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nnrnnn 0 n1 2 n 3 1 4 5 3 n 6 7 n32n4 6n 7n nrnnn nnnn nn6767 86794 9 nnn1nn 8 nn n 6nn n n7 x028 6n 76n 72 AB. http://www.solidinvestmentsfl.com Solid Investments Specializes in Triple Net (NNN) Leased Property. We assist the Buyer with their 1031 exchange, helping to find high quality, investment grade absolute net leased income producing property. Solid Investments Specializes in Triple Net (NNN) Leased Property. We assist the Buyer with their 1031 exchange, helping to find high quality, investment grade absolute net leased income producing property. 1 Ip D K n n n n p np np n n p n ppp 22 N Cf D n n p p n n p n n n n n xp n n n n n n n pp n x pn n n n n n pn n n n qn n n pn n n n p n n n n n n n n n n n n p n n n x n n p B n n n p n 23 Ip If n n n 1 I n n n n n n p p n n p n 0 0 Cl X gX2 XlXg fgp8ejpf X0lnnnXp 8ejpejljf ffXcpjfpXjXefjmjnnnXejpfjXmXjXeX lgX X nXp El Eln EXp qg X g XX g X g PXX XlXq8 Xg gXlXn pg XXllp lX ngn Xgp gpn nXl l n 8g0 Xgp El n ln l00 X X X n 8 Xp g00 n n X Xl ElX l Xl X 8pEXp l Socher. , Bauer, Manning, NG 2013. Problem. How can we parse a sentence and create a dense representation of it? . N-grams have obvious . problems, most important is . sparsity. Can we resolve syntactic ambiguity with context? “They ate . Arun . Mallya. Best viewed with . Computer Modern fonts. installed. Outline. Why Recurrent Neural Networks (RNNs)?. The Vanilla RNN unit. The RNN forward pass. Backpropagation. refresher. The RNN backward pass. Li Deng . Deep Learning Technology Center. Microsoft AI and Research Group. Invited Presentation at NIPS Symposium, December 8, 2016. Outline. Topic one. : RNN versus Nonlinear Dynamic Systems;. sequential discriminative vs. generative models.

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\r\n Machine l earning - based i ttH → inv isible Xubo GU @ Shanghai Jiao Tong University , School of Mechanical Engineering CERN Work Project Report CERN, CMS Supervisor s : Benjamin Krikler , Oli nnrnnnnnnnnnnnnnn1nnnn nnnnnnnnnnnnn nn 2nnnnnnnnn nnnnnnnnnnnn-nnn nnn nnnnnnnnnnnnnnn nnnn n nnn 3454n6 nn78n99-nn894nnnnnnnnnn-62n8nnn728nnnnnnn3894n n// nnnn nnnnnnnnnnnnnnrnnnnnnnnnnnnnnnnnnnn n Ad- 0.2inordertoachieveSIRimprovementsandmaintainSARandSDR.Comparingcolumns2,3,4,and5andcolumns6,7,8,and9,wecanobservethatjointlytrainingthenetworkwiththemaskingfunctionachieveslargeimprovements.Since STAT 689. forecasting. Forecasting is the process of making predictions of the future based on past and present data!. forecasting. Coming up with predictions is important.. It is also very hard since none has the correct model of the world.. Human Language Technologies. Giuseppe Attardi. Some slides from . Arun. . Mallya. Università di Pisa. Recurrent. RNNs are called . recurrent.  because they perform the same task for every element of a sequence, with the output depending on the previous values..