Markov chainA Markov chain or Markov process is a stochastic model describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event. Informally, this may be thought of as, "What happens next depends only on the state of affairs now." A countably infinite sequence, in which the chain moves state at discrete time steps, gives a discrete-time Markov chain (DTMC). A continuous-time process is called a continuous-time Markov chain (CTMC).
Recurrent neural networkA recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. In contrast to uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. Their ability to use internal state (memory) to process arbitrary sequences of inputs makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.
Yamato periodThe Yamato period is the period of Japanese history when the Imperial court ruled from modern-day Nara Prefecture, then known as Yamato Province. While conventionally assigned to the period 250–710, including both the Kofun period (250–538) and the Asuka period (538–710), the actual start of Yamato rule is disputed. The Yamato court's supremacy was challenged during the Kofun period by other polities centered in various parts of Japan. What is certain is that Yamato clans had major advantages over their neighbouring clans in the 6th century.
Uruk periodThe Uruk period (ca. 4000 to 3100 BC; also known as Protoliterate period) existed from the protohistoric Chalcolithic to Early Bronze Age period in the history of Mesopotamia, after the Ubaid period and before the Jemdet Nasr period. Named after the Sumerian city of Uruk, this period saw the emergence of urban life in Mesopotamia and the Sumerian civilization. The late Uruk period (34th to 32nd centuries) saw the gradual emergence of the cuneiform script and corresponds to the Early Bronze Age; it has also been described as the "Protoliterate period".
Markov modelIn probability theory, a Markov model is a stochastic model used to model pseudo-randomly changing systems. It is assumed that future states depend only on the current state, not on the events that occurred before it (that is, it assumes the Markov property). Generally, this assumption enables reasoning and computation with the model that would otherwise be intractable. For this reason, in the fields of predictive modelling and probabilistic forecasting, it is desirable for a given model to exhibit the Markov property.
Ubaid periodThe Ubaid period (c. 5500–3700 BC) is a prehistoric period of Mesopotamia. The name derives from Tell al-'Ubaid where the earliest large excavation of Ubaid period material was conducted initially in 1919 by Henry Hall and later by Leonard Woolley. In South Mesopotamia the period is the earliest known period on the alluvial plain although it is likely earlier periods exist obscured under the alluvium. In the south it has a very long duration between about 5500 and 3800 BC when it is replaced by the Uruk period.
Kofun periodThe Kofun period is an era in the history of Japan from about 300 to 538 AD (the date of the introduction of Buddhism), following the Yayoi period. The Kofun and the subsequent Asuka periods are sometimes collectively called the Yamato period. This period is the earliest era of recorded history in Japan, but studies depend heavily on archaeology since the chronology of historical sources tends to be distorted. The word kofun is Japanese for the type of burial mound dating from this era. It was a period of cultural import.
Markov propertyIn probability theory and statistics, the term Markov property refers to the memoryless property of a stochastic process, which means that its future evolution is independent of its history. It is named after the Russian mathematician Andrey Markov. The term strong Markov property is similar to the Markov property, except that the meaning of "present" is defined in terms of a random variable known as a stopping time. The term Markov assumption is used to describe a model where the Markov property is assumed to hold, such as a hidden Markov model.
Multiple unitA multiple-unit train or simply multiple unit (MU) is a self-propelled train composed of one or more carriages joined together, which when coupled to another multiple unit can be controlled by a single driver, with multiple-unit train control. Although multiple units consist of several carriages, single self-propelled carriages – also called railcars, rail motor coaches or railbuses – are in fact multiple-units when two or more of them are working connected through multiple-unit train control (regardless if passengers can walk between the units or not).
Hidden Markov modelA hidden Markov model (HMM) is a statistical Markov model in which the system being modeled is assumed to be a Markov process — call it — with unobservable ("hidden") states. As part of the definition, HMM requires that there be an observable process whose outcomes are "influenced" by the outcomes of in a known way.
Reservoir computingReservoir computing is a framework for computation derived from recurrent neural network theory that maps input signals into higher dimensional computational spaces through the dynamics of a fixed, non-linear system called a reservoir. After the input signal is fed into the reservoir, which is treated as a "black box," a simple readout mechanism is trained to read the state of the reservoir and map it to the desired output. The first key benefit of this framework is that training is performed only at the readout stage, as the reservoir dynamics are fixed.
ManA man is an adult male human. Prior to adulthood, a male human is referred to as a boy (a male child or adolescent). Like most other male mammals, a man's genome usually inherits an X chromosome from the mother and a Y chromosome from the father. Sex differentiation of the male fetus is governed by the SRY gene on the Y chromosome. During puberty, hormones which stimulate androgen production result in the development of secondary sexual characteristics, thus exhibiting greater differences between the sexes.
Vanishing gradient problemIn machine learning, the vanishing gradient problem is encountered when training artificial neural networks with gradient-based learning methods and backpropagation. In such methods, during each iteration of training each of the neural networks weights receives an update proportional to the partial derivative of the error function with respect to the current weight. The problem is that in some cases, the gradient will be vanishingly small, effectively preventing the weight from changing its value.
Diesel multiple unitA diesel multiple unit or DMU is a multiple-unit train powered by on-board diesel engines. A DMU requires no separate locomotive, as the engines are incorporated into one or more of the carriages. Diesel-powered single-unit railcars are also generally classed as DMUs. Diesel-powered units may be further classified by their transmission type: diesel–mechanical DMMU, diesel–hydraulic DHMU, or diesel–electric DEMU. The diesel engine may be located above the frame in an engine bay or under the floor.
Electric multiple unitAn electric multiple unit or EMU is a multiple-unit train consisting of self-propelled carriages using electricity as the motive power. An EMU requires no separate locomotive, as electric traction motors are incorporated within one or a number of the carriages. An EMU is usually formed of two or more semi-permanently coupled carriages, but electrically powered single-unit railcars are also generally classed as EMUs. The great majority of EMUs are passenger trains, but versions also exist for carrying mail.
Attention (machine learning)Machine learning-based attention is a mechanism mimicking cognitive attention. It calculates "soft" weights for each word, more precisely for its embedding, in the context window. It can do it either in parallel (such as in transformers) or sequentially (such as recursive neural networks). "Soft" weights can change during each runtime, in contrast to "hard" weights, which are (pre-)trained and fine-tuned and remain frozen afterwards. Multiple attention heads are used in transformer-based large language models.
Discrete-time Fourier transformIn mathematics, the discrete-time Fourier transform (DTFT), also called the finite Fourier transform, is a form of Fourier analysis that is applicable to a sequence of values. The DTFT is often used to analyze samples of a continuous function. The term discrete-time refers to the fact that the transform operates on discrete data, often samples whose interval has units of time. From uniformly spaced samples it produces a function of frequency that is a periodic summation of the continuous Fourier transform of the original continuous function.
Discrete time and continuous timeIn mathematical dynamics, discrete time and continuous time are two alternative frameworks within which variables that evolve over time are modeled. Discrete time views values of variables as occurring at distinct, separate "points in time", or equivalently as being unchanged throughout each non-zero region of time ("time period")—that is, time is viewed as a discrete variable. Thus a non-time variable jumps from one value to another as time moves from one time period to the next.
Violence against menViolence against men is a term for violent acts that are disproportionately or exclusively committed against men or boys. Men are over-represented as both victims and perpetrators of violence. Studies of social attitudes show violence is perceived as more or less serious depending on the gender of victim and perpetrator. People are less likely to report a man hitting another man to the police than a man hitting a woman. Male law enforcement officers show a greater reluctance to file charges or reports when a man is the victim of domestic violence.
Discrete mathematicsDiscrete mathematics is the study of mathematical structures that can be considered "discrete" (in a way analogous to discrete variables, having a bijection with the set of natural numbers) rather than "continuous" (analogously to continuous functions). Objects studied in discrete mathematics include integers, graphs, and statements in logic. By contrast, discrete mathematics excludes topics in "continuous mathematics" such as real numbers, calculus or Euclidean geometry.
