Search "+Peter Norvig +Automated machine learning +Class imbalance problem +Travelling salesman problem -Probability, Paradox, and the Reasonable Person Principle +Cross validation +Cluster analysis +Computer science -Ulrike von Luxburg +Science policy +Policy +scikit-learn +Public health policy +Boosting (machine learning) +Gradient descent -Neural network"

Positive matches

• 0.216 + - Machine learning
• 0.106 + - Class imbalance
• 0.033 + - Opioid crisis
• 0.025 + - Science
• 0.025 + - Interdisciplinary research
• 0.022 + - Research funding
• 0.022 + - Decision tree
• 0.021 + - Data clustering
• 0.020 + - Neuron
• 0.016 + - Yoav Freund
• 0.016 + - Recommender system
• 0.016 + - Ron Meir
• 0.016 + - Rob Schapire
• 0.013 + - tfidf
• 0.013 + - Random forest
• 0.011 + - Python/Modules
• 0.011 + - IPython notebook
• 0.011 + - Learning
• 0.010 + - Poker
• 0.010 + - Jupyter/notebook

Negative matches

• 0.018 + - Paper/Srivastava2014
• 0.008 + - Jack Terwilliger
• 0.006 + - Liquid state machine
• 0.006 + - Neural Turing machine
• 0.006 + - word2vec
• 0.006 + - Recurrent neural network
• 0.005 + - Dropout
• 0.004 + - Ilya Sutskever
• 0.004 + - Probability
• 0.004 + - Graph embedding
• 0.003 + - Hierarchical softmax
• 0.003 + - sense2vec
• 0.003 + - wiki2vec
• 0.002 + - Skip-gram
• 0.002 + - WordRank
• 0.002 + - Attention (Deep learning)
• 0.002 + - Gensim
• 0.001 + - Tomas Mikolov
• 0.001 + - Paper/Levy2014
• 0.001 + - Paper/Hamilton2016