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Tetramethyl acetyloctahydronaphthalenes-Chemical Summary-OTNE is the abbreviation for the fragrance material with Chemical Abstract Service (CAS) numbers 68155-66-8, 54464-57-2 and 68155-67-9 and EC List number 915-730-3. It is a multi-constituent isomer mixture containing: 1-(1,2,3,4,5,6,7,8-octahydro-2,3,8,8-tetramet... | milkshake721/2.1M-wiki-STEM |
Tetramethyl acetyloctahydronaphthalenes-Physical-chemical properties-OTNE is a clear yellow liquid at 20 °C. Its melting point is below −20 °C at atmospheric pressure, and its boiling point is determined to be at around 290 °C (modified OECD 103 method). All physicochemical data have been obtained from the OTNE REACH r... | milkshake721/2.1M-wiki-STEM |
Tetramethyl acetyloctahydronaphthalenes-Safety-Iso E Super may cause allergic reactions detectable by patch tests in humans and chronic exposure to Iso E Super from perfumes may result in permanent hypersensitivity. In a study with female mice, Iso E Super was positive in the local lymph node assay (LLNA) and irritancy... | milkshake721/2.1M-wiki-STEM |
Tetramethyl acetyloctahydronaphthalenes-Environmental data-OTNE is classified as H410 Very toxic to aquatic life with long-lasting effects (EU-CLP) or R51/53 Toxic to aquatic organisms, may cause long-term adverse effects in the aquatic environment (EU DSD).
The biodegradation of OTNE in fresh water (T1/2) is at most 4... | milkshake721/2.1M-wiki-STEM |
Tetramethyl acetyloctahydronaphthalenes-Regulatory status-OTNE is registered on all major chemical inventories (US, Japan, China, Korea, Philippines, and Australia) and has been EU REACH registered in 2010. | milkshake721/2.1M-wiki-STEM |
Tetramethyl acetyloctahydronaphthalenes-Regulatory status-In 2014 the US National Toxicology Program (NTP) conducted a 13-week repeat dose toxicity study and found no adverse effects.OTNE has been recommended for inclusion in an update for the EU Fragrance Allergens labelling for cosmetic products based on a small numb... | milkshake721/2.1M-wiki-STEM |
Tetramethyl acetyloctahydronaphthalenes-Commercial products-The fragrance Molecule 01 (Escentric Molecules, 2005) is a specific isomer of Iso E Super, by the company IFF. Its partner fragrance Escentric 01 contains Iso E Super along with ambroxan, pink pepper, green lime with balsamic notes like benzoin mastic and ince... | milkshake721/2.1M-wiki-STEM |
Tetramethyl acetyloctahydronaphthalenes-History-OTNE was patented in 1975 as an invention of International Flavors and Fragrances. | milkshake721/2.1M-wiki-STEM |
Bromoxylene-Bromoxylene-A bromoxylene is an aromatic compound containing a benzene ring linked with two methyl groups, and a bromine atom. There are several isomers. | milkshake721/2.1M-wiki-STEM |
Phaclofen-Phaclofen-Phaclofen, or phosphonobaclofen, is a selective antagonist for the GABAB receptor. It was the first selective GABAB antagonist discovered, but its utility was limited by the fact that it does not cross the blood brain barrier. | milkshake721/2.1M-wiki-STEM |
Dernford Fen-Dernford Fen-Dernford Fen is a 10.3-hectare (25-acre) biological Site of Special Scientific Interest north-west of Sawston in Cambridgeshire.The site is a rare surviving example of rough fen and carr. Other habitats are dry grassland and scrub, together with ditches and a chalk stream. There are breeding w... | milkshake721/2.1M-wiki-STEM |
Operator associativity-Operator associativity-In programming language theory, the associativity of an operator is a property that determines how operators of the same precedence are grouped in the absence of parentheses. If an operand is both preceded and followed by operators (for example, ^ 3 ^), and those operators ... | milkshake721/2.1M-wiki-STEM |
Operator associativity-Operator associativity-Consider the expression a ~ b ~ c. If the operator ~ has left associativity, this expression would be interpreted as (a ~ b) ~ c. If the operator has right associativity, the expression would be interpreted as a ~ (b ~ c). If the operator is non-associative, the expression ... | milkshake721/2.1M-wiki-STEM |
Operator associativity-Operator associativity-Many programming language manuals provide a table of operator precedence and associativity; see, for example, the table for C and C++. | milkshake721/2.1M-wiki-STEM |
Operator associativity-Operator associativity-The concept of notational associativity described here is related to, but different from, the mathematical associativity. An operation that is mathematically associative, by definition requires no notational associativity. (For example, addition has the associative property... | milkshake721/2.1M-wiki-STEM |
Operator associativity-Examples-Associativity is only needed when the operators in an expression have the same precedence. Usually + and - have the same precedence. Consider the expression 7 - 4 + 2. The result could be either (7 - 4) + 2 = 5 or 7 - (4 + 2) = 1. The former result corresponds to the case when + and - ar... | milkshake721/2.1M-wiki-STEM |
Operator associativity-Examples-In order to reflect normal usage, addition, subtraction, multiplication, and division operators are usually left-associative, while for an exponentiation operator (if present) and Knuth's up-arrow operators there is no general agreement. Any assignment operators are typically right-assoc... | milkshake721/2.1M-wiki-STEM |
Operator associativity-Examples-A detailed example Consider the expression 5^4^3^2, in which ^ is taken to be a right-associative exponentiation operator. A parser reading the tokens from left to right would apply the associativity rule to a branch, because of the right-associativity of ^, in the following way: Term 5 ... | milkshake721/2.1M-wiki-STEM |
Operator associativity-Right-associativity of assignment operators-In many imperative programming languages, the assignment operator is defined to be right-associative, and assignment is defined to be an expression (which evaluates to a value), not just a statement. This allows chained assignment by using the value of ... | milkshake721/2.1M-wiki-STEM |
Operator associativity-Right-associativity of assignment operators-In C, the assignment a = b is an expression that evaluates to the same value as the expression b converted to the type of a, with the side effect of storing the R-value of b into the L-value of a. Therefore the expression a = (b = c) can be interpreted ... | milkshake721/2.1M-wiki-STEM |
Operator associativity-Right-associativity of assignment operators-In C++, the assignment a = b is an expression that evaluates to the same value as the expression a, with the side effect of storing the R-value of b into the L-value of a. Therefore the expression a = (b = c) can still be interpreted as b = c; a = b;. A... | milkshake721/2.1M-wiki-STEM |
Operator associativity-Non-associative operators-Non-associative operators are operators that have no defined behavior when used in sequence in an expression. In Prolog the infix operator :- is non-associative because constructs such as "a :- b :- c" constitute syntax errors. | milkshake721/2.1M-wiki-STEM |
Operator associativity-Non-associative operators-Another possibility is that sequences of certain operators are interpreted in some other way, which cannot be expressed as associativity. This generally means that syntactically, there is a special rule for sequences of these operations, and semantically the behavior is ... | milkshake721/2.1M-wiki-STEM |
Calligra Words-Calligra Words-Calligra Words is a word processor, which is part of Calligra Suite and developed by KDE as free software. | milkshake721/2.1M-wiki-STEM |
Calligra Words-History-When the Calligra Suite was formed, unlike the other Calligra applications Words was not a continuation of the corresponding KOffice application – KWord. The Words was largely written from scratch – in May 2011 a completely new layout engine was announced. The first release was made available on ... | milkshake721/2.1M-wiki-STEM |
Calligra Words-Reception-Initial reception of Calligra Words shortly after the 2.4 release was mixed. While Linux Pro Magazine Online's Bruce Byfield wrote “Calligra needed an impressive first release. Perhaps surprisingly, and to the development team’s credit, it has managed one in 2.4.”, he also noted that “Words in ... | milkshake721/2.1M-wiki-STEM |
Calligra Words-Formula editor-Formulas in Calligra Words are provided by the Formula plugin. It is a formula editor with a WYSIWYG interface. | milkshake721/2.1M-wiki-STEM |
Temporary equilibrium method-Temporary equilibrium method-The temporary equilibrium method has been devised by Alfred Marshall for analyzing economic systems that comprise interdependent variables of different speed. Sometimes it is referred to as the moving equilibrium method. | milkshake721/2.1M-wiki-STEM |
Temporary equilibrium method-Temporary equilibrium method-For example, assume an industry with a certain capacity that produces a certain commodity. Given this capacity, the supply offered by the industry will depend on the prevailing price. The corresponding supply schedule gives short-run supply. The demand depends o... | milkshake721/2.1M-wiki-STEM |
Temporary equilibrium method-Temporary equilibrium method-In physics, the method is known as scale separation, | milkshake721/2.1M-wiki-STEM |
Undergrowth-Undergrowth-In forestry and ecology, understory (American English), or understorey (Commonwealth English), also known as underbrush or undergrowth, includes plant life growing beneath the forest canopy without penetrating it to any great extent, but above the forest floor. Only a small percentage of light p... | milkshake721/2.1M-wiki-STEM |
Undergrowth-Undergrowth-In temperate deciduous forests, many understory plants start into growth earlier in the year than the canopy trees, to make use of the greater availability of light at that particular time of year. A gap in the canopy caused by the death of a tree stimulates the potential emergent trees into com... | milkshake721/2.1M-wiki-STEM |
Undergrowth-Understory structure-The understory is the underlying layer of vegetation in a forest or wooded area, especially the trees and shrubs growing between the forest canopy and the forest floor. | milkshake721/2.1M-wiki-STEM |
Undergrowth-Understory structure-Plants in the understory comprise an assortment of seedlings and saplings of canopy trees together with specialist understory shrubs and herbs. Young canopy trees often persist in the understory for decades as suppressed juveniles until an opening in the forest overstory permits their g... | milkshake721/2.1M-wiki-STEM |
Undergrowth-Understory structure-The canopy of a tropical forests are typically about 10m thick, and intercepts around 95% of the sunlight. The understory therefore receives less intense light than plants in the canopy and such light as does penetrate is impoverished in wavelengths of light that are most effective for ... | milkshake721/2.1M-wiki-STEM |
Undergrowth-Understory structure-As a rule forest understories also experience higher humidity than exposed areas. The forest canopy reduces solar radiation, so the ground does not heat up or cool down as rapidly as open ground. Consequently, the understory dries out more slowly than more exposed areas do. The greater ... | milkshake721/2.1M-wiki-STEM |
Ventricular-brain ratio-Ventricular-brain ratio-Ventricular-brain ratio (VBR), also known as the ventricle-to-brain ratio or ventricle-brain ratio, is the ratio of total ventricle area to total brain area, which can be calculated with planimetry from brain imagining techniques such as CT scans. | milkshake721/2.1M-wiki-STEM |
Ventricular-brain ratio-Ventricular-brain ratio-It is a common measure of ventricular dilation or cerebral atrophy in patients with traumatic brain injury or hydrocephalus ex vacuo. VBR also tends to increase with age.Generally, a higher VBR means a worse prognosis for recovering from a brain injury. For example, VBR i... | milkshake721/2.1M-wiki-STEM |
Collaborative e-democracy-Collaborative e-democracy-Collaborative e-democracy refers to a hybrid democratic model combining elements of direct democracy, representative democracy, and e-democracy (or the incorporation of ICTs into democratic processes). This concept, first introduced at international academic conferenc... | milkshake721/2.1M-wiki-STEM |
Collaborative e-democracy-Theoretical Framework-Collaborative e-democracy encompasses the following theoretical components: Collaborative Democracy: A political framework where electors and elected officials actively collaborate to achieve optimal solutions using technologies that facilitate broad citizen participation... | milkshake721/2.1M-wiki-STEM |
Collaborative e-democracy-Theoretical Framework-Collaborative e-Policymaking (CPM): A software-facilitated, five-phase policy process in which citizens participate either directly or indirectly via proxy representatives. This process unfolds on a government-backed social networking site, with all citizens as members. E... | milkshake721/2.1M-wiki-STEM |
Collaborative e-democracy-Theoretical Framework-Proxy voting and Liquid Democracy: In a collaborative e-democracy, the system takes into account the limitations of direct democracy, where each citizen is expected to vote on every policy issue. Recognizing that this could impose an excessive burden, collaborative e-demo... | milkshake721/2.1M-wiki-STEM |
Collaborative e-democracy-Policy Process-Collaborative e-democracy engages various stakeholders such as affected individuals, domain experts, and parties capable of implementing solutions in the process of shaping public laws and policies. The cycle of each policy begins with the identification of a common issue or obj... | milkshake721/2.1M-wiki-STEM |
Collaborative e-democracy-Policy Process-Voting Phase: Based on the collectively created information, the group votes for the proposal perceived as the most optimal solution for the identified issue or goal. The outcome of this phase may result in the introduction of a new law or execution of a new government action. A... | milkshake721/2.1M-wiki-STEM |
Collaborative e-democracy-Principles-Collaborative e-democracy operates on several key principles: Self-government and Direct Democracy: Collaborative e-democracy is grounded in the ideal of self-governance and direct democracy. It embodies the ancient Roman law maxim, quod omnes tangit ab omnibus approbetur, which tra... | milkshake721/2.1M-wiki-STEM |
Collaborative e-democracy-Principles-Open source governance: This philosophy promotes the application of open source and open content principles to democracy, enabling any engaged citizen to contribute to policy creation.
Aggregation: The social networking platform plays a role in gathering citizens' opinions on differ... | milkshake721/2.1M-wiki-STEM |
Collaborative e-democracy-Principles-Collective Learning & Adoption: The direct democracy aspect of collaborative e-democracy shifts policymaking responsibility from government teams (top-down) to the citizen collective (bottom-up). The repercussions of their decisions initiate a collective learning process. Collaborat... | milkshake721/2.1M-wiki-STEM |
Collaborative e-democracy-Benefits and Limitations-Collaborative e-democracy aims to bring forth several benefits: Transparency and Accessibility: The CPM process aspires to provide transparency and make governmental operations accessible to all citizens via the internet.Political efficacy: Engaging citizens in governm... | milkshake721/2.1M-wiki-STEM |
Collaborative e-democracy-Research and Development-The concepts of collaborative e-democracy and collaborative e-policy-making were first introduced at two academic conferences on e-governance and e-democracy in 2009. The key presentations were: Petrik, Klaus (2009). “Participation and e-Democracy: How to Utilize Web 2... | milkshake721/2.1M-wiki-STEM |
Cadbury Creme Egg-Cadbury Creme Egg-A Cadbury Creme Egg, originally named Fry's Creme Egg, is a chocolate confection produced in the shape of an egg. It originated from the British chocolatier Fry's in 1963 before being renamed by Cadbury in 1971. The product consists of a thick chocolate shell containing a sweet white... | milkshake721/2.1M-wiki-STEM |
Cadbury Creme Egg-Cadbury Creme Egg-The confectionery is produced by Cadbury in the United Kingdom, by The Hershey Company in the United States, and by Cadbury Adams in Canada. | milkshake721/2.1M-wiki-STEM |
Cadbury Creme Egg-History-While filled eggs were first manufactured by the Cadbury Brothers in 1923, the Creme Egg in its current form was introduced in 1963. Initially sold as "Fry's Creme Eggs" (incorporating the Fry's brand, after the British chocolatier), they were renamed "Cadbury's Creme Eggs" in 1971. | milkshake721/2.1M-wiki-STEM |
Cadbury Creme Egg-Composition-Cadbury Creme Eggs are manufactured as two chocolate half shells, each of which is filled with a white fondant made from sugar, glucose syrup, inverted sugar syrup, dried egg white, and flavouring. The fondant in each half is topped with a smaller amount of the same mixture coloured yellow... | milkshake721/2.1M-wiki-STEM |
Cadbury Creme Egg-Manufacture and sales-Creme Eggs are produced by Cadbury in the United Kingdom, by The Hershey Company in the United States, and by Cadbury Adams in Canada. They are sold by Mondelez International in all markets except the US, where The Hershey Company has the local marketing rights. At the Bournville... | milkshake721/2.1M-wiki-STEM |
Cadbury Creme Egg-Manufacture and sales-Creme Eggs are available individually and in boxes, with the numbers of eggs per package varying per country. The foil wrapping of the eggs was traditionally pink, blue, purple, and yellow in the United Kingdom and Ireland, though green was removed and purple replaced blue early ... | milkshake721/2.1M-wiki-STEM |
Cadbury Creme Egg-Manufacture and sales-Creme Eggs are available annually between 1 January and Easter Sunday. In the UK in the 1980s, Cadbury made Creme Eggs available year-round but sales dropped and they returned to seasonal availability. In 2018, white chocolate versions of the Creme Eggs were made available. These... | milkshake721/2.1M-wiki-STEM |
Cadbury Creme Egg-Advertising-The Creme Egg has been marketed in the UK and Ireland with the question "How do you eat yours?" and in New Zealand with the slogan "Don't get caught with egg on your face". Australia and New Zealand have also used a variation of the UK question, using the slogan "How do you do it?"In the U... | milkshake721/2.1M-wiki-STEM |
Cadbury Creme Egg-Advertising-A similar advertising campaign in 2010 featured animated Creme Eggs destroying themselves in large numbers, such as gathering together at a cinema before bombarding into each other to release all of the eggs' goo, and another which featured eggs being destroyed by mouse traps.In Halloween ... | milkshake721/2.1M-wiki-STEM |
Cadbury Creme Egg-Advertising-Campaigns/slogans c. 1970s: "Shopkeeper" campaign in which a boy asks for 6000 Cadbury Creme Eggs "Irresistibly" campaign showing characters prepared to do something unusual for a Creme Egg, similar to the "What would you do for a Klondike bar?" campaign Early 1980s: "Can't Resist Them" ... | milkshake721/2.1M-wiki-STEM |
Cadbury Creme Egg-Advertising-Creme Egg Camp In 2018, Cadbury opened a pop-up camp. The camp in Last Days of Shoreditch, Old Street was open every Thursday to Sunday from 19 January, to 18 February 2018 | milkshake721/2.1M-wiki-STEM |
Cadbury Creme Egg-Varieties-Cadbury has introduced many variants to the original Creme Egg, including: Other products include: Creme Egg Fondant in a narrow cardboard tube (limited edition) Creme Egg ice cream with a fondant sauce in milk chocolate Creme Egg Pots Of Joy – melted Cadbury milk chocolate with a fondant la... | milkshake721/2.1M-wiki-STEM |
Cadbury Creme Egg-Varieties-Jaffa Egg – Manufactured in New Zealand, Dark chocolate with orange filling Marble Egg – Manufactured in New Zealand, Dairy Milk and Dream Chocolate swirled together | milkshake721/2.1M-wiki-STEM |
Fibrous tunic of eyeball-Fibrous tunic of eyeball-The sclera and cornea form the fibrous tunic of the bulb of the eye; the sclera is opaque, and constitutes the posterior five-sixths of the tunic; the cornea is transparent, and forms the anterior sixth.
The term "corneosclera" is also used to describe the sclera and co... | milkshake721/2.1M-wiki-STEM |
Noncommutative projective geometry-Noncommutative projective geometry-In mathematics, noncommutative projective geometry is a noncommutative analog of projective geometry in the setting of noncommutative algebraic geometry. | milkshake721/2.1M-wiki-STEM |
Noncommutative projective geometry-Examples-The quantum plane, the most basic example, is the quotient ring of the free ring: k⟨x,y⟩/(yx−qxy) More generally, the quantum polynomial ring is the quotient ring: k⟨x1,…,xn⟩/(xixj−qijxjxi) | milkshake721/2.1M-wiki-STEM |
Noncommutative projective geometry-Proj construction-By definition, the Proj of a graded ring R is the quotient category of the category of finitely generated graded modules over R by the subcategory of torsion modules. If R is a commutative Noetherian graded ring generated by degree-one elements, then the Proj of R in... | milkshake721/2.1M-wiki-STEM |
Federated learning-Federated learning-Federated learning (also known as collaborative learning) is a machine learning technique that trains an algorithm via multiple independent sessions, each using its own dataset. This approach stands in contrast to traditional centralized machine learning techniques where local data... | milkshake721/2.1M-wiki-STEM |
Federated learning-Federated learning-Federated learning enables multiple actors to build a common, robust machine learning model without sharing data, thus addressing critical issues such as data privacy, data security, data access rights and access to heterogeneous data. Its applications engage industries including d... | milkshake721/2.1M-wiki-STEM |
Federated learning-Definition-Federated learning aims at training a machine learning algorithm, for instance deep neural networks, on multiple local datasets contained in local nodes without explicitly exchanging data samples. The general principle consists in training local models on local data samples and exchanging ... | milkshake721/2.1M-wiki-STEM |
Federated learning-Definition-The main difference between federated learning and distributed learning lies in the assumptions made on the properties of the local datasets, as distributed learning originally aims at parallelizing computing power where federated learning originally aims at training on heterogeneous datas... | milkshake721/2.1M-wiki-STEM |
Federated learning-Definition-Mathematical formulation The objective function for federated learning is as follows: f(x1,…,xK)=1K∑i=1Kfi(xi) where K is the number of nodes, xi are the weights of model as viewed by node i , and fi is node i 's local objective function, which describes how model weights xi conforms... | milkshake721/2.1M-wiki-STEM |
Federated learning-Definition-Centralized federated learning In the centralized federated learning setting, a central server is used to orchestrate the different steps of the algorithms and coordinate all the participating nodes during the learning process. The server is responsible for the nodes selection at the begin... | milkshake721/2.1M-wiki-STEM |
Federated learning-Definition-Decentralized federated learning In the decentralized federated learning setting, the nodes are able to coordinate themselves to obtain the global model. This setup prevents single point failures as the model updates are exchanged only between interconnected nodes without the orchestration... | milkshake721/2.1M-wiki-STEM |
Federated learning-Definition-Heterogeneous federated learning An increasing number of application domains involve a large set of heterogeneous clients, e.g., mobile phones and IoT devices. Most of the existing Federated learning strategies assume that local models share the same global model architecture. Recently, a ... | milkshake721/2.1M-wiki-STEM |
Federated learning-Main features-Iterative learning To ensure good task performance of a final, central machine learning model, federated learning relies on an iterative process broken up into an atomic set of client-server interactions known as a federated learning round. Each round of this process consists in transmi... | milkshake721/2.1M-wiki-STEM |
Federated learning-Main features-Client selection: a fraction of local nodes are selected to start training on local data. The selected nodes acquire the current statistical model while the others wait for the next federated round.
Configuration: the central server orders selected nodes to undergo training of the model... | milkshake721/2.1M-wiki-STEM |
Federated learning-Main features-Termination: once a pre-defined termination criterion is met (e.g., a maximum number of iterations is reached or the model accuracy is greater than a threshold) the central server aggregates the updates and finalizes the global model.The procedure considered before assumes synchronized ... | milkshake721/2.1M-wiki-STEM |
Federated learning-Main features-Non-IID data In most cases, the assumption of independent and identically distributed samples across local nodes does not hold for federated learning setups. Under this setting, the performances of the training process may vary significantly according to the unbalanced local data sample... | milkshake721/2.1M-wiki-STEM |
Federated learning-Main features-This allows to decouple each contribution according to the specific distribution available at the local nodes.
The main categories for non-iid data can be summarized as follows: Covariate shift: local nodes may store examples that have different statistical distributions compared to oth... | milkshake721/2.1M-wiki-STEM |
Federated learning-Algorithmic hyper-parameters-Network topology The way the statistical local outputs are pooled and the way the nodes communicate with each other can change from the centralized model explained in the previous section. This leads to a variety of federated learning approaches: for instance no central o... | milkshake721/2.1M-wiki-STEM |
Federated learning-Algorithmic hyper-parameters-Federated learning parameters Once the topology of the node network is chosen, one can control different parameters of the federated learning process (in addition to the machine learning model's own hyperparameters) to optimize learning: Number of federated learning round... | milkshake721/2.1M-wiki-STEM |
Federated learning-Technical limitations-Federated learning requires frequent communication between nodes during the learning process. Thus, it requires not only enough local computing power and memory, but also high bandwidth connections to be able to exchange parameters of the machine learning model. However, the tec... | milkshake721/2.1M-wiki-STEM |
Federated learning-Federated learning variations-In this section, the notation of the paper published by H. Brendan McMahan and al. in 2017 is followed.To describe the federated strategies, let us introduce some notations: K : total number of clients; k : index of clients; nk : number of data samples available during t... | milkshake721/2.1M-wiki-STEM |
Federated learning-Federated learning variations-Federated stochastic gradient descent is the direct transposition of this algorithm to the federated setting, but by using a random fraction C of the nodes and using all the data on this node. The gradients are averaged by the server proportionally to the number of trai... | milkshake721/2.1M-wiki-STEM |
Federated learning-Federated learning variations-Federated averaging Federated averaging (FedAvg) is a generalization of FedSGD, which allows local nodes to perform more than one batch update on local data and exchanges the updated weights rather than the gradients. The rationale behind this generalization is that in F... | milkshake721/2.1M-wiki-STEM |
Federated learning-Federated learning variations-Federated Learning with Dynamic Regularization (FedDyn) Federated learning methods suffer when the device datasets are heterogeneously distributed. Fundamental dilemma in heterogeneously distributed device setting is that minimizing the device loss functions is not the s... | milkshake721/2.1M-wiki-STEM |
Federated learning-Federated learning variations-Personalized Federated Learning by Pruning (Sub-FedAvg) Federated Learning methods cannot achieve good global performance under Non-IID settings which motivates the participating clients to yield personalized models in federation. Recently, Vahidian et al. introduced Sub... | milkshake721/2.1M-wiki-STEM |
Federated learning-Federated learning variations-Hybrid Federated Dual Coordinate Ascent (HyFDCA) Very few methods for hybrid federated learning, where clients only hold subsets of both features and samples, exist. Yet, this scenario is very important in practical settings. Hybrid Federated Dual Coordinate Ascent (HyFD... | milkshake721/2.1M-wiki-STEM |
Federated learning-Federated learning variations-HyFDCA claims several improvement over existing algorithms: HyFDCA is a provably convergent primal-dual algorithm for hybrid FL in at least the following settings.
Hybrid Federated Setting with Complete Client Participation Horizontal Federated Setting with Random Subset... | milkshake721/2.1M-wiki-STEM |
Federated learning-Federated learning variations-HyFDCA empirically outperforms FedAvg in loss function value and validation accuracy across a multitude of problem settings and datasets. The authors also introduce a hyperparameter selection framework for FL with competing metrics using ideas from multiobjective optimiz... | milkshake721/2.1M-wiki-STEM |
Federated learning-Federated learning variations-Federated ViT using Dynamic Aggregation (FED-REV) Federated Learning (FL) provides training of global shared model using decentralized data sources on edge nodes while preserving data privacy. However, its performance in the computer vision applications using Convolution... | milkshake721/2.1M-wiki-STEM |
Federated learning-Current research topics-Federated learning has started to emerge as an important research topic in 2015 and 2016, with the first publications on federated averaging in telecommunication settings. Another important aspect of active research is the reduction of the communication burden during the feder... | milkshake721/2.1M-wiki-STEM |
Federated learning-Use cases-Federated learning typically applies when individual actors need to train models on larger datasets than their own, but cannot afford to share the data in itself with others (e.g., for legal, strategic or economic reasons). The technology yet requires good connections between local servers ... | milkshake721/2.1M-wiki-STEM |
Federated learning-Use cases-Transportation: self-driving cars Self-driving cars encapsulate many machine learning technologies to function: computer vision for analyzing obstacles, machine learning for adapting their pace to the environment (e.g., bumpiness of the road). Due to the potential high number of self-drivin... | milkshake721/2.1M-wiki-STEM |
Federated learning-Use cases-Industry 4.0: smart manufacturing In Industry 4.0, there is a widespread adoption of machine learning techniques to improve the efficiency and effectiveness of industrial process while guaranteeing a high level of safety. Nevertheless, privacy of sensitive data for industries and manufactur... | milkshake721/2.1M-wiki-STEM |
Federated learning-Use cases-Medicine: digital health Federated learning seeks to address the problem of data governance and privacy by training algorithms collaboratively without exchanging the data itself. Today's standard approach of centralizing data from multiple centers comes at the cost of critical concerns rega... | milkshake721/2.1M-wiki-STEM |
Federated learning-Use cases-Robotics Robotics includes a wide range of applications of machine learning methods: from perception and decision-making to control. As robotic technologies have been increasingly deployed from simple and repetitive tasks (e.g. repetitive manipulation) to complex and unpredictable tasks (e.... | milkshake721/2.1M-wiki-STEM |
LibGDX-LibGDX-libGDX is a free and open-source game-development application framework written in the Java programming language with some C and C++ components for performance dependent code. It allows for the development of desktop and mobile games by using the same code base. It is cross-platform, supporting Windows, L... | milkshake721/2.1M-wiki-STEM |
LibGDX-History-In the middle of 2009 Mario Zechner, the creator of libGDX, wanted to write Android games and started developing a framework called AFX (Android Effects) for this. When he found that deploying the changes from Desktop to Android device was cumbersome, he modified AFX to work on the Desktop as well, makin... | milkshake721/2.1M-wiki-STEM |
LibGDX-History-From a diverse team of open source enthusiasts comes libGDX, a cross-platform game development framework that allows programmers to write, test, and debug Java games on a desktop PC running Windows, Linux, or Mac OS X and deploy that same code to Android, iOS and WebGL-enabled browsers—something not wide... | milkshake721/2.1M-wiki-STEM |
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