<--- Back to Details
First PageDocument Content
Machine learning / Artificial intelligence / Learning / Mathematics / Sparse approximation / Semantic memory / Regularization / Supervised learning / Semantic network / Sparse matrix / Dense graph
Date: 2011-02-04 14:34:11
Machine learning
Artificial intelligence
Learning
Mathematics
Sparse approximation
Semantic memory
Regularization
Supervised learning
Semantic network
Sparse matrix
Dense graph

Discovering Structure by Learning Sparse Graphs Brenden M. Lake and Joshua B. Tenenbaum Department of Brain and Cognitive Sciences Massachusetts Institute of Technology {brenden, jbt}@mit.edu Abstract

Add to Reading List

Source URL: cims.nyu.edu

Download Document from Source Website

File Size: 653,10 KB

Share Document on Facebook

Similar Documents

PROJECT PAI  TECHNICAL WHITEPAPER SUMMARY PAI BLOCKCHAIN PROTOCOL: A DECENTRALIZED ARTIFICIAL INTELLIGENCE NETWORK

PROJECT PAI TECHNICAL WHITEPAPER SUMMARY PAI BLOCKCHAIN PROTOCOL: A DECENTRALIZED ARTIFICIAL INTELLIGENCE NETWORK

DocID: 1xVWW - View Document

Persistent Memory for Artificial Intelligence Bill Gervasi Principal Systems Architect  Santa Clara, CA

Persistent Memory for Artificial Intelligence Bill Gervasi Principal Systems Architect Santa Clara, CA

DocID: 1xVOm - View Document

Journal of Machine Learning Research, 4th International Conference on Predictive Applications and APIs  Marvin - Open source artificial intelligence platform Lucas B. Miguel

Journal of Machine Learning Research, 4th International Conference on Predictive Applications and APIs Marvin - Open source artificial intelligence platform Lucas B. Miguel

DocID: 1xVLb - View Document

Cybersecurity Powered by Artificial Intelligence and the Blockchain HEROIC.com Team February 2018

Cybersecurity Powered by Artificial Intelligence and the Blockchain HEROIC.com Team February 2018

DocID: 1xVHi - View Document