papers on the horizon

[DolevArtzi]

• https://www.stat.cmu.edu/~ryantibs/papers/sparsitynn.pdf
• https://paperswithcode.com/paper/recursive-deep-models-for-semantic
• https://nlp.stanford.edu/pubs/StanfordCoreNlp2014.pdf
• RNN papers https://icml.cc/2011/papers/125_icmlpaper.pdf https://aclanthology.org/D11-1014.pdf
• in progress, Bengio 2003a
• MLE
• Perceptron
• Minksy XOR unsolvable
• Backprops
  • Hinton Backprop
• Vanishing gradients
• SVM
  • SVM
• RBM
• Deep Image Net

[DolevArtzi]

"A Logical Calculus of the Ideas Immanent in Nervous Activity" by Warren McCulloch and Walter Pitts (1943) - This paper introduced the concept of a "neural network" as a computational model for the workings of the brain.

"Perceptrons" by Frank Rosenblatt (1958) - This paper introduced the concept of the perceptron, a simple mathematical model of a neural network.

"The Logic Theorist" by Allen Newell, J. C. Shaw, and Herbert Simon (1956) - This paper described a program called the Logic Theorist, which was able to prove mathematical theorems using artificial intelligence techniques.

"Grammar Induction and Parsing with a Recursive Neural Network" by Stephen Clark and James R. Curran (2007) - This paper introduced the use of recursive neural networks for natural language processing tasks.

"The Elements of a Scientific Theory of Intelligence" by Judea Pearl (2000) - This paper introduced the concept of causality, which has become a key focus of AI research.

"Hierarchical Temporal Memory" by Jeff Hawkins, Dileep George, and D. S. Modha (2004) - This paper introduced the concept of hierarchical temporal memory, a computational model for the workings of the brain.

"Human-Level Control through Deep Reinforcement Learning" by Volodymyr Mnih, et al. (2015) - This paper introduced the use of deep reinforcement learning for achieving human-level performance in a range of challenging tasks.