Search results
Results from the WOW.Com Content Network
The explanation made in the original paper [1] was that batch norm works by reducing internal covariate shift, but this has been challenged by more recent work. One experiment [2] trained a VGG-16 network [5] under 3 different training regimes: standard (no batch norm), batch norm, and batch norm with noise added to each layer during training ...
It is called instance-based because it constructs hypotheses directly from the training instances themselves. [3] This means that the hypothesis complexity can grow with the data: [3] in the worst case, a hypothesis is a list of n training items and the computational complexity of classifying a single new instance is O(n). One advantage that ...
In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once.
The cross-entropy (CE) method is a Monte Carlo method for importance sampling and optimization. It is applicable to both combinatorial and continuous problems, with either a static or noisy objective. The method approximates the optimal importance sampling estimator by repeating two phases: [1] Draw a sample from a probability distribution.
The norm (see also Norms) can be used to approximate the optimal norm via convex relaxation. It can be shown that the L 1 {\displaystyle L_{1}} norm induces sparsity. In the case of least squares, this problem is known as LASSO in statistics and basis pursuit in signal processing.
Instance selection (or dataset reduction, or dataset condensation) is an important data pre-processing step that can be applied in many machine learning (or data mining) tasks. [1] Approaches for instance selection can be applied for reducing the original dataset to a manageable volume, leading to a reduction of the computational resources that ...
A former Tennessee teacher who got pregnant after raping a 12-year-old boy pleaded guilty and has been sentenced to 25 years in prison with no parole. On Dec. 20, Alissa McCommon, 39, of Covington ...
The actual term multi-instance learning was introduced in the middle of the 1990s, by Dietterich et al. while they were investigating the problem of drug activity prediction. [3] They tried to create a learning system that could predict whether new molecule was qualified to make some drug, or not, through analyzing a collection of known molecules.