Search "+Peter Norvig +Automated machine learning +Class imbalance problem +Travelling salesman problem -Probability, Paradox, and the Reasonable Person Principle +Cross validation +Cluster analysis +Machine learning +Machine learning for healthcare +tf-idf +Boosting (machine learning) -Ron Meir +Probability +Gradient descent +Learning -Neural network"

Positive matches

• 0.117 + - Class imbalance
• 0.026 + - Recommender system
• 0.023 + - Text analysis
• 0.022 + - Data clustering
• 0.022 + - Ulrike von Luxburg
• 0.022 + - Deep learning
• 0.021 + - Neuron
• 0.021 + - scikit-learn
• 0.021 + - Probability theory
• 0.021 + - Probability distribution
• 0.019 + - Pointwise mutual information
• 0.018 + - Yoav Freund
• 0.017 + - Rob Schapire
• 0.016 + - How to study
• 0.016 + - Michael Ramscar
• 0.013 + - Regular expression
• 0.013 + - Future of work
• 0.013 + - tfidf
• 0.013 + - Lexical feature selection
• 0.013 + - NLTK

Negative matches

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