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...astive version of the wake-sleep algorithm. The result is an efficient way to train a deep belief network with substantial accuracy, as is shown by top-n The following figure shows the network used to model the joint distribution ...

...BN) are difficult to learn because the posterior distribution is difficult to infer. ...learn an efficient representation which accurately characterizes the input to the system. ...

In order to make quantitative observations about our environment, we must often acquire ...cquire these signals, we must have some minimum number of samples in order to exactly reconstruct the signal. ...

...o variables as a dot product between two low dimensional embedding vectors to achieve generalization. 4. '''Collaborative deep learning''' haven been used to couple deep learning for content information and collaborative filtering fo ...

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...rformance of a statistical machine translation system is empirically found to improve by using the conditional probabilities of phrase pairs computed by ...ence. From a probabilistic perspective, this new model is a general method to learn the conditional distribution over a variable-length sequence conditio ...

Probabilistic models approximate the distribution of data to help with analysis and prediction by relying on a set of assumptions. Data ...s other animated kids movies for her. One day her parents forget to switch to their Netflix account and watch a horror movie. ...

...ne way an AV can prevent an accident is going from a passive safety system to an active safety system once a risk is identified. ...since it is a thin, transparent layer of ice. Because of this, focus needs to be placed on AVs identifying black ice. ...

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...have infinite number of parameters, only finite number of them is required to explain the observed data. ...rkov Model. The new model, which named HDP-HMM, allows the number of stats to be infinite. ...

...hod is more effective compared to other neural network models when applied to long sentences. ...word. The decoder then selectively combines the most relevant annotations to generate each target word; this implements a mechanism of attention in the ...

...ine text. the author For example in the figure below, the GPT2 model tries to generate the continuation text given the context. On the left side, the bea ...is too probable which indicates the lack of diversity (variance) compared to human-generated texts ...

...ther overcome overfitting. Also, large margin triplet constraints are used to find basis metrics, which further improves the results. ...a <math>(\alpha , \beta , p)</math>-Lipschitz smooth function with respect to a vector norm <math>\| . \|</math> if <math>\| f(x) - f(x^') \| \leq \alp ...

In order to propose the best decision tool for Amyotrophic Lateral Sclerosis (ALS) pred ...ntrol. Its origin is still unknown, though in some instances it is thought to be hereditary. Sadly, at this point of time, it is not curable and the prog ...

...limitation and name their approach Neural Turing Machine (NTM) as analogy to [https://en.wikipedia.org/wiki/Turing_machine Turing machines] that are fin ...rs propose to ignore the known capacity limitations of working memory, and to introduce sophisticated gating and memory addressing operations that are ty ...

...ective approach for text classification is the bag-of-words model. That is to represent documents as vectors and train a classifier based on these repres To utilize the order information, people developed N-gram model, which is to predict the Nth word base on the last N-1 words with Markov Chain Model. Ye ...

...math> is called the Number of Random projections (<math>M</math>) required to project a K-dimensional manifold from <math>R^{N}</math> into <math>R^{M}</ ...structure, it is reasonable to use random projection (non-adaptive method) to map data into lower dimension (<math>M</math>) and then apply clustering al ...

...can find the discribtion for k classes in the next pages which is referred to as FDA for multi class problems. ...

...to show how we can utilize several different two-dimensional maps in order to visualize a set of pairwise similarities. Aspect maps resemble both cluster ...ays: Despite difficulty of optimizing the SNE objective function, it leads to much better solutions and since SNE is based on probabilistic model, it is ...

The current approach to tackling NP-hard combinatorial optimization problems are good heuristics or ...mine the greedy action, the current state of the problem is taken as input to a graph embedding network from which an action will be given by its output. ...