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Property describing run-time complexity of algorithms
In computer science, an output-sensitive algorithm is an algorithm whose running time depends on the size of the output, instead of, or in addition to
Output-sensitive_algorithm
Class of algorithms in computational geometry
{\displaystyle h} (the number of points in the hull). Such algorithms are called output-sensitive algorithms. They may be asymptotically more efficient than Θ
Convex_hull_algorithms
Algorithm for finding the convex hull of a set of points in the plane
In computational geometry, Chan's algorithm, named after Timothy M. Chan, is an optimal output-sensitive algorithm to compute the convex hull of a set
Chan's_algorithm
Method for division with remainder
than even slow division algorithms like long division. It is useful if Q is known to be small (being an output-sensitive algorithm), and can serve as an
Division_algorithm
Algorithm for listing maximal cliques
{1,3}): no output BronKerbosch2({5}, Ø, {1,2,4}): no output The Bron–Kerbosch algorithm is not known to be an output-sensitive algorithm: unlike some
Bron–Kerbosch_algorithm
Algorithm for computing convex hulls in a set of points
O(nh)} . The run time depends on the size of the output, so Jarvis's march is an output-sensitive algorithm. However, because the running time depends linearly
Gift_wrapping_algorithm
Task of computing complete subgraphs
clique. An algorithm such as theirs in which the running time depends on the output size is known as an output-sensitive algorithm. Their algorithm is based
Clique_problem
Algorithm that outputs all solutions to a problem
output, or the total size of the set of all outputs, similarly to what is done with output-sensitive algorithms. An enumeration problem P is defined as a
Enumeration_algorithm
Type of algorithm in computer science
computer science, a deterministic algorithm is an algorithm that, given a particular input, will always produce the same output, with the underlying machine
Deterministic_algorithm
Optimized algorithm for computing the convex hull of a set of points
output-sensitive time complexity implies that the algorithm’s running time depends on both the input size and the size of the output. Earlier output-sensitive
Kirkpatrick–Seidel_algorithm
Non-parametric classification method
Cover. The k-NN algorithm can also be generalized for regression. In k-NN regression, also known as nearest neighbor smoothing, the output is the property
K-nearest_neighbors_algorithm
Means of improving the efficiency of TCP/IP networks
buffering its output until it has a full packet's worth of output, thus allowing output to be sent all at once. The RFC defines the algorithm as inhibit
Nagle's_algorithm
Copy of a directed graph with redundant edges removed
transitive reduction using an output-sensitive algorithm in an amount of time that depends on r in place of m. The algorithm is: For each vertex v, in the
Transitive_reduction
Machine learning paradigm
machine learning paradigm where an algorithm learns to map input data to a specific output based on example input-output pairs. This process involves training
Supervised_learning
Intersection graph of a chord diagram
1016/S0012-365X(96)00344-5. Nash, Nicholas; Gregg, David (2010), "An output sensitive algorithm for computing a maximum independent set of a circle graph", Information
Circle_graph
Canadian computer scientist
contributions to computational geometry, algorithms, and data structures". Chan's algorithm, an output-sensitive algorithm for planar convex hulls Two CS faculty
Timothy_M._Chan
Tree data structure to hold intervals
in the collection, this is asymptotically optimal; however, output-sensitive algorithms, where the runtime is expressed in terms of m {\displaystyle
Interval_tree
is desired for these problems is an output-sensitive algorithm, one that takes a small amount of time per output clause. The decision, dualization, and
Monotone_dualization
Problem of sorting pairs of numbers by their sum
be significantly smaller than n 2 {\displaystyle n^{2}} , and output-sensitive algorithms for constructing it have been investigated. Steven Skiena recounts
X_+_Y_sorting
Technological phenomenon with social implications
with the ways in which unanticipated output and manipulation of data can impact the physical world. Because algorithms are often considered to be neutral
Algorithmic_bias
Problem of finding obscured edges in a wire-frame 3D model
65–73, 1988. J. H. Reif and S. Sen. An efficient output-sensitive hidden surface removal algorithm and its parallelization. In Proc. 4th Annual Symp
Hidden-line_removal
research on range reporting data structures has investigated output-sensitive algorithms, where the query time is analyzed in terms of both n and the
Range_reporting
Data clustering algorithm
CURE's hierarchical clustering algorithm. This enables CURE to correctly identify the clusters and makes it less sensitive to outliers. Running time is
CURE_algorithm
Analysis of datasets using techniques from topology
00199 [math.AT]. Chen, Chao; Kerber, Michael (2013-05-01). "An output-sensitive algorithm for persistent homology". Computational Geometry. 27th Annual
Topological_data_analysis
Standard for the encryption of electronic data
Standard (DES), which had been published in 1977. The algorithm described by AES is a symmetric-key algorithm, meaning the same key is used for both encrypting
Advanced_Encryption_Standard
Smallest convex set containing a given set
n)} . For points in two and three dimensions, more complicated output-sensitive algorithms are known that compute the convex hull in time O ( n log h
Convex_hull
Early unclassified symmetric-key block cipher
The Data Encryption Standard (DES /ˌdiːˌiːˈɛs, dɛz/) is a symmetric-key algorithm for the encryption of digital data. Although its short key length of 56
Data_Encryption_Standard
String metric for measuring edit distance
an exact algorithm need not evaluate the entire dynamic-programming matrix. Ukkonen developed exact threshold and distance-sensitive algorithms whose running
Levenshtein_distance
Digital identifier derived from the data by an algorithm
fingerprinting algorithm that produces a snippet, hash, or fingerprint of various forms of multimedia. A perceptual hash is a type of locality-sensitive hash,
Fingerprint_(computing)
An algorithm is a fundamental set of rules or defined procedures that are typically designed and used to be a simpler way to solve a specific problem
List_of_algorithms
Discrete Fourier transform algorithm
to surround the country from outside. To analyze the output of these sensors, an FFT algorithm would be needed. In discussion with Tukey, Richard Garwin
Fast_Fourier_transform
Control loop feedback mechanism
summed to calculate the output of the PID controller. Defining u(t) as the controller output, the final form of the PID algorithm is
PID_controller
Algorithm used in relational databases
that this algorithm is memory-sensitive, because there are two competing demands for memory (the hash table for partition 0, and the output buffers for
Hash_join
Data compression technique
this method, the most notable are FGK (Faller-Gallager-Knuth) and Vitter algorithm. It is an online coding technique based on Huffman coding. Having no initial
Adaptive_Huffman_coding
Mapping arbitrary data to fixed-size values
fingerprinting algorithm that produces a snippet, hash, or fingerprint of various forms of multimedia. A perceptual hash is a type of locality-sensitive hash,
Hash_function
Algorithmic technique using hashing
of code. A hash function is a mathematical algorithm which maps arbitrary-sized data to a fixed size output. Many solutions use cryptographic hash functions
Fuzzy_hashing
Property of an algorithm
science, algorithmic efficiency is a property of an algorithm which relates to the amount of computational resources used by the algorithm. Algorithmic efficiency
Algorithmic_efficiency
Function's sensitivity to argument change
measures how much the output value of the function can change for a small change in the input argument. This is used to measure how sensitive a function is to
Condition_number
for training CMAC is sensitive to the learning rate and could lead to divergence. In 2004, a recursive least squares (RLS) algorithm was introduced to train
Cerebellar model articulation controller
Cerebellar_model_articulation_controller
Bioinformatics search algorithm
In bioinformatics, BLAST (basic local alignment search tool) is an algorithm and program for comparing primary biological sequence information, such as
BLAST_(biotechnology)
Overview of and topical guide to machine learning
neighbors algorithm Kernel methods for vector output Kernel principal component analysis Learning vector quantization Leabra Linde–Buzo–Gray algorithm Local
Outline_of_machine_learning
Color filter array
1976 called the green photosensors luminance-sensitive elements and the red and blue ones chrominance-sensitive elements. He used twice as many green elements
Bayer_filter
Measurement of blood pumped by the heart
monitor), derives left-sided cardiac output (Q) from a sample of arterial pulsations. The device uses an algorithm based on the Frank–Starling law of the
Cardiac_output
Algorithmically generated data that have a similar distribution as sampled data
synthesizers or flight simulators. The output of such systems approximates the real thing, but is fully algorithmically generated. Synthetic data is used in
Synthetic_data
Color reconstruction algorithm
is a digital image processing algorithm used to reconstruct a full color image from the incomplete color samples output from an image sensor overlaid
Demosaicing
Electronic design automation method
in most ATPG algorithms. D Algorithm tries to propagate the stuck at fault value denoted by D (for SA0) or D (for SA1) to a primary output. Path-Oriented
Automatic test pattern generation
Automatic_test_pattern_generation
Idea that small causes can have large effects
In chaos theory, the butterfly effect is the sensitive dependence on initial conditions in which a small change in one state of a deterministic nonlinear
Butterfly_effect
Type of adversarial machine learning attack
attacker tries to reconstruct or infer sensitive information about a model's training data by analyzing the outputs of a trained machine learning model.
Model_inversion_attack
Bioinformatics computer program
generating a guide tree is less sensitive to noise. ClustalW was one of the first multiple sequence alignment algorithms to combine pairwise alignment and
Clustal
Probabilistic optimization technique and metaheuristic
sensitive to coarser energy variations, while it is sensitive to finer energy variations when T is small. The name and inspiration of the algorithm demand
Simulated_annealing
Class of fingerprinting algorithm
fingerprinting algorithm that produces a snippet, hash, or fingerprint of various forms of multimedia. A perceptual hash is a type of locality-sensitive hash,
Perceptual_hashing
Rewriting system and type of formal grammar
McQuillan, I., Bernard, J., & Prusinkiewicz, P. (2018). Algorithms for inferring context-sensitive L-systems. In Unconventional Computation and Natural Computation:
L-system
Tree-based ensemble machine learning methods
decision trees' habit of overfitting to their training set. The first algorithm for random decision forests was created in 1995 by Tin Kam Ho using the
Random_forest
Unencrypted information
is used as input to an encryption algorithm; the output is usually termed ciphertext, particularly when the algorithm is a cipher. Codetext is less often
Plaintext
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
Measure of algorithm accuracy
are evaluated on finite samples, the evaluation of a learning algorithm may be sensitive to sampling error. As a result, measurements of prediction error
Generalization_error
Measurement of algorithmic bias
Fairness in machine learning (ML) refers to the various attempts to correct algorithmic bias in automated decision processes based on ML models. Decisions made
Fairness_(machine_learning)
Measuring the time or resources used by a section of a computer program
their instruction scheduling or branch prediction algorithm is performing... — ATOM, PLDI The output of a profiler may be: A statistical summary of the
Profiling (computer programming)
Profiling_(computer_programming)
Practice and study of secure communication techniques
the new SHA-3 hash algorithm. Unlike block and stream ciphers that are invertible, cryptographic hash functions produce a hashed output that cannot be used
Cryptography
Set of methods for supervised statistical learning
for regression tasks, where the objective becomes ϵ-sensitive. The support vector clustering algorithm, created by Hava Siegelmann and Vladimir Vapnik, applies
Support_vector_machine
Instrument that records seismic waves by measuring ground motions
and to study the internal structure of Earth. A simple seismometer, sensitive to up-down motions of the Earth, is like a weight hanging from a spring
Seismometer
Biased assessment of an algorithm
Algorithm aversion is defined as a "biased assessment of an algorithm which manifests in negative behaviors, and attitudes towards the algorithm compared
Algorithm_aversion
Structuring text as input to generative artificial intelligence
refining prompts for an artificial intelligence program, algorithm, etc., in order to optimize its output or to achieve a desired outcome; the discipline or
Prompt_engineering
Technique for quickly estimating similarity of sets
also use the algorithm in their newly created FLoC (Federated Learning of Cohorts) system. A hash function maps arbitrary data onto outputs of a fixed size
SimHash
Biological theory of intelligence
generation: a spatial pooling algorithm, which outputs sparse distributed representations (SDR), and a sequence memory algorithm, which learns to represent
Hierarchical_temporal_memory
Method of analyzing variables in software
cycles, a more advanced algorithm is required. The most common way of solving the data-flow equations is by using an iterative algorithm. It starts with an
Data-flow_analysis
Used for encoding or decoding ciphertext
that are stored in a file, which, when processed through a cryptographic algorithm, can encode or decode cryptographic data. Based on the used method, the
Key_(cryptography)
Field of machine learning
agent can be trained for each algorithm. Since the performance is sensitive to implementation details, all algorithms should be implemented as closely
Reinforcement_learning
Numerical eigenvalue calculation
The Lanczos algorithm is an iterative method devised by Cornelius Lanczos that is an adaptation of power methods to find the m {\displaystyle m} "most
Lanczos_algorithm
Noise that reduces quantization error
frequencies. The ear is therefore very sensitive to distortion, or additional frequency content, but far less sensitive to additional random noise at all frequencies
Dither
Security and privacy measure
Database encryption can generally be defined as a process that uses an algorithm to transform data stored in a database into "cipher text" that is incomprehensible
Database_encryption
Set of cryptographic hash functions
SHA-2 (Secure Hash Algorithm 2) is a set of cryptographic hash functions designed by the United States National Security Agency (NSA) and first published
SHA-2
Machine learning technique for privacy-preserving training
information an individual training example can be inferred from the algorithm's output. Unlike standard SGD, DP-SGD's privacy loss accumulates over every
Differentially private stochastic gradient descent
Differentially_private_stochastic_gradient_descent
Hash function phenomenon
compact representative of particular input value used by data integrity algorithms to operate efficiently using this representative in place of the much
Hash_collision
Methods of safely sharing general data
visible even to internal analysts. Roughly, an algorithm is differentially private if an observer seeing its output cannot tell whether a particular individual's
Differential_privacy
entire sequence. BCJR equalizer: uses the BCJR algorithm (also called the Forward-backward algorithm) to find the maximum a posteriori (MAP) solution
Equalization_(communications)
Collection of efficiently-computable functions which emulate a random oracle
sees the final output which is a PRF of the two inputs -- a PRF of Alice's secret and Bob's secret. This enables transactions of sensitive cryptographic
Pseudorandom_function_family
Analysing a string of symbols, according to the rules of a formal grammar
may also contain semantic information.[citation needed] Some parsing algorithms generate a parse forest or list of parse trees from a string that is syntactically
Parsing
Computational benchmark
probability distributions. If there is a classical algorithm that can efficiently sample from the output of an arbitrary quantum circuit, the polynomial
Quantum_supremacy
Collection of hash functions
mp. Retrieved 2025-12-09. "RFC: perlfeaturedelta": "one-at-a-time hash algorithm ... [was added in version] 5.8.0" "perl: hv_func.h" Dillinger, Peter C
Jenkins_hash_function
Exponential function of an exponential function
Mathematics Vol. 7: 27–41 Chan, T. M. (1996), "Optimal output-sensitive convex hull algorithms in two and three dimensions", Discrete and Computational
Double_exponential_function
Type of machine learning model
behave as assistants. Biased or inaccurate training data can make an LLM's output less reliable. A software harness can provide LLMs with memory and access
Large_language_model
Statistical method in data analysis
clustering algorithm Dasgupta's objective Dendrogram Determining the number of clusters in a data set Hierarchical clustering of networks Locality-sensitive hashing
Hierarchical_clustering
Machine-learning process
distributional learning. Algorithms using these approaches have been applied to learning context-free grammars and mildly context-sensitive languages and have
Grammar_induction
Reinforcement learning method
learning algorithms refer to a category of reinforcement learning algorithms that leverage the disparity between the real output and the expected output of
Error-driven_learning
System with multiple networked computers
running time of the algorithm is much smaller than D communication rounds, then the nodes in the network must produce their output without having the possibility
Distributed_computing
1985 digital FM synthesizer
output, a single footswitch jack for a sustain pedal or portamento pedal and a BC1 breath controller jack. The DX21 has 4 operators and 8 algorithms,
Yamaha_DX21
Compact encoding of digital data
line coding, the means for mapping data onto a signal. Data compression algorithms present a space–time complexity trade-off between the bytes needed to
Data_compression
Set of all Pareto efficient situations
Genetic Algorithm Based on NSGA-II". Energies. 6 (3): 1439–55. doi:10.3390/en6031439. hdl:2117/18257. Nielsen, Frank (1996). "Output-sensitive peeling
Pareto_frontier
corresponding output of a function. Kernels encapsulate the properties of functions in a computationally efficient way and allow algorithms to easily swap
Kernel methods for vector output
Kernel_methods_for_vector_output
Method of graph analysis
party that collected sensitive graph data can process it using a differentially private algorithm and publish the output of the algorithm. The goal of differentially
Differentially private analysis of graphs
Differentially_private_analysis_of_graphs
Algorithm for modelling sequential data
encoder–decoder transformer, adapted from Formal Algorithms for Transformers. input: Encoder input t_e Decoder input t_d output: Array of probability distributions
Transformer_(deep_learning)
Machine learning technique
scan important features of a scene. These research developments inspired algorithms such as the Neocognitron and its variants. Meanwhile, developments in
Attention_(machine_learning)
Grouping a set of objects by similarity
analysis refers to a family of algorithms and tasks rather than one specific algorithm. It can be achieved by various algorithms that differ significantly
Cluster_analysis
Algorithm for generating pseudo-randomized numbers
A linear congruential generator (LCG) is an algorithm that yields a sequence of pseudo-randomized numbers calculated with a discontinuous piecewise linear
Linear_congruential_generator
Rendering method
technique for modeling light transport for use in a wide variety of rendering algorithms for generating digital images. On a spectrum of computational cost and
Ray_tracing_(graphics)
Chinese text-to-video model
30-second video generation, native 4K Ultra-HD resolution with 10-bit HDR output, two-channel stereo audio generation, and expanded keyframe editing support
Kling_AI
Mathematical concept
propagate and potentially amplify into substantial errors in the final output. Algorithms that are characterized as numerically stable are robust in the sense
Approximation_error
PMID 27182962. Lunter, G.; Goodson, M. (2010). "Stampy: A statistical algorithm for sensitive and fast mapping of Illumina sequence reads". Genome Research.
List of sequence alignment software
List_of_sequence_alignment_software
Open-source password management software
passwords or IDs and encrypt them through Blowfish symmetric block cipher algorithm or GNU Privacy Guard encryption. KDE Wallet Manager (KWallet) requires
KWallet
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OUTPUT SENSITIVE-ALGORITHM
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OUTPUT SENSITIVE-ALGORITHM
OUTPUT SENSITIVE-ALGORITHM
OUTPUT SENSITIVE-ALGORITHM
OUTPUT SENSITIVE-ALGORITHM
OUTPUT SENSITIVE-ALGORITHM
OUTPUT SENSITIVE-ALGORITHM
OUTPUT SENSITIVE-ALGORITHM
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