- Referenced in 286 articles
- application to the problem of training neural networks. Scatter search is an evolutionary method that ... search can compete with the best-known training algorithms in terms of training quality while...
- Referenced in 262 articles
- networks with many layers (deep architectures) and train them with the method introduced ... Salakhutdinov). This method includes a pre training with the contrastive divergence method publishing ... fine tuning with common known training algorithms like backpropagation or conjugate gradient...
- Referenced in 261 articles
- Futhermore, this version includes an algorithm for training large-scale transductive SVMs. The algorithm proceeds ... Spectral Graph Transducer. SVMlight can also train SVMs with cost models (see [Morik...
Neural Network Toolbox
- Referenced in 175 articles
- layers. With the toolbox you can design, train, visualize, and simulate neural networks ... system modeling and control. To speed up training and handle large data sets...
- Referenced in 190 articles
- digits, available from this page, has a training set of 60,000 examples...
- Referenced in 99 articles
- designed to determine a cluster of training patterns belonging to the same class. The weights ... comparing the inter-pattern distances of the training patterns. This offers a significant advantage over ... often time consuming) weight modification strategy to train individual neurons. The individual clusters (represented...
- Referenced in 84 articles
- images per class. There are 50000 training images and 10000 test images. The dataset ... divided into five training batches and one test batch, each with 10000 images. The test ... randomly-selected images from each class. The training batches contain the remaining images in random ... order, but some training batches may contain more images from one class than another. Between...
- Referenced in 94 articles
- where each iteration operates on a single training example. In contrast, previous analyses of stochastic ... depend directly on the size of the training set, the resulting algorithm is especially suited ... runtime does depend linearly on the training set size. Our algorithm is particularly well suited...
- Referenced in 114 articles
- first constructs a vocabulary from the training text data and then learns vector representation...
- Referenced in 105 articles
- schemes (including multi-input and multi-output training). runs seamlessly on CPU and GPU. Read...
- Referenced in 101 articles
- coming with no less than 50 million training examples and others with 7 billion test...
- Referenced in 60 articles
- topics simultaneously. In multi-label learning, the training set is composed of instances each associated ... label sets of unseen instances through analyzing training instances with known label sets. In this ... instance, its K nearest neighbors in the training set are firstly identified. After that, based...
- Referenced in 67 articles
- Vector Machines (SVMs) for regression problems are trained by solving a quadratic optimization problem which ... solve, where l is the number of training examples. In this paper, we propose...
- Referenced in 64 articles
- package caret: Classification and Regression Training. Misc functions for training and plotting classification and regression...
- Referenced in 63 articles
- former case we provide a new “training” algorithm that finds the optimal parameter ... periodogram criterion; for the first two methods “training” can be used to find the optimal...
- Referenced in 74 articles
- been enhanced, in particular by information about training sequences used for the construction of nucleotide...
- Referenced in 73 articles
- mention a whole host of training and resource...
- Referenced in 45 articles
- Parallel software for training large scale support vector machines on multiprocessor systems Parallel software ... solving the quadratic program arising in training support vector machines for classification problems is introduced ... real-world data sets with millions training samples highlight how the software makes large scale...
- Referenced in 47 articles
- Toolbox (TT=Tensor Train). TT(Tensor Train) format is an efficient way for low-parametric...
- Referenced in 65 articles
- Although the benchmark data set used to train and test the current method was from...