Add mathematical foundations to AI chapter

assets/bibliography.bib

@@ -662,3 +662,64 @@
   doi             = {10.1162/NECO_a_00052},
   url             = {https://doi.org/10.1162/NECO_a_00052}
 }
+
+
+
+@Article{Rumelhart1986,
+  author          = {Rumelhart, David E. and Hinton, Geoffrey E. and Williams,
+                  Ronald J.},
+  title           = {Learning representations by back-propagating errors},
+  journal         = {Nature},
+  year            = 1986,
+  month           = {Oct},
+  day             = 01,
+  volume          = 323,
+  number          = 6088,
+  pages           = {533-536},
+  abstract        = {We describe a new learning procedure, back-propagation, for
+                  networks of neurone-like units. The procedure repeatedly
+                  adjusts the weights of the connections in the network so as to
+                  minimize a measure of the difference between the actual output
+                  vector of the net and the desired output vector. As a result
+                  of the weight adjustments, internal `hidden' units which are
+                  not part of the input or output come to represent important
+                  features of the task domain, and the regularities in the task
+                  are captured by the interactions of these units. The ability
+                  to create useful new features distinguishes back-propagation
+                  from earlier, simpler methods such as the
+                  perceptron-convergence procedure1.},
+  issn            = {1476-4687},
+  doi             = {10.1038/323533a0},
+  url             = {https://doi.org/10.1038/323533a0}
+}
+
+@book{book:2530718,
+  title           = {Machine Learning Refined: Foundations, Algorithms, and
+                  Applications},
+  author          = {Jeremy Watt, Reza Borhani, Aggelos K. Katsaggelos},
+  publisher       = {Cambridge University Press},
+  isbn            = {1108480721,9781108480727},
+  year            = 2020,
+  edition         = 2
+}
+
+@article{ruder2016overview,
+  title           = {An overview of gradient descent optimization algorithms},
+  author          = {Ruder, Sebastian},
+  journal         = {arXiv preprint arXiv:1609.04747},
+  year            = 2016
+}
+
+@article{DBLP:journals/corr/WangRX17,
+  author          = {Haohan Wang and Bhiksha Raj and Eric P. Xing},
+  title           = {On the Origin of Deep Learning},
+  journal         = {CoRR},
+  volume          = {abs/1702.07800},
+  year            = 2017,
+  url             = {http://arxiv.org/abs/1702.07800},
+  archivePrefix   = {arXiv},
+  eprint          = {1702.07800},
+  timestamp       = {Mon, 13 Aug 2018 16:46:19 +0200},
+  biburl          = {https://dblp.org/rec/journals/corr/WangRX17.bib},
+  bibsource       = {dblp computer science bibliography, https://dblp.org}
+}