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A residual neural network (also referred to as a residual network or ResNet) [1] is a deep learning architecture in which the layers learn residual functions with reference to the layer inputs. It was developed in 2015 for image recognition , and won the ImageNet Large Scale Visual Recognition Challenge ( ILSVRC ) of that year.
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In statistics, the restricted (or residual, or reduced) maximum likelihood (REML) approach is a particular form of maximum likelihood estimation that does not base estimates on a maximum likelihood fit of all the information, but instead uses a likelihood function calculated from a transformed set of data, so that nuisance parameters have no effect.
TD-Lambda is a learning algorithm invented by Richard S. Sutton based on earlier work on temporal difference learning by Arthur Samuel. [11] This algorithm was famously applied by Gerald Tesauro to create TD-Gammon, a program that learned to play the game of backgammon at the level of expert human players.
The spaces of multivariate functions that can be implemented by a network are determined by the structure of the network, the set of simple functions, and its multiplicative parameters. A great deal of theoretical work has gone into characterizing these function spaces. Most universal approximation theorems are in one of two classes.
A Canadian woman allegedly attempted to smuggle 22 pounds of methamphetamine wrapped as Christmas presents through a New Zealand airport on Sunday, Dec. 8.
In the early morning hours of Dec. 26, 1996, Patsy Ramsey called 911 to report her 6-year-old daughter JonBenét missing, and found a rambling ransom note left inside their Boulder, Colorado, home.
The Dallas Stars have been hit with a hefty fine by the NHL after they violated the Collective Bargaining Agreement between the NHLPA and the league by holding an optional practice last week ...