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Type of algorithm
In computer science, a sequential algorithm or serial algorithm is an algorithm that is executed sequentially – once through, from start to finish, without
Sequential_algorithm
Sequence of operations for a task
characterization of sequential algorithms. His sequential ASM thesis states that every sequential algorithm is behaviorally equivalent to a sequential ASM, with
Algorithm
Independent set which is not a subset of any other independent set
Between the totally sequential and the totally parallel algorithms, there is a continuum of algorithms that are partly sequential and partly parallel
Maximal_independent_set
Algorithm for solving the quadratic programming problem from training SVMs
Sequential minimal optimization (SMO) is an algorithm for solving the quadratic programming (QP) problem that arises during the training of support-vector
Sequential minimal optimization
Sequential_minimal_optimization
Algorithmic application of graph theory
connected-component algorithms in image analysis applications, due to the bottleneck of sequentially processing each pixel. The interest to the algorithm arises again
Connected-component_labeling
Method for finding minimum spanning trees
In computer science, Prim's algorithm is a greedy algorithm that finds a minimum spanning tree for a weighted undirected graph. This means it finds a
Prim's_algorithm
Algorithm which can do multiple operations in a given time
algorithms are often referred to as "sequential algorithms", by contrast with concurrent algorithms. Algorithms vary significantly in how parallelizable
Parallel_algorithm
Computational problem
to an algorithm of Knuth for sorting with a stack (for inputs that can be sorted in this way). An even simpler linear-time sequential algorithm does not
All_nearest_smaller_values
Data mining technique
string processing algorithms and itemset mining which is typically based on association rule learning. Local process models extend sequential pattern mining
Sequential_pattern_mining
Type of multi-objective optimization
and developed a lexicographic simplex algorithm. In contrast to the sequential algorithm, this simplex algorithm considers all objective functions simultaneously
Lexicographic_optimization
Algorithm that begins on possibly incomplete inputs
matching Adversary model Dynamic algorithm Prophet inequality Real-time computing Streaming algorithm Sequential algorithm Online machine learning/Offline
Online_algorithm
Algorithm that arranges lists in order
elements) of the input. Although some algorithms are designed for sequential access, the highest-performing algorithms assume data is stored in a data structure
Sorting_algorithm
Minimum spanning forest algorithm that greedily adds edges
which runs the sequential algorithm on p subgraphs, then merges those subgraphs until only one, the final MST, remains. Dijkstra's algorithm Greedy geometric
Kruskal's_algorithm
Sequence in computer science
However, Algorithm 2 is work-efficient—it performs only a constant factor (2) of the amount of work required by the sequential algorithm—while Algorithm 1 is
Prefix_sum
Limited memory technique for decoding free codes
sequential decoding is a limited memory technique for decoding tree codes. Sequential decoding is mainly used as an approximate decoding algorithm for
Sequential_decoding
Sequentially looking in an array
A linear search sequentially checks each element of the list until it finds an element that matches the target value. If the algorithm reaches the end
Linear_search
Mutual exclusion algorithm
Dekker's algorithm is the first known correct solution to the mutual exclusion problem in concurrent programming where processes only communicate via
Dekker's_algorithm
Measure of parallel computing efficacy
best sequential algorithm. For example, an algorithm that can be solved in O ( n ) {\displaystyle O(n)} time using the best known sequential algorithm and
Cost_efficiency
Way of setting up and executing parallel computer programs
solve(problem): if problem is small enough: solve problem directly (sequential algorithm) else: for part in subdivide(problem) fork subtask to solve(part)
Fork–join_model
Optimization algorithm
Sequential quadratic programming (SQP) is an iterative method for constrained nonlinear optimization, also known as Lagrange-Newton method. SQP methods
Sequential quadratic programming
Sequential_quadratic_programming
Subfield of computer science
them. In many respects, analysis of parallel algorithms is similar to the analysis of sequential algorithms, but is generally more involved because one
Analysis of parallel algorithms
Analysis_of_parallel_algorithms
Computational problem of graph theory
of nodes is known as all-pair-shortest-paths (APSP) problem. As sequential algorithms for this problem often yield long runtimes, parallelization has
Parallel all-pairs shortest path algorithm
Parallel_all-pairs_shortest_path_algorithm
Measures to ensure concurrent computing operations generate correct results
additional complexity and overhead in a concurrent algorithm compared to the simpler sequential algorithm. For example, a failure in concurrency control can
Concurrency_control
graph theory, there exist many sequential algorithms for solving it. Among them are Prim's, Kruskal's and Borůvka's algorithms, each utilising different properties
Parallel algorithms for minimum spanning trees
Parallel_algorithms_for_minimum_spanning_trees
Abstract computer for designing parallel algorithms
is used by sequential-algorithm designers to model algorithmic performance (such as time complexity), the PRAM is used by parallel-algorithm designers
Parallel_RAM
Machine learning strategy
contextual bandit problem. For example, Bouneffouf et al. propose a sequential algorithm named Active Thompson Sampling (ATS), which, in each round, assigns
Active learning (machine learning)
Active_learning_(machine_learning)
Formal specification language created by Leslie Lamport
imperative programming language and is better-suited when specifying sequential algorithms. PlusCal was designed to replace pseudocode, retaining its simplicity
PlusCal
Type of Monte Carlo algorithms for signal processing and statistical inference
Particle filters, also known as sequential Monte Carlo methods, are a set of Monte Carlo algorithms used to find approximate solutions for filtering problems
Particle_filter
Meta-algorithmic technique to choose an algorithm
Algorithm selection (sometimes also called per-instance algorithm selection or offline algorithm selection) is a meta-algorithmic technique to choose
Algorithm_selection
Class of algorithms operating on data streams
Data stream mining Data stream clustering Online algorithm Stream processing Sequential algorithm Munro, J. Ian; Paterson, Mike (1978). "Selection and
Streaming_algorithm
Attempts to formalize the concept of algorithms
Algorithm characterizations are attempts to formalize the word algorithm. Algorithm does not have a generally accepted formal definition. Researchers
Algorithm_characterizations
Indian-American computer scientist
done extensive work in the design and analysis of parallel and sequential algorithms. He was born in India, and he did his bachelor's degree in engineering
S._Rao_Kosaraju
Divide and conquer sorting algorithm
the algorithm have been developed over the years. Some parallel merge sort algorithms are strongly related to the sequential top-down merge algorithm while
Merge_sort
Computational problem of graph theory
classical sequential algorithms which solve this problem, such as Dijkstra's algorithm. In this article, however, we present two parallel algorithms solving
Parallel single-source shortest path algorithm
Parallel_single-source_shortest_path_algorithm
1995, 9-36. (ISBN 0-19-853854-5) Y. Gurevich, Sequential Abstract State Machines capture Sequential Algorithms, ACM Transactions on Computational Logic 1(1)
Abstract_state_machine
Statistical analysis where the sample size is not fixed in advance
In statistics, sequential analysis or sequential hypothesis testing is statistical analysis where the sample size is not fixed in advance. Instead data
Sequential_analysis
Algorithm for linear programming
optimization, Dantzig's simplex algorithm (or simplex method) is an algorithm for linear programming. The name of the algorithm is derived from the concept
Simplex_algorithm
algorithm, a proprietary algorithm that embodies many of the principles of Rete. However, there are other execution algorithms such as the sequential
Business_rules_approach
Lossless data compression algorithms
Lempel–Ziv–Stac (LZS) Ziv, Jacob; Lempel, Abraham (May 1977). "A Universal Algorithm for Sequential Data Compression". IEEE Transactions on Information Theory. 23
LZ77_and_LZ78
Any algorithm which solves the search problem
In computer science, a search algorithm is an algorithm designed to solve a search problem. Search algorithms work to retrieve information stored within
Search_algorithm
Data structure for approximate set membership
guaranteed to be on the same PE. In the second step each PE uses a sequential algorithm for duplicate detection on the receiving elements, which are only
Bloom_filter
Class in computational complexity theory
binary, we have reduced the obvious sequential algorithm from exponential time to linear time. That puts the sequential problem in P. Then, it will be in
P-complete
Mathematical model of computation
computer science Gurevich, Yuri (July 2000). "Sequential Abstract State Machines Capture Sequential Algorithms" (PDF). ACM Transactions on Computational Logic
Finite-state_machine
based on table representation of rules. Engine implements optimized sequential algorithm. OpenL includes such table types as decision table, decision tree
OpenL_Tablets
Sequence of locally optimal choices
A greedy algorithm is an algorithm which, at each step, makes the choice that is locally optimal, and subsequently does not reconsider past choices. Greedy
Greedy_algorithm
Maximal biconnected subgraph
corresponds to a leaf vertex in the block-cut tree. The classic sequential algorithm for computing biconnected components in a connected undirected graph
Biconnected_component
Sampling technique
selection-rejection algorithm developed by Fan et al. in 1962 requires a single pass over data; however, it is a sequential algorithm and requires knowledge
Simple_random_sample
Optimization method
In numerical optimization, the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm is an iterative method for solving unconstrained nonlinear optimization
Broyden–Fletcher–Goldfarb–Shanno algorithm
Broyden–Fletcher–Goldfarb–Shanno_algorithm
Optimization method
Values algorithm runs much faster than the Saturation algorithm and the Ordered Outcomes algorithm. Behringer presented a sequential algorithm for lexmaxmin
Lexicographic max-min optimization
Lexicographic_max-min_optimization
measurements Odds algorithm (Bruss algorithm) Optimal online search for distinguished value in sequential random input False nearest neighbor algorithm (FNN) estimates
List_of_algorithms
Algorithm for shuffling a finite sequence
The Fisher–Yates shuffle is an algorithm for shuffling a finite sequence. The algorithm takes a list of all the elements of the sequence, and continually
Fisher–Yates_shuffle
Mathematical version of an order change
Fisher-Yates is not the fastest algorithm for generating a permutation, because Fisher-Yates is essentially a sequential algorithm and "divide and conquer" procedures
Permutation
Formal specification language
created in 2009; it transpiles to TLA+ and is useful for specifying sequential algorithms. TLA+2 was announced in 2014, expanding language support for proof
TLA+
Almost-sorted sequence in computer science
{\displaystyle O(n\log(n/k))} -time. This algorithm is Par-optimal, that is, there exists no sequential algorithm with a better worst-case complexity. Nearly-sorted
K-sorted_sequence
Resource problem in machine learning
constructed convergent population selection strategies in "some aspects of the sequential design of experiments". A theorem, the Gittins index, first published
Multi-armed_bandit
Problem of finding obscured edges in a wire-frame 3D model
real machines. The hidden-line algorithm does O(n2 log n) work, which is the upper bound for the best sequential algorithms used in practice. Cook, Dwork
Hidden-line_removal
Sequential model-based optimization of expensive black-box functions
, the algorithm produces additional evaluation points x 1 , x 2 , … {\displaystyle x_{1},x_{2},\ldots } . After n {\displaystyle n} sequential evaluations
Bayesian_optimization
Abstract computational machine model
models, (type 2) Pointer algorithms. Yuri Gurevich (2000), Sequential Abstract State Machines Capture Sequential Algorithms, ACM Transactions on Computational
Pointer_machine
Concurrent programming algorithm for mutual exclusion
Peterson's algorithm (or Peterson's solution) is a concurrent programming algorithm for mutual exclusion that allows two or more processes to share a single-use
Peterson's_algorithm
Type of algorithm for constrained optimization
solve. Other nonlinear programming algorithms: Sequential quadratic programming Successive linear programming Sequential linear-quadratic programming Interior
Penalty_method
Optimization algorithm
an optimization algorithm in the collection of quasi-Newton methods that approximates the Broyden–Fletcher–Goldfarb–Shanno algorithm (BFGS) using a limited
Limited-memory_BFGS
Estimate of time taken for running an algorithm
situations where the algorithm has to sequentially read its entire input. Therefore, much research has been invested into discovering algorithms exhibiting linear
Time_complexity
Optimization by removing non-optimal solutions to subproblems
an algorithm design paradigm for discrete and combinatorial optimization problems, as well as mathematical optimization. A branch-and-bound algorithm consists
Branch_and_bound
Digital workload distribution techniques
The sequential algorithms paired to these functions are defined by flexible parameters unique to the specific database. Numerous scheduling algorithms, also
Load_balancing_(computing)
Computer program for the Boolean satisfiability problem
space between the processing elements. Divide-and-conquer algorithms, such as the sequential DPLL, already apply the technique of splitting the search
SAT_solver
Algorithm in mathematical optimization
Both papers detail a generic form of the algorithm terminating in O(V 2E) along with a O(V 3) sequential implementation, a O(VE log(V 2/E)) implementation
Push–relabel maximum flow algorithm
Push–relabel_maximum_flow_algorithm
Overview of and topical guide to computer programming
sequence Search algorithm Sorting algorithm Merge algorithm String algorithms Greedy algorithm Reduction Sequential algorithm Parallel algorithm Distributed
Outline of computer programming
Outline_of_computer_programming
Mathematical model describing how an output of a function is computed given an input
can be classified into three categories: sequential models, functional models, and concurrent models. Sequential models include: Finite-state machines Post
Model_of_computation
trajectories through the solution domains of the problem at hands: Algorithm: Sequential trajectory-based general pseudo-code Generate(s(0)); // Initial
Parallel_metaheuristic
Optimization algorithm
computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems
Ant colony optimization algorithms
Ant_colony_optimization_algorithms
outperforms Felzenszwalb's sequential algorithm by an order of magnitude. In 2017, Saglam and Baykan used Prim's sequential representation of minimum spanning
Minimum spanning tree-based segmentation
Minimum_spanning_tree-based_segmentation
Optimization algorithm
technique which belongs to the family of local search. It is an iterative algorithm that starts with an arbitrary solution to a problem, then attempts to
Hill_climbing
Vishkin 1989;Anderson & Miller 1990). This number of steps matches the sequential algorithm. List ranking can equivalently be viewed as performing a prefix sum
List_ranking
Algorithm for the directed version of the minimum spanning tree problem
In graph theory, Edmonds' algorithm or Chu–Liu/Edmonds' algorithm is an algorithm for finding a spanning arborescence of minimum weight (sometimes called
Edmonds'_algorithm
Algorithm used to solve non-linear least squares problems
In mathematics and computing, the Levenberg–Marquardt algorithm (LMA or just LM), also known as the damped least-squares (DLS) method, is used to solve
Levenberg–Marquardt_algorithm
Process in materials science
Random sequential adsorption (RSA) refers to a process where particles are randomly introduced in a system, and if they do not overlap any previously adsorbed
Random_sequential_adsorption
Computer memory concept
Indexing into a list that has sequential access requires O(n) time, where n is the index. As a result, many algorithms such as quicksort and binary search
Sequential_access
Parallel version of breadth-first search algorithm
BFS through the use of parallel computing. In the conventional sequential BFS algorithm, two data structures are created to store the frontier and the
Parallel_breadth-first_search
Method for creating, maintaining, and manipulating computer files
optimizer which automatically selects indexes. An indexing algorithm that allows both sequential and keyed access to data. Most databases use some variation
ISAM
Technique for finding an extremum of a function
but very robust. The technique derives its name from the fact that the algorithm maintains the function values for four points whose three interval widths
Golden-section_search
Ambiguous term in statistics
694–699, Edmonton, ACM Press, 2002. D. D. Lewis and W. A. Gale, A Sequential Algorithm for Training Text classifiers. In: W. B. Croft and C. J. van Rijsbergen
Calibration_(statistics)
Triangulation method
triangulation algorithm in Ed". Computer-Aided Design. 30 (5): 333–341. doi:10.1016/S0010-4485(97)00082-1. A Comparison of Sequential Delaunay Triangulation
Delaunay_triangulation
Algorithm for finding max graph matchings
In graph theory, the blossom algorithm is an algorithm for constructing maximum matchings on graphs. The algorithm was developed by Jack Edmonds in 1961
Blossom_algorithm
Population-based search algorithm
computer science and operations research, the bees algorithm is a population-based search algorithm which was developed by Pham, Ghanbarzadeh et al. in
Bees_algorithm
Algorithm for computing the maximal flow of a network
Dinic's algorithm or Dinitz's algorithm is a strongly polynomial algorithm for computing the maximum flow in a flow network, conceived in 1970 by Israeli
Dinic's_algorithm
Linear programming algorithm
Karmarkar's algorithm is an algorithm introduced by Narendra Karmarkar in 1984 for solving linear programming problems. It was the first reasonably efficient
Karmarkar's_algorithm
Randomized algorithm
pseudocode for the KLRS algorithm: KLRS(Stream, BufferSize M, TargetDistribution) Input: * Stream (data points (x, y) arriving sequentially) * BufferSize M *
Reservoir_sampling
Node ordering for directed acyclic graphs
Mehlhorn, Kurt; Dietzfelbinger, Martin; Dementiev, Roman (2019), Sequential and Parallel Algorithms and Data Structures: The Basic Toolbox, Springer International
Topological_sorting
Ancient algorithm for generating prime numbers
In mathematics, the sieve of Eratosthenes is an ancient algorithm for finding all prime numbers up to any given limit. It does so by iteratively marking
Sieve_of_Eratosthenes
Class of algorithms that find approximate solutions to optimization problems
computer science and operations research, approximation algorithms are efficient algorithms that find approximate solutions to optimization problems
Approximation_algorithm
Combinatorial optimization method
to integer values. Branch and cut involves running a branch and bound algorithm and using cutting planes to tighten the linear programming relaxations
Branch_and_cut
Study of mathematical algorithms for optimization problems
of the simplex algorithm that are especially suited for network optimization Combinatorial algorithms Quantum optimization algorithms The iterative methods
Mathematical_optimization
Type of randomized algorithm
Carlo algorithm is a randomized algorithm whose output may be incorrect with a certain (typically small) probability. Two examples of such algorithms are
Monte_Carlo_algorithm
Method of solving linear programming problems
linear programming problems using the simplex algorithm. The Big M method extends the simplex algorithm to problems that contain "greater-than" constraints
Big_M_method
Amateur radio communications software
at the cost that the highly efficient Viterbi algorithm must be replaced by a simple sequential algorithm for the decoding process. The standard message
WSPR_(amateur_radio_software)
Optimization algorithm
unconstrained mathematical optimization. It is a first-order iterative algorithm for minimizing a differentiable multivariate function. The idea is to
Gradient_descent
Numerical optimization algorithm
shrink the simplex towards a better point. An intuitive explanation of the algorithm from "Numerical Recipes": The downhill simplex method now takes a series
Nelder–Mead_method
Algorithm for caching data
policies (also known as cache replacement algorithms or cache algorithms) are optimizing instructions or algorithms which a computer program or hardware-maintained
Cache_replacement_policies
Algorithm for finding zeros of functions
method, named after Isaac Newton and Joseph Raphson, is a root-finding algorithm which produces successively better approximations to the roots (or zeroes)
Newton's_method
Instructions a computer can execute
understand how they are retrieved. Imperative languages specify a sequential algorithm using declarations, expressions, and statements: A declaration introduces
Computer_program
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SEQUENTIAL ALGORITHM
SEQUENTIAL ALGORITHM
SEQUENTIAL ALGORITHM
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SEQUENTIAL ALGORITHM
SEQUENTIAL ALGORITHM
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SEQUENTIAL ALGORITHM
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