In computer science, a heap is a specialized tree-based data structure which is essentially an almost complete tree that satisfies the heap property: if P is a parent node of C, then the key of P is either greater than or equal to or less than or equal to the key of C. The node at the "top" of the heap is called the root node.
Ronald Linn Rivest is a cryptographer and an Institute Professor at MIT. He is a member of MIT's Department of Electrical Engineering and Computer Science (EECS) and a member of MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL). He was a member of the Election Assistance Commission's Technical Guidelines Development Committee, tasked with assisting the EAC in drafting the Voluntary Voting System Guidelines.
Granular synthesis is a basic sound synthesis method that operates on the microsound time scale.
Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model of sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to perform the task. Machine learning algorithms are used in a wide variety of applications, such as email filtering, detection of network intruders, and computer vision, where it is infeasible to develop an algorithm of specific instructions for performing the task. Machine learning is closely related to computational statistics, which focuses on making predictions using computers. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. Data mining is a field of study within machine learning, and focuses on exploratory data analysis through unsupervised learning. In its application across business problems, machine learning is also referred to as predictive analytics.
Unsupervised learning is a term used for Hebbian learning, associated to learning without a teacher, also known as self-organization and a method of modelling the probability density of inputs.
The MIT Press is a university press affiliated with the Massachusetts Institute of Technology (MIT) in Cambridge, Massachusetts.
Charles Eric Leiserson is a computer scientist, specializing in the theory of parallel computing and distributed computing, and particularly practical applications thereof. As part of this effort, he developed the Cilk multithreaded language. He invented the fat-tree interconnection network, a hardware-universal interconnection network used in many supercomputers, including the Connection Machine CM5, for which he was network architect. He helped pioneer the development of VLSI theory, including the retiming method of digital optimization with James B. Saxe and systolic arrays with H. T. Kung. He conceived of the notion of cache-oblivious algorithms, which are algorithms that have no tuning parameters for cache size or cache-line length, but nevertheless use cache near-optimally. He developed the Cilk language for multithreaded programming, which uses a provably good work-stealing algorithm for scheduling. Leiserson coauthored the standard algorithms textbook Introduction to Algorithms together with Thomas H. Cormen, Ronald L. Rivest, and Clifford Stein.
In machine learning and statistics, classification is the problem of identifying to which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations whose category membership is known. Examples are assigning a given email to the "spam" or "non-spam" class, and assigning a diagnosis to a given patient based on observed characteristics of the patient. Classification is an example of pattern recognition.
John Henry Holland was an American scientist and Professor of psychology and Professor of electrical engineering and computer science at the University of Michigan, Ann Arbor. He was a pioneer in what became known as genetic algorithms.
Clifford Seth Stein, a computer scientist, is a professor of industrial engineering and operations research at Columbia University in New York, NY, where he also holds an appointment in the Department of Computer Science. Stein is chair of the Industrial Engineering and Operations Research Department at Columbia University. Prior to joining Columbia, Stein was a professor at Dartmouth College in New Hampshire.
Introduction to Algorithms is a book by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. The book has been widely used as the textbook for algorithms courses at many universities and is commonly cited as a reference for algorithms in published papers, with over 10,000 citations documented on CiteSeerX. The book sold half a million copies during its first 20 years. Its fame has led to the common use of the abbreviation "CLRS", or, in the first edition, "CLR".
Neural network software is used to simulate, research, develop, and apply artificial neural networks, software concepts adapted from biological neural networks, and in some cases, a wider array of adaptive systems such as artificial intelligence and machine learning.
In philosophy, the computational theory of mind (CTM) refers to a family of views that hold that the human mind is an information processing system and that cognition and consciousness together are a form of computation. Warren McCulloch and Walter Pitts (1943) were the first to suggest that neural activity is computational. They argued that neural computations explain cognition. The theory was proposed in its modern form by Hilary Putnam in 1967, and developed by his PhD student, philosopher and cognitive scientist Jerry Fodor in the 1960s, 1970s and 1980s. Despite being vigorously disputed in analytic philosophy in the 1990s due to work by Putnam himself, John Searle, and others, the view is common in modern cognitive psychology and is presumed by many theorists of evolutionary psychology. In the 2000s and 2010s the view has resurfaced in analytic philosophy.
Melanie Mitchell is a professor of computer science at Portland State University. She has worked at the Santa Fe Institute and Los Alamos National Laboratory. Her major work has been in the areas of analogical reasoning, Complex Systems, genetic algorithms and cellular automata, and her publications in those fields are frequently cited.
Algorithmic art, also known as algorithm art, is art, mostly visual art, of which the design is generated by an algorithm. Algorithmic artists are sometimes called algorists.
In the mathematical and algorithmic study of graph theory, the converse, transpose or reverse of a directed graph G is another directed graph on the same set of vertices with all of the edges reversed compared to the orientation of the corresponding edges in G. That is, if G contains an edge (u,v) then the converse/transpose/reverse of G contains an edge (v,u) and vice versa.
Leabra stands for local, error-driven and associative, biologically realistic algorithm. It is a model of learning which is a balance between Hebbian and error-driven learning with other network-derived characteristics. This model is used to mathematically predict outcomes based on inputs and previous learning influences. This model is heavily influenced by and contributes to neural network designs and models. This algorithm is the default algorithm in emergent when making a new project, and is extensively used in various simulations.
Hyunjune Sebastian Seung is a Korean American multi-disciplinary expert whose research efforts have spanned the fields of neuroscience, physics and bioinformatics. He was a professor of Computational Neuroscience in the Department of Brain and Cognitive Sciences and a professor of Physics at the Massachusetts Institute of Technology and is now a professor at Princeton University. He also was an Investigator of the Howard Hughes Medical Institute.
George Stiny is an American design and computation theorist. He co-created the concept of shape grammars with James Gips.
