Search "+Home -Bookshelf +Funny things +Alan Moore +YY +Sociology -Donald Knuth +Probability Theory: The Logic of Science +Math +David MacKay +Science of science +Science +Scientometrics +Books +Graph embedding +Peer review +Sentence embedding +PyTorch-BigGraph -Bertrand Meyer -G. Dobínski +Research advices +Continuous embedding +Aaron Clauset +GloVe +GraphSAGE +Learning +Paper/MacKay1991 +Hessian matrix +Interdisciplinary research -Machine learning"

Positive matches

• 0.117 + - Network geometry
• 0.039 + - Word embedding
• 0.023 + - Industry-Academic Partnership
• 0.022 + - Natural language processing
• 0.017 + - word2vec
• 0.017 + - PyTorch
• 0.017 + - Probability theory
• 0.015 + - Migration
• 0.012 + - Policy
• 0.011 + - Information theory
• 0.009 + - How to study
• 0.009 + - Edwin Thompson Jaynes
• 0.009 + - Paper
• 0.008 + - Network science
• 0.008 + - Michael Ramscar
• 0.008 + - Deep learning
• 0.008 + - Science policy
• 0.007 + - Teaching
• 0.007 + - Embedded topic model
• 0.007 + - Gender

Negative matches

• 0.010 + - Class imbalance problem
• 0.001 + - Regex
• 0.001 + - Stability selection
• 0.001 + - Weka
• 0.001 + - Class imbalance
• 0.001 + - Privacy and Deanonymization
• 0.001 + - Training dataset
• 0.001 + - Carlos Guestrin
• 0.001 + - EM algorithm
• 0.001 + - https://github.com/JohnLangford/vowpal_wabbit/wiki
• 0.001 + - Artificial neural network
• 0.001 + - GraphLab
• 0.001 + - Javascript
• 0.001 + - Machine learning for physical sciences
• 0.001 + - Rob Schapire
• 0.001 + - Netflix prize
• 0.001 + - Future of work
• 0.001 + - Gradient descent
• 0.001 + - Automated machine learning
• 0.001 + - Python/Modules