Principal component analysisPrincipal component analysis (PCA) is a popular technique for analyzing large datasets containing a high number of dimensions/features per observation, increasing the interpretability of data while preserving the maximum amount of information, and enabling the visualization of multidimensional data. Formally, PCA is a statistical technique for reducing the dimensionality of a dataset. This is accomplished by linearly transforming the data into a new coordinate system where (most of) the variation in the data can be described with fewer dimensions than the initial data.
Independent component analysisIn signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents. This is done by assuming that at most one subcomponent is Gaussian and that the subcomponents are statistically independent from each other. ICA is a special case of blind source separation. A common example application is the "cocktail party problem" of listening in on one person's speech in a noisy room.
Quantities of informationThe mathematical theory of information is based on probability theory and statistics, and measures information with several quantities of information. The choice of logarithmic base in the following formulae determines the unit of information entropy that is used. The most common unit of information is the bit, or more correctly the shannon, based on the binary logarithm.
Feedforward neural networkA feedforward neural network (FNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. Its flow is uni-directional, meaning that the information in the model flows in only one direction—forward—from the input nodes, through the hidden nodes (if any) and to the output nodes, without any cycles or loops, in contrast to recurrent neural networks, which have a bi-directional flow.
TibiaThe tibia (ˈtɪbiə; : tibiae ˈtɪbii or tibias), also known as the shinbone or shankbone, is the larger, stronger, and anterior (frontal) of the two bones in the leg below the knee in vertebrates (the other being the fibula, behind and to the outside of the tibia); it connects the knee with the ankle. The tibia is found on the medial side of the leg next to the fibula and closer to the median plane. The tibia is connected to the fibula by the interosseous membrane of leg, forming a type of fibrous joint called a syndesmosis with very little movement.
Weak supervisionWeak supervision, also called semi-supervised learning, is a paradigm in machine learning, the relevance and notability of which increased with the advent of large language models due to large amount of data required to train them. It is characterized by using a combination of a small amount of human-labeled data (exclusively used in more expensive and time-consuming supervised learning paradigm), followed by a large amount of unlabeled data (used exclusively in unsupervised learning paradigm).
Limb (anatomy)A limb is a jointed, muscled appendage of a tetrapod vertebrate animal used for weight-bearing and terrestrial locomotion. The distalmost portion of a limb is known as its extremity. The limbs' bony endoskeleton, known as the appendicular skeleton, is homologous among all tetrapods, who use their limbs for walking, running and jumping, swimming, grasping and climbing. All tetrapods have four limbs that are organized into two bilaterally symmetrical pairs, with one pair at each end of the torso, which phylogenetrically correspond to the four paired fins (pectoral and pelvic fins) of their fish ancestors.
HumerusThe humerus (ˈhjuːmərəs; : humeri) is a long bone in the arm that runs from the shoulder to the elbow. It connects the scapula and the two bones of the lower arm, the radius and ulna, and consists of three sections. The humeral upper extremity consists of a rounded head, a narrow neck, and two short processes (tubercles, sometimes called tuberosities). The body is cylindrical in its upper portion, and more prismatic below. The lower extremity consists of 2 epicondyles, 2 processes (trochlea & capitulum), and 3 fossae (radial fossa, coronoid fossa, and olecranon fossa).
Self-supervised learningSelf-supervised learning (SSL) is a paradigm in machine learning for processing data of lower quality, rather than improving ultimate outcomes. Self-supervised learning more closely imitates the way humans learn to classify objects. The typical SSL method is based on an artificial neural network or other model such as a decision list. The model learns in two steps. First, the task is solved based on an auxiliary or pretext classification task using pseudo-labels which help to initialize the model parameters.
UlnaThe ulna or ulnal bone (: ulnae or ulnas) is a long bone found in the forearm that stretches from the elbow to the wrist, and when in anatomical position, is found on the medial side of the forearm. That is, the ulna is on the same side of the forearm as the little finger. It runs parallel to the radius, the other long bone in the forearm. The ulna is longer and the radius is shorter, but the radius is thicker and the ulna is thinner. Therefore, the ulna is considered to be the smaller bone of the two bones in the lower arm.
