neuroengineering Workshop
Researchers Search for New Ways to Balance Big Data and Privacy
How can researchers extract useful information from patient data to develop life-saving treatments while making sure records stay private and protected? A WID collaboration looks for an answer.
Closing the Loop on Big Data… One Beer at a Time
WID researchers develop algorithms for many applications and industries, but one side project boasts a more playful goal: Mapping brew preferences.
Tools for Discovery: Sushmita Roy
Systems Biology scientist Sushmita Roy finds and predicts trends in biological networks. Her toolkit includes computer science programs, blogs and other bright minds in the Discovery Building.
Tools for Discovery: Jordan Ellenberg
UW–Madison Mathematics Professor and Discovery Fellow Jordan Ellenberg provides perspective on programming in math, Google Hangout and why our brains are the ultimate tool for discovery.