Machine learningMachine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms. Recently, generative artificial neural networks have been able to surpass results of many previous approaches.
LearningLearning is the process of acquiring new understanding, knowledge, behaviors, skills, values, attitudes, and preferences. The ability to learn is possessed by humans, animals, and some machines; there is also evidence for some kind of learning in certain plants. Some learning is immediate, induced by a single event (e.g. being burned by a hot stove), but much skill and knowledge accumulate from repeated experiences. The changes induced by learning often last a lifetime, and it is hard to distinguish learned material that seems to be "lost" from that which cannot be retrieved.
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.
Computational resourceIn computational complexity theory, a computational resource is a resource used by some computational models in the solution of computational problems. The simplest computational resources are computation time, the number of steps necessary to solve a problem, and memory space, the amount of storage needed while solving the problem, but many more complicated resources have been defined. A computational problem is generally defined in terms of its action on any valid input.
Computational complexityIn computer science, the computational complexity or simply complexity of an algorithm is the amount of resources required to run it. Particular focus is given to computation time (generally measured by the number of needed elementary operations) and memory storage requirements. The complexity of a problem is the complexity of the best algorithms that allow solving the problem. The study of the complexity of explicitly given algorithms is called analysis of algorithms, while the study of the complexity of problems is called computational complexity theory.
PeloponneseThe Peloponnese (ˌpɛləpəˈniːz,_-ˈniːs), Peloponnesus (ˌpɛləpəˈniːsəs; Pelopónnēsos, peloˈponisos), or Morea is a peninsula and geographic region in southern Greece. It is connected to the central part of the country by the Isthmus of Corinth land bridge which separates the Gulf of Corinth from the Saronic Gulf. From the late Middle Ages until the 19th century, the peninsula was known as the Morea (Μωρέας, Morèas), a name still in colloquial use in its demotic form (Μωριάς, Moriàs).
Experiential learningExperiential learning (ExL) is the process of learning through experience, and is more narrowly defined as "learning through reflection on doing". Hands-on learning can be a form of experiential learning, but does not necessarily involve students reflecting on their product. Experiential learning is distinct from rote or didactic learning, in which the learner plays a comparatively passive role. It is related to, but not synonymous with, other forms of active learning such as action learning, adventure learning, free-choice learning, cooperative learning, service-learning, and situated learning.
Reinforcement learningReinforcement learning (RL) is an area of machine learning concerned with how intelligent agents ought to take actions in an environment in order to maximize the notion of cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Reinforcement learning differs from supervised learning in not needing labelled input/output pairs to be presented, and in not needing sub-optimal actions to be explicitly corrected.
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).
Computational complexity theoryIn theoretical computer science and mathematics, computational complexity theory focuses on classifying computational problems according to their resource usage, and relating these classes to each other. A computational problem is a task solved by a computer. A computation problem is solvable by mechanical application of mathematical steps, such as an algorithm. A problem is regarded as inherently difficult if its solution requires significant resources, whatever the algorithm used.
Computational problemIn theoretical computer science, a computational problem is a problem that may be solved by an algorithm. For example, the problem of factoring "Given a positive integer n, find a nontrivial prime factor of n." is a computational problem. A computational problem can be viewed as a set of instances or cases together with a, possibly empty, set of solutions for every instance/case. For example, in the factoring problem, the instances are the integers n, and solutions are prime numbers p that are the nontrivial prime factors of n.
Hagia SophiaHagia Sophia ( 'Holy Wisdom'; Ayasofya; Hagía Sophía; Sancta Sapientia), officially the Hagia Sophia Mosque (Ayasofya-i Kebir Cami-i Şerifi), is a mosque and a major cultural and historical site in Istanbul, Turkey. The last of three church buildings to be successively erected on the site by the Eastern Roman Empire, it was completed in 537 AD. It was an Orthodox church until the Ottoman conquest of Constantinople in 1453, then a mosque until 1935, then a museum and then from 2020 a mosque again, as well as being a Roman Catholic cathedral for some decades after the Fourth Crusade of 1204.
ThessalonikiThessaloniki (ˌθɛsələˈniːki Θεσσαλονίκη, θesaloˈnici), also known as Thessalonica (ˌθɛsələ'naikə,_ˌθɛsəˈlɒnɪkə), Saloniki, Salonika, or Salonica (səˈlɒnɪkə,_ˌsæləˈniːkə ), is the second-largest city in Greece, with slightly over one million inhabitants in its metropolitan area, and the capital of the geographic region of Macedonia, the administrative region of Central Macedonia and the Decentralized Administration of Macedonia and Thrace.
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.
ArchitectureArchitecture is the art and technique of designing and building, as distinguished from the skills associated with construction. It is both the process and the product of sketching, conceiving, planning, designing, and constructing buildings or other structures. The term comes ; ; . Architectural works, in the material form of buildings, are often perceived as cultural symbols and as works of art. Historical civilizations are often identified with their surviving architectural achievements.
Learning spaceLearning space or learning setting refers to a physical setting for a learning environment, a place in which teaching and learning occur. The term is commonly used as a more definitive alternative to "classroom," but it may also refer to an indoor or outdoor location, either actual or virtual. Learning spaces are highly diverse in use, configuration, location, and educational institution. They support a variety of pedagogies, including quiet study, passive or active learning, kinesthetic or physical learning, vocational learning, experiential learning, and others.
VeniceVenice (ˈvɛnᵻs ; Venezia veˈnɛttsja; Venesia veˈnɛsja, outdatedly Venexia veˈnɛzja) is a city in northeastern Italy and the capital of the Veneto region. It is built on a group of 118 small islands that are separated by expanses of open water and by canals; portions of the city are linked by over 400 bridges. The islands are in the shallow Venetian Lagoon, an enclosed bay lying between the mouths of the Po and the Piave rivers (more exactly between the Brenta and the Sile).
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.
Feature learningIn machine learning, feature learning or representation learning is a set of techniques that allows a system to automatically discover the representations needed for feature detection or classification from raw data. This replaces manual feature engineering and allows a machine to both learn the features and use them to perform a specific task. Feature learning is motivated by the fact that machine learning tasks such as classification often require input that is mathematically and computationally convenient to process.
Learning theory (education)Learning theory describes how students receive, process, and retain knowledge during learning. Cognitive, emotional, and environmental influences, as well as prior experience, all play a part in how understanding, or a worldview, is acquired or changed and knowledge and skills retained. Behaviorists look at learning as an aspect of conditioning and advocate a system of rewards and targets in education.
