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- #REDIRECT [[rOBPCA: A New Approach to Robust Principal Component Analysis]] ...75 bytes (10 words) - 09:46, 30 August 2017
- #REDIRECT [[a Rank Minimization Heuristic with Application to Minimum Order System Approximation]] ...98 bytes (12 words) - 09:45, 30 August 2017
- #REDIRECT [[a New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization]] ...105 bytes (12 words) - 09:45, 30 August 2017
- ...rd in that we can easily point to where the mistakes occur and suggest how to correct them. ...n also be seen as a multimodal problem where the whole network/model needs to combine the solution space of learning in both the image processing and tex ...23 KB (3,760 words) - 10:33, 4 December 2017
- ...stics and signal processing. Except in some special cases the RMP is known to be computationally hard. \mbox{subject to: } & X \in C, ...8 KB (1,446 words) - 09:45, 30 August 2017
- ...pular online shopping website Amazon.com for recommending related products to users of Amazon.com based on what these users have recently purchased from Our goal, then, is to predict or infer the other preferences---in a sense, completing the matrix. ...24 KB (3,853 words) - 09:45, 30 August 2017
- ...lassify with high confidence. These attacks pose a major threat that needs to be addressed before these systems can be deployed on a large scale, especia ...much lower than claimed. In fact, the majority of these attacks were found to be ineffective against true iterative white box attacks. ...27 KB (3,974 words) - 17:54, 6 December 2018
- ...rform [http://en.wikipedia.org/wiki/Inference inference] across data sets. To this end, they demonstrate their penalized CCA method on a genomic data set ...r value decomposition will give the best rank-<math>r</math> approximation to the matrix. ...30 KB (4,829 words) - 09:45, 30 August 2017
- #REDIRECT [[a Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis]] ...131 bytes (15 words) - 09:45, 30 August 2017
- ...ide information and incorporate the side information in the classification to improve the algorithms. ...uctured classification problem in practice, we need both an expressive way to represent our beliefs about the structure, as well as an efficient probabil ...17 KB (2,924 words) - 09:46, 30 August 2017
- ...RECT [[graphical models for structured classification, with an application to interpreting images of protein subcellular location patterns]] ...145 bytes (17 words) - 09:46, 30 August 2017
- ...g box labeling. In addition, Camera Control is non-trivial, which can lead to many expensive trial-and-errors in the real world. To address these challenges, this paper presents an end-to-end active tracking solution via deep reinforcement learning. More specific ...29 KB (4,453 words) - 18:27, 16 December 2018
- ...lude the VO field, thus the paper proposes a novel deep-learning based end-to-end VO algorithm and then empirically demonstrates its viability. ...ture based methods and direct methods, which differ in the method employed to select reference points. Sparse feature based methods establish reference p ...16 KB (2,430 words) - 18:30, 16 December 2018
- #REDIRECT [[stat946f15/Sequence to sequence learning with neural networks]] ...75 bytes (10 words) - 09:46, 30 August 2017
- ...amount of work to learn more than one language past childhood. The ability to efficiently and quickly translate between languages would then be of great ...s that capture their meaning, as sentences with similar meanings are close to each other while sentences with different meanings will be far. ...23 KB (3,755 words) - 19:49, 5 February 2018
- ...is that the training requires large amounts of expert data, which is hard to obtain. In addition, an agent trained using BC is unaware of how its action ...re it takes each action since the transition function to move from state A to state B is not learned. ...24 KB (3,880 words) - 23:00, 20 April 2018
- ...s & Dietterich (2019), showing that the classification error rose from 25% to 62% when some corruption was introduced on the ImageNet test set. ...ce that networks trained on translation augmentations are highly sensitive to the shifting of pixels. ...11 KB (1,652 words) - 18:44, 6 December 2020
- ...pecially trained to be applied on one dataset alone and might be difficult to use for non-experts in a more general setting (Perslev et al., 2019). ...r architectural tuning to be applied to variable data sets, and it is able to classify sleep stages at any temporal resolution (Perslev et al., 2019). ...8 KB (1,170 words) - 01:41, 26 November 2021
- #REDIRECT [[from Machine Learning to Machine Reasoning]] ...56 bytes (7 words) - 09:46, 30 August 2017
- '''Sequence to sequence learning''' has been used to solve many tasks such as machine translation, speech recognition, and text ...other. This allows to precisely control the maximum length of dependencies to be modeled. ...27 KB (4,178 words) - 20:37, 28 November 2017
Page text matches
- ...hence because of this for whatever data we need to feed in the network has to be continuous in nature. Images can easily be represented as real-valued ve ...parameters it needs to learn is quite high. There have been some solutions to it: ...4 KB (646 words) - 19:44, 26 October 2017
- ...batch-normalization layers right before the activations (to have the input to the activations be normalized as desired). Both networks were trained with ...he 15th, 50th, and 85th percentiles of the input were recorded. The figure to the left demonstrates how these values changed during training. The y axis ...4 KB (637 words) - 02:07, 28 November 2018
- ...properties (cite). Algorithms for inference do exist but they do however, come at a price of reduced expressive capabilities in logical inference and prob ...852 bytes (116 words) - 09:46, 30 August 2017
- ==A Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis== [[A Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis]] ...2 KB (222 words) - 09:45, 30 August 2017
- ...>; on the other hand we would reject the samples if the ratio is not close to 1. At x=9; we will reject samples according to the ratio <math> \frac {f(x)}{c \cdot g(x)} </math> after sampling from <ma ...6 KB (937 words) - 09:45, 30 August 2017
- 3 data sets are used to compare CSL to existing methods, 1 function regression task and 2 image classification tas ...s <math>f_j</math> as well as determine which mapping function corresponds to each of the <math>m</math> observations. 3 scalar-valued, scalar-input func ...5 KB (878 words) - 19:25, 15 November 2020
- ...d during training time. Here by defining tasks as domains, the paper tries to overcome the problem in a model-agnostic way. ...1 KB (200 words) - 15:47, 9 November 2020
- ...sed for the uniform distribution, other methods must be developed in order to generate pseudo random numbers from other distributions. ...he fact that when a random sample from the uniform distribution is applied to the inverse of a cumulative density function (cdf) of some distribution, th ...5 KB (836 words) - 09:45, 30 August 2017
- ...on of its classes. This decomposition is always possible and it is reduced to one class only in the case of an irreducible chain. ...ath> The state 3 can go to every other state but none of the others can go to it ...7 KB (1,129 words) - 09:45, 30 August 2017
- -\textbf{u}^T\textbf{a} \; \textrm{ subject } \; \textrm{ to } \; \|\textbf{u}\|^2_2 \leq 1, \; \|\textbf{u}\|_1 \leq c_1 and we differentiate, set the derivative to 0 and solve for <math>\textbf{u}</math>: ...2 KB (311 words) - 09:45, 30 August 2017
- '''NOTE: Wiki has been migrated from wikicoursenote.com to wiki.math.uwaterloo.ca/statwiki''' ==Go to [[stat841f10|Stat441/841 & CM 463/763-Fall 2010]] == ...5 KB (769 words) - 22:53, 5 September 2021
- ...pefully, the pattern of the teams and lineups in the latent space can lead to interesting conclusions. Secondly, we apply the selected methods to lineup data sets and get the plots of the lineups in the low-dimensional sp ...6 KB (983 words) - 09:46, 30 August 2017
- ...<math>f(x)</math> so that a variation of importance estimation can be used to estimate an integral in the form<br /> All that is required is a Markov chain which eventually converges to <math>f(x)</math>. ...5 KB (865 words) - 09:45, 30 August 2017
- ...ork, the inputs are no longer normalized at each hidden layer. So, we want to reduce this internal covariate shift by normalizing the input at each hidde ...However, this is a very expensive operation, and does not necessarily lead to a gradient function that is well defined. ...6 KB (931 words) - 21:10, 28 November 2018
- ...r the gander , some of which occasionally amuses but none of which amounts to much of a story” contains negative sentiment, but it is not immediately cle This competition seeks to implement machine learning algorithms that can determine the sentiment of a ...7 KB (1,125 words) - 09:46, 30 August 2017
- ...n the Bayesian and Frequentist views on probability, along with references to '''Bayesian Inference'''. ...enough, by the central limit theorem, the Normal distribution can be used to approximate a Binomial distribution. ...6 KB (924 words) - 09:45, 30 August 2017
- ...n up your name at the moment. When you chose the paper that you would like to present, add its title and a link to the paper. ...3 KB (418 words) - 09:45, 30 August 2017
- ...ces as the parameters in the model are tuned, and thus the model is unable to evolve. ...would result in the error values of the deeper network being at most equal to those of the shallower network. However, this result is not seen in practic ...6 KB (1,020 words) - 12:01, 3 December 2021
- ...riants of this model have been introduced by the authors, two of which try to learn task-specific word vectors for words. It is observed that learning ta ...different models for doing different tasks. For instance, they can be fed to CNNs for document or sentence classification. The vector representations us ...7 KB (1,086 words) - 22:49, 13 November 2018
- ...playstyle E_g(h(x)) \rightarrow</math>the expectation of h(x) with respect to g(x), where <math>\displaystyle \frac{f(x)}{g(x)} </math> is a weight <math The method of Importance Sampling is simple but can lead to some problems. The <math> \displaystyle \hat I </math> estimated by Importa ...6 KB (1,083 words) - 09:45, 30 August 2017