db.cs.cmu.edu
Graph Similarity with Attribution and Alignment - Carnegie Mellon Database Group
http://db.cs.cmu.edu/projects/graph-similarity-with-attribution-and-alignment
Graph Similarity with Attribution and Alignment. This project focuses on revealing similarities between graphs at the node, as well as the graph level. It comprises 3 main problems:. Graph similarity with known correspondence. How much did a network change since yesterday? How different is the wiring between a left-handed male’s brain and a right-handed female’s brain? Graph similarity without known correspondence:. Can we identify structural twins in social networks? Joshua T. Vogelstein. Author={Berlin...
ml.jhu.edu
Machine Learning @ Johns Hopkins University | People
http://ml.jhu.edu/people
Filter by application area: Astrophysics. To find many more JHU faculty in each application area, follow links from the research. Page This page lists only members of the cross-cutting machine learning group. Dimensionality reduction, statistical signal processing, online learning, adversarial learning, stochastic approximation. CS 675: Statistical Machine Learning. CS 479/679: Representation Learning. Graphical models, transfer learning, structured regularization. CS 475: Machine Learning. AMS 735: Topi...
bickson.blogspot.com
Large Scale Machine Learning and Other Animals: January 2015
http://bickson.blogspot.com/2015_01_01_archive.html
Large Scale Machine Learning and Other Animals. Friday, January 30, 2015. GraphLab Hisotry O'Reilly Podcast. My friend Ben Lorica just released a postcast. With our CEO Prof. Carlos Guestrin about GraphLab project history. I must admit I got some nice credits there. :-). Wednesday, January 28, 2015. Johns Hopkins ML Postdoc Position. I got this from my colleague Joshua Vogelstein. At Johns Hopkins University invites outstanding candidates to apply for a postdoctoral or. Dept of Computer Science),. M$ Acq...
informationashvins.wordpress.com
June | 2014 | Information Ashvins
https://informationashvins.wordpress.com/2014/06
Archive for June, 2014. June 28, 2014. A friend of the blog was recently asking both of us how to cluster time series (of possibly different lengths), and in response to that query I had looked at the paper “ A novel hierarchical clustering algorithm for gene sequences. But any technique seems to require some notion of similarity to proceed. As Leslie Valiant. Says in his book,. I hold the view that supervised learning is a powerful natural phenomenon, while unsupervised learning is not. Et al, discusses...
neurodata.io
Neurodata
https://neurodata.io/people
Carey E. Priebe. Michael I. Miller.
informationashvins.wordpress.com
Clusters | Information Ashvins
https://informationashvins.wordpress.com/2014/06/28/clusters
Laquo; Scaling Laws for Waste. Random Episodic Silent Thought. June 28, 2014. A friend of the blog was recently asking both of us how to cluster time series (of possibly different lengths), and in response to that query I had looked at the paper “ A novel hierarchical clustering algorithm for gene sequences. But any technique seems to require some notion of similarity to proceed. As Leslie Valiant. Says in his book,. So maybe clustering is not a powerful natural phenomenon (but would Rand disagree. By my...
smart-stats.org
SMARTies | smart-stats.org
http://www.smart-stats.org/members
Skip to main content. Johns Hopkins Bloomberg School of Public Health. 615 N Wolfe Street, Room E3038. Baltimore, MD 21205. Email: jbai at jhsph dot edu. BS: Mathematics/Statistics, Tsinghua University, 2011. At] jhsph [dot] edu. At] jhsph [dot] edu. PhD Candidate in Biostatistics. At] gmail [dot] com. MPH: Public Health, Johns Hopkins University, 2009. BS: Biomedical Engineering, University of Southern California, 2004. At] jhsph [dot] edu. At] jhsph [dot] edu. Personal webpage: jonathangellar.com.
