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Amos Storkey
Amos James Storkey is Professor of Machine Learning and Artificial Intelligence at the School of Informatics, University of Edinburgh. Storkey studied mathematics at Trinity College, Cambridge and obtained his doctorate from Imperial College, London. In 1997 during his PhD, he worked on the Hopfield Network a form of recurrent artificial neural network popularized by John Hopfield in 1982. Hopfield nets serve as content-addressable ("associative") memory systems with binary threshold nodes and Storkey developed what became known as the "Storkey Learning Rule" .Storkey, Amos. "Increasing the capacity of a Hopfield network without sacrificing functionality." Artificial Neural Networks – ICANN'97 (1997)451-456Storkey, Amos. "Efficient Covariance Matrix Methods for Bayesian Gaussian Processes and Hopfield Neural Networks". PhD Thesis. University of London. (1999) Subsequently, he has worked on approximate Bayesian methods, machine learning in astronomy, graphical models, inferen ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Alan Storkey
Alan Storkey (born 2 October 1943, in London) is an economist, sociologist and artist. He is known for his writing and lectures and for his work on transport and the arms industry, arms trade. He grew up in Wembley, Nottingham and Norwich, the son of Alec and Doris Storkey. In 1968 he married Elaine Storkey née Elaine Lively, a philosopher, sociologist and broadcaster. They have three sons, five grandsons and a granddaughter. Education and academic posts Alan Storkey was educated at the City of Norwich School, where he was school captain, and then at Christ's College, Cambridge where he studied economics. He did postgraduate work in sociology at the London School of Economics and a doctorate in economics (consumption theory) at the Vrije Universiteit, Amsterdam, studying under Bob Goudzwaard. His first academic post was in sociology at Stirling University from where he went on to direct the Shaftesbury Project. Having taught economics and politics at Worksop College, he became ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Neural Network
Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute 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. An artificial neuron receives signals then processes them and can signal neurons connected to it. The "signal" at a connection is a real number, and the output of each neuron is computed by some non-linear function of the sum of its inputs. The connections are called ''edges''. Neurons and edges typically have a ''weight'' that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Neurons may have a threshold such that a signal is sent only if the aggregate signal crosses that threshold. Typically ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
1971 Births
* The year 1971 had three partial solar eclipses ( February 25, July 22 and August 20) and two total lunar eclipses (February 10, and August 6). The world population increased by 2.1% this year, the highest increase in history. Events January * January 2 – 66 people are killed and over 200 injured during a crush in Glasgow, Scotland. * January 5 – The first ever One Day International cricket match is played between Australia and England at the Melbourne Cricket Ground. * January 8 – Tupamaros kidnap Geoffrey Jackson, British ambassador to Uruguay, in Montevideo, keeping him captive until September. * January 9 – Uruguayan president Jorge Pacheco Areco demands emergency powers for 90 days due to kidnappings, and receives them the next day. * January 12 – The landmark United States television sitcom ''All in the Family'', starring Carroll O'Connor as Archie Bunker, debuts on CBS. * January 14 – Seventy Brazilian political prisoners ar ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Google Scholar
Google Scholar is a freely accessible web search engine that indexes the full text or metadata of scholarly literature across an array of publishing formats and disciplines. Released in beta in November 2004, the Google Scholar index includes peer-reviewed online academic journals and books, conference papers, theses and dissertations, preprints, abstracts, technical reports, and other scholarly literature, including court opinions and patents. Google Scholar uses a web crawler, or web robot, to identify files for inclusion in the search results. For content to be indexed in Google Scholar, it must meet certain specified criteria. An earlier statistical estimate published in PLOS One using a mark and recapture method estimated approximately 80–90% coverage of all articles published in English with an estimate of 100 million.''Trend Watch'' (2014) Nature 509(7501), 405 – discussing Madian Khabsa and C Lee Giles (2014''The Number of Scholarly Documents on the Public Web'' ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Monte Carlo Tree Search
In computer science, Monte Carlo tree search (MCTS) is a heuristic search algorithm for some kinds of decision processes, most notably those employed in software that plays board games. In that context MCTS is used to solve the game tree. MCTS was combined with neural networks in 2016 and has been used in multiple board games like Chess, Shogi, Checkers, Backgammon, Contract Bridge, Computer Go, Scrabble, and Clobber as well as in turn-based-strategy video games (such as Total War: Rome II's implementation in the high level campaign AI). History Monte Carlo method The Monte Carlo method, which uses random sampling for deterministic problems which are difficult or impossible to solve using other approaches, dates back to the 1940s. In his 1987 PhD thesis, Bruce Abramson combined minimax search with an ''expected-outcome model'' based on random game playouts to the end, instead of the usual static evaluation function. Abramson said the expected-outcome model "is shown to b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
GNU Go
GNU Go is a free software program by the Free Software Foundation that plays Go. Its source code is quite portable, and can be easily compiled for Linux, as well as other Unix-like systems, Microsoft Windows and macOS; ports exist for other platforms. The program plays Go against the user, at about 5 to 7 kyu strength on the 9×9 board. Multiple board sizes are supported, from 5×5 to 19×19. Strength At this level of performance, GnuGo was between six and seven stones weaker than the top commercial programs on good hardware as of early 2009, but comparable in strength to the strongest programs not using Monte Carlo methods. It did well at many computer Go tournaments. For instance, it took the gold medal at the 2003 and 2006 Computer Olympiad and second place at the 2006 Gifu Challenge. Protocols Although ASCII-based, GNU Go supports two protocols—the Go Modem Protocol and the Go Text Protocol—by which GUIs can interface with it to give a graphical display. Several su ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Convolutional Neural Network
In deep learning, a convolutional neural network (CNN, or ConvNet) is a class of artificial neural network (ANN), most commonly applied to analyze visual imagery. CNNs are also known as Shift Invariant or Space Invariant Artificial Neural Networks (SIANN), based on the shared-weight architecture of the convolution kernels or filters that slide along input features and provide translation-equivariant responses known as feature maps. Counter-intuitively, most convolutional neural networks are not invariant to translation, due to the downsampling operation they apply to the input. They have applications in image and video recognition, recommender systems, image classification, image segmentation, medical image analysis, natural language processing, brain–computer interfaces, and financial time series. CNNs are regularized versions of multilayer perceptrons. Multilayer perceptrons usually mean fully connected networks, that is, each neuron in one layer is connected to all neuro ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Neuron
An artificial neuron is a mathematical function conceived as a model of biological neurons, a neural network. Artificial neurons are elementary units in an artificial neural network. The artificial neuron receives one or more inputs (representing excitatory postsynaptic potentials and inhibitory postsynaptic potentials at neural dendrites) and sums them to produce an output (or , representing a neuron's action potential which is transmitted along its axon). Usually each input is separately weighted, and the sum is passed through a non-linear function known as an activation function or transfer function. The transfer functions usually have a sigmoid shape, but they may also take the form of other non-linear functions, piecewise linear functions, or step functions. They are also often monotonically increasing, continuous, differentiable and bounded. Non-monotonic, unbounded and oscillating activation functions with multiple zeros that outperform sigmoidal and ReLU like activation ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Binary Numeral System
A binary number is a number expressed in the base-2 numeral system or binary numeral system, a method of mathematical expression which uses only two symbols: typically "0" (zero) and "1" ( one). The base-2 numeral system is a positional notation with a radix of 2. Each digit is referred to as a bit, or binary digit. Because of its straightforward implementation in digital electronic circuitry using logic gates, the binary system is used by almost all modern computers and computer-based devices, as a preferred system of use, over various other human techniques of communication, because of the simplicity of the language and the noise immunity in physical implementation. History The modern binary number system was studied in Europe in the 16th and 17th centuries by Thomas Harriot, Juan Caramuel y Lobkowitz, and Gottfried Leibniz. However, systems related to binary numbers have appeared earlier in multiple cultures including ancient Egypt, China, and India. Leibniz was specifica ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Content-addressable Memory
Content-addressable memory (CAM) is a special type of computer memory used in certain very-high-speed searching applications. It is also known as associative memory or associative storage and compares input search data against a table of stored data, and returns the address of matching data. CAM is frequently used in networking devices where it speeds up forwarding information base and routing table operations. This kind of associative memory is also used in cache memory. In associative cache memory, both address and content is stored side by side. When the address matches, the corresponding content is fetched from cache memory. History Dudley Allen Buck invented the concept of content-addressable memory in 1955. Buck is credited with the idea of ''recognition unit''. Hardware associative array Unlike standard computer memory, random-access memory (RAM), in which the user supplies a memory address and the RAM returns the data word stored at that address, a CAM is designed such ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
John Hopfield
John Joseph Hopfield (born July 15, 1933) is an American scientist most widely known for his invention of an associative neural network in 1982. It is now more commonly known as the Hopfield network. Biography Hopfield was born in 1933 to Polish physicist John J. Hopfield (spectroscopist), John Joseph Hopfield and physicist Helen Hopfield. Helen was the older Hopfield's second wife. He is the sixth of Hopfield's children and has three children and six grandchildren of his own. He received his Bachelor of Arts, A.B. from Swarthmore College in 1954, and a Ph.D. in physics from Cornell University in 1958 (supervised by Albert Overhauser). He spent two years in the theory group at Bell Laboratories, and subsequently was a faculty member at University of California, Berkeley (physics), Princeton University (physics), California Institute of Technology (Chemistry and Biology) and again at Princeton, where he is the Howard A. Prior Professor of Molecular Biology, Emeritus. For 35 yea ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Recurrent Neural Network
A recurrent neural network (RNN) is a class of artificial neural networks where connections between nodes can create a cycle, allowing output from some nodes to affect subsequent input to the same nodes. This allows it to exhibit temporal dynamic behavior. Derived from feedforward neural networks, RNNs can use their internal state (memory) to process variable length sequences of inputs. This makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition. Recurrent neural networks are theoretically Turing complete and can run arbitrary programs to process arbitrary sequences of inputs. The term "recurrent neural network" is used to refer to the class of networks with an infinite impulse response, whereas "convolutional neural network" refers to the class of finite impulse response. Both classes of networks exhibit temporal dynamic behavior. A finite impulse recurrent network is a directed acyclic graph that can be unrolled and replace ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
