Byzantine armyThe Byzantine army was the primary military body of the Byzantine armed forces, serving alongside the Byzantine navy. A direct continuation of the Eastern Roman army, shaping and developing itself on the legacy of the late Hellenistic armies, it maintained a similar level of discipline, strategic prowess and organization. It was among the most effective armies of western Eurasia for much of the Middle Ages. Over time the cavalry arm became more prominent in the Byzantine army as the legion system disappeared in the early 7th century.
Internet protocol suiteThe Internet protocol suite, commonly known as TCP/IP, is a framework for organizing the set of communication protocols used in the Internet and similar computer networks according to functional criteria. The foundational protocols in the suite are the Transmission Control Protocol (TCP), the User Datagram Protocol (UDP), and the Internet Protocol (IP). Early versions of this networking model were known as the Department of Defense (DoD) model because the research and development were funded by the United States Department of Defense through DARPA.
Artificial neural networkArtificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.
Byzantine EmpireThe Byzantine Empire, also referred to as the Eastern Roman Empire, was the continuation of the Roman Empire primarily in its eastern provinces during Late Antiquity and the Middle Ages, when its capital city was Constantinople. It survived the fall of the Western Roman Empire in the 5th century AD and continued to exist until the fall of Constantinople to the Ottoman Empire in 1453. During most of its existence, the empire remained the most powerful economic, cultural, and military force in the Mediterranean world.
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.
Rectifier (neural networks)In the context of artificial neural networks, the rectifier or ReLU (rectified linear unit) activation function is an activation function defined as the positive part of its argument: where x is the input to a neuron. This is also known as a ramp function and is analogous to half-wave rectification in electrical engineering. This activation function was introduced by Kunihiko Fukushima in 1969 in the context of visual feature extraction in hierarchical neural networks.
Convolutional neural networkConvolutional neural network (CNN) is a regularized type of feed-forward neural network that learns feature engineering by itself via filters (or kernel) optimization. Vanishing gradients and exploding gradients, seen during backpropagation in earlier neural networks, are prevented by using regularized weights over fewer connections. For example, for each neuron in the fully-connected layer 10,000 weights would be required for processing an image sized 100 × 100 pixels.
Generative adversarial networkA generative adversarial network (GAN) is a class of machine learning framework and a prominent framework for approaching generative AI. The concept was initially developed by Ian Goodfellow and his colleagues in June 2014. In a GAN, two neural networks contest with each other in the form of a zero-sum game, where one agent's gain is another agent's loss. Given a training set, this technique learns to generate new data with the same statistics as the training set.
Communication protocolA communication protocol is a system of rules that allows two or more entities of a communications system to transmit information via any variation of a physical quantity. The protocol defines the rules, syntax, semantics, and synchronization of communication and possible error recovery methods. Protocols may be implemented by hardware, software, or a combination of both. Communicating systems use well-defined formats for exchanging various messages.
Byzantine Empire under the Komnenos dynastyThe Byzantine Empire was ruled by emperors of the Komnenos dynasty for a period of 104 years, from 1081 to about 1185. The Komnenian (also spelled Comnenian) period comprises the reigns of five emperors, Alexios I, John II, Manuel I, Alexios II and Andronikos I. It was a period of sustained, though ultimately incomplete, restoration of the military, territorial, economic and political position of the Byzantine Empire.
Deep learningDeep learning is part of a broader family of machine learning methods, which is based on artificial neural networks with representation learning. The adjective "deep" in deep learning refers to the use of multiple layers in the network. Methods used can be either supervised, semi-supervised or unsupervised.
Variational autoencoderIn machine learning, a variational autoencoder (VAE) is an artificial neural network architecture introduced by Diederik P. Kingma and Max Welling. It is part of the families of probabilistic graphical models and variational Bayesian methods. Variational autoencoders are often associated with the autoencoder model because of its architectural affinity, but with significant differences in the goal and mathematical formulation. Variational autoencoders are probabilistic generative models that require neural networks as only a part of their overall structure.
Adversarial machine learningAdversarial machine learning is the study of the attacks on machine learning algorithms, and of the defenses against such attacks. A survey from May 2020 exposes the fact that practitioners report a dire need for better protecting machine learning systems in industrial applications. To understand, note that most machine learning techniques are mostly designed to work on specific problem sets, under the assumption that the training and test data are generated from the same statistical distribution (IID).
Byzantine IconoclasmThe Byzantine Iconoclasm (Eikonomachía) were two periods in the history of the Byzantine Empire when the use of s or icons was opposed by religious and imperial authorities within the Ecumenical Patriarchate (at the time still comprising the Roman-Latin and the Eastern-Orthodox traditions) and the temporal imperial hierarchy. The First Iconoclasm, as it is sometimes called, occurred between about 726 and 787, while the Second Iconoclasm occurred between 814 and 842.
Transmission Control ProtocolThe Transmission Control Protocol (TCP) is one of the main protocols of the Internet protocol suite. It originated in the initial network implementation in which it complemented the Internet Protocol (IP). Therefore, the entire suite is commonly referred to as TCP/IP. TCP provides reliable, ordered, and error-checked delivery of a stream of octets (bytes) between applications running on hosts communicating via an IP network. Major internet applications such as the World Wide Web, email, remote administration, and rely on TCP, which is part of the Transport Layer of the TCP/IP suite.
Culture of GreeceThe culture of Greece has evolved over thousands of years, beginning in Minoan and later in Mycenaean Greece, continuing most notably into Classical Greece, while influencing the Roman Empire and its successor the Byzantine Empire. Other cultures and states such as the Frankish states, the Ottoman Empire, the Venetian Republic and Bavarian and Danish monarchies have also left their influence on modern Greek culture, but historians credit the Greek War of Independence and democracy.
BufferbloatBufferbloat is a cause of high latency and jitter in packet-switched networks caused by excess buffering of packets. Bufferbloat can also cause packet delay variation (also known as jitter), as well as reduce the overall network throughput. When a router or switch is configured to use excessively large buffers, even very high-speed networks can become practically unusable for many interactive applications like voice over IP (VoIP), audio streaming, online gaming, and even ordinary web browsing.
AlbaniansThe Albanians (ælˈbɛɪniənz; Shqiptarët ʃcipˈtaɾət) are an ethnic group native to the Balkan Peninsula who share a common Albanian ancestry, culture, history and language. They primarily live in Albania, Kosovo, North Macedonia, Montenegro, Serbia as well as in Croatia, Greece, Italy and Turkey. They also constitute a large diaspora with several communities established across Europe, the Americas and Oceania. Albanians have Paleo-Balkanic origins.
Byzantine faultA Byzantine fault (also Byzantine generals problem, interactive consistency, source congruency, error avalanche, Byzantine agreement problem, and Byzantine failure) is a condition of a computer system, particularly distributed computing systems, where components may fail and there is imperfect information on whether a component has failed. The term takes its name from an allegory, the "Byzantine generals problem", developed to describe a situation in which, to avoid catastrophic failure of the system, the system's actors must agree on a concerted strategy, but some of these actors are unreliable.
Consensus (computer science)A fundamental problem in distributed computing and multi-agent systems is to achieve overall system reliability in the presence of a number of faulty processes. This often requires coordinating processes to reach consensus, or agree on some data value that is needed during computation. Example applications of consensus include agreeing on what transactions to commit to a database in which order, state machine replication, and atomic broadcasts.
