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The SPIKE algorithm is a hybrid parallel solver for banded linear systems developed by Eric Polizzi and Ahmed Sameh[1]^[2] The SPIKE algorithm deals with
SPIKE_algorithm
Topics referred to by the same term
Look up Spike, spike, spikes, spiking, or spiky in Wiktionary, the free dictionary. Spike, spikes, or spiking may refer to: The Spike (novel), a novel
Spike
Curve simplification algorithm
The Visvalingam–Whyatt algorithm, or simply the Visvalingam algorithm, is an algorithm that decimates a curve composed of line segments to a similar curve
Visvalingam–Whyatt_algorithm
based on graph partitioning Levinson recursion — for Toeplitz matrices SPIKE algorithm — hybrid parallel solver for narrow-banded matrices Cyclic reduction
List of numerical analysis topics
List_of_numerical_analysis_topics
Type of stochastic recurrent neural network
intriguing because of the locality and Hebbian nature of their training algorithm (being trained by Hebb's rule), and because of their parallelism and the
Boltzmann_machine
Artificial neural network that mimics neurons
ANN appeared to simulate non-algorithmic intelligent information processing systems. However, the notion of the spiking neural network as a mathematical
Spiking_neural_network
Journalism term
Spiking, in journalism, is the act of withholding a story from publication for editorial, commercial, or political reasons. A spiking may be permanent
Spike_(journalism)
American computer scientist
occasion of his 70th birthday. Sameh and Eric Polizzi developed the SPIKE algorithm, a hybrid parallel solver for banded linear systems.[citation needed]
Ahmed_Sameh
Subset of artificial intelligence
intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform
Machine_learning
Iterative method for finding maximum likelihood estimates in statistical models
In statistics, an expectation–maximization (EM) algorithm is an iterative method to find (local) maximum likelihood or maximum a posteriori (MAP) estimates
Expectation–maximization algorithm
Expectation–maximization_algorithm
Vector quantization algorithm minimizing the sum of squared deviations
efficient heuristic algorithms converge quickly to a local optimum. These are usually similar to the expectation–maximization algorithm for mixtures of Gaussian
K-means_clustering
Algorithm for supervised learning of binary classifiers
In machine learning, the perceptron is an algorithm for supervised learning of binary classifiers. A binary classifier is a function that can decide whether
Perceptron
Use of predictive analytics to direct policing
crime reports to make educated guesses of where crime is likely to spike. Algorithms are produced by taking into account past statistics, to process large
Predictive_policing
Practice and study of secure communication techniques
concerns cryptographic algorithms developed for a strictly constrained environment. The growth of Internet of Things (IoT) has spiked research into the development
Cryptography
Method by which information is represented in the brain
generating characteristic electrical pulses called action potentials: voltage spikes that can travel down axons. Sensory neurons change their activities by firing
Neural_coding
Bayesian variable selection technique in statistics
Spike-and-slab regression is a type of Bayesian linear regression in which a particular hierarchical prior distribution for the regression coefficients
Spike-and-slab_regression
Optimization algorithm
unconstrained mathematical optimization. It is a first-order iterative algorithm for minimizing a differentiable multivariate function. The idea is to
Gradient_descent
Heart rate measuring algorithm used in ECGs
The Pan–Tompkins algorithm is commonly used to detect QRS complexes in electrocardiographic signals (ECG). The QRS complex represents the ventricular
Pan–Tompkins_algorithm
Overview of and topical guide to machine learning
analogies Soft output Viterbi algorithm Solomonoff's theory of inductive inference SolveIT Software Spectral clustering Spike-and-slab variable selection
Outline_of_machine_learning
Non-linear digital filtering technique to remove noise
zero-padded boundaries. Code for a simple two-dimensional median filter algorithm might look like this: 1. allocate outputPixelValue[image width][image
Median_filter
Radicalization via social media algorithms
Algorithmic radicalization is the concept that recommender algorithms on popular social media sites, such as YouTube and Facebook, drive users toward
Algorithmic_radicalization
Field of machine learning
unsupervised learning. While supervised learning and unsupervised learning algorithms respectively attempt to discover patterns in labeled and unlabeled data
Reinforcement_learning
Concept concerning content amplification by recommendation systems
Algorithmic amplification describes increases in the distribution or visibility of content on digital platforms, arising from a combination of automated
Algorithmic_amplification
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
Spike sorting is a class of techniques used in the analysis of electrophysiological data. Spike sorting algorithms use the shape(s) of waveforms collected
Spike_sorting
Optimization algorithm for artificial neural networks
calculations. Strictly speaking, the term backpropagation refers only to an algorithm for efficiently computing the gradient, not how the gradient is used,
Backpropagation
Chess engine
Spike is a freeware chess engine developed by German programmers Ralf Schäfer and Volker Böhm. First released in 2004, the program operates as a standalone
Spike_(chess)
Machine learning calibration technique
probability, or give poor probability estimates. Platt scaling is an algorithm to solve the aforementioned problem. It produces probability estimates
Platt_scaling
Network of neurons with spiking signals
representation of an interconnected network of neurons or cells which exchange spiking signals. It was invented by Erol Gelenbe and is linked to the G-network
Random_neural_network
Ensemble learning method
ensemble methods that build models in parallel (such as bagging), boosting algorithms build models sequentially. Each new model in the sequence is trained to
Boosting_(machine_learning)
Biological process that adjusts the strength of connections between neurons in the brain
Tsodyks M (January 2001). "An algorithm for modifying neurotransmitter release probability based on pre- and postsynaptic spike timing". Neural Computation
Spike-timing-dependent plasticity
Spike-timing-dependent_plasticity
Measurement of power meeting specifications
amount of current, then suddenly stops demanding it, there will be a dip or spike in the voltage due to the inductances in the power supply line). Variations
Electric_power_quality
Density-based data clustering algorithm
clustering algorithm proposed by Martin Ester, Hans-Peter Kriegel, Jörg Sander, and Xiaowei Xu in 1996. It is a density-based clustering algorithm that does
DBSCAN
Machine learning algorithm
the most popular machine learning algorithms given their intelligibility and simplicity because they produce algorithms that are easy to interpret and visualize
Decision_tree_learning
Model-free reinforcement learning algorithm
Proximal policy optimization (PPO) is a reinforcement learning (RL) algorithm for training an intelligent agent. Specifically, it is a policy gradient
Proximal_policy_optimization
Optimization algorithm
behind stochastic approximation can be traced back to the Robbins–Monro algorithm of the 1950s. Today, stochastic gradient descent has become an important
Stochastic_gradient_descent
Semiconductor memory supply crisis
data compression algorithms List of DRAM manufacturers vLLM – open-source LLM inference engine that uses the PagedAttention algorithm to improve memory
2025–present global memory supply shortage
2025–present_global_memory_supply_shortage
Paradigm in machine learning that uses no classification labels
framework in machine learning where, in contrast to supervised learning, algorithms learn patterns exclusively from unlabeled data. Other frameworks in the
Unsupervised_learning
Computational statistics technique
also commonly called the acceptance-rejection method or "accept-reject algorithm" and is a type of exact simulation method. The method works for any distribution
Rejection_sampling
Algorithm for labeling clusters on a grid
The Hoshen–Kopelman algorithm is a simple and efficient algorithm for labeling clusters on a grid, where the grid is a regular network of cells, with
Hoshen–Kopelman_algorithm
Data clustering algorithm
CURE (Clustering Using REpresentatives) is an efficient data clustering algorithm for large databases[citation needed]. Compared with K-means clustering
CURE_algorithm
2014. "Explaining algorithm updates and data refreshes". 2006-12-23. Levy, Steven (February 22, 2010). "Exclusive: How Google's Algorithm Rules the Web"
Timeline_of_Google_Search
Housing shortage and inflation
Haru; Little, Ryan (October 15, 2022). "Rent Going Up? One Company's Algorithm Could Be Why". ProPublica. Retrieved August 21, 2024. Sisco, Josh (March
Housing crisis in the United States
Housing_crisis_in_the_United_States
Control loop feedback mechanism
action. This is because the digitized version of the algorithm produces a large unwanted spike when the setpoint is changed. If the setpoint is constant
PID_controller
Usage of artificial intelligence to generate music
human cognitive processes. A prominent feature is the capability of an AI algorithm to learn from historical data, such as in computer accompaniment technology
Artificial intelligence in music
Artificial_intelligence_in_music
Mathematical descriptions of the properties of certain cells in the nervous system
Biological neuron models, also known as spiking neuron models, are mathematical descriptions of the conduction of electrical signals in neurons. Neurons
Biological_neuron_model
Educational platform
lessons, accessible via its website and mobile app, using a recommendation algorithm to match students and teachers. Preply was founded in 2012 by Ukrainian
Preply
Algorithm for learning predictive state models from discrete sequences
Causal-state splitting reconstruction (CSSR) is an algorithm for learning a predictive model of a discrete-valued time series or other symbol sequence
CSSR_algorithm
Method for discovering interesting relations between variables in databases
relevant, but it could also cause the algorithm to have low performance. Sometimes the implemented algorithms will contain too many variables and parameters
Association_rule_learning
American rock band
bankruptcy, reBus was shelved and Patrick commenced on recording The Algorithm, which was released in August 2023. Richard Patrick played guitar with
Filter_(band)
Neuroscientific theory
aspect of causation in Hebb's work foreshadowed what is now known about spike-timing-dependent plasticity, which requires temporal precedence. Hebbian
Hebbian_theory
Automated recognition of patterns and regularities in data
from labeled "training" data. When no labeled data are available, other algorithms can be used to discover previously unknown patterns. KDD and data mining
Pattern_recognition
Mathematical technique
for locating the maxima of a density function, a so-called mode-seeking algorithm. Application domains include cluster analysis in computer vision and image
Mean_shift
Solving problems using biological models
evolutionary algorithms or in the context of swarm intelligence algorithms, are subdivided into Population Based Bio-Inspired Algorithms (PBBIA). They
Bio-inspired_computing
Type of feedforward neural network
function as its nonlinear activation function. However, the backpropagation algorithm requires that modern MLPs use continuous activation functions such as
Multilayer_perceptron
Set of methods for supervised statistical learning
vector network is a supervised max-margin model with associated learning algorithms that analyze data for classification and regression analysis. Developed
Support_vector_machine
the scheme was deemed fundamentally flawed by lawyers in 2014 as an algorithm was used to match welfare recipients' reported earnings with averaged
List of The Weekly with Charlie Pickering episodes
List_of_The_Weekly_with_Charlie_Pickering_episodes
Method of machine learning
requiring the need of out-of-core algorithms. It is also used in situations where it is necessary for the algorithm to dynamically adapt to new patterns
Online_machine_learning
Statistical method in data analysis
begins with each data point as an individual cluster. At each step, the algorithm merges the two most similar clusters based on a chosen distance metric
Hierarchical_clustering
Adaptive boosting based classification algorithm
AdaBoost (short for Adaptive Boosting) is a statistical classification meta-algorithm formulated by Yoav Freund and Robert Schapire in 1995, who won the 2003
AdaBoost
Method of detecting shapes within images
in a so-called accumulator space that is explicitly constructed by the algorithm for computing the Hough transform. Mathematically it is simply the Radon
Hough_transform
Method of data analysis
typically involve the use of a computer-based algorithm for computing eigenvectors and eigenvalues. These algorithms are readily available as sub-components
Principal_component_analysis
Biological theory of intelligence
mammalian (in particular, human) brain. At the core of HTM are learning algorithms that can store, learn, infer, and recall high-order sequences. Unlike
Hierarchical_temporal_memory
Algorithm for finding density based clusters in spatial data
Ordering points to identify the clustering structure (OPTICS) is an algorithm for finding density-based clusters in spatial data. It was presented in
OPTICS_algorithm
Machine learning technique
reward function to improve an agent's policy through an optimization algorithm like proximal policy optimization. RLHF has applications in various domains
Reinforcement learning from human feedback
Reinforcement_learning_from_human_feedback
Model-free reinforcement learning algorithm
Q-learning is a reinforcement learning algorithm that trains an agent to assign values to its possible actions based on its current state, without requiring
Q-learning
Applications Group at Alnwick and genetic algorithms; the early 1980s WiSARD neural network from the RAMnets algorithm at Brunel University London; Randall
List_of_Equinox_episodes
Machine learning technique
introduced the view of boosting algorithms as iterative functional gradient descent algorithms. That is, algorithms that optimize a cost function over
Gradient_boosting
Messaging and VoIP service owned by Meta
transform (MDCT) and linear predictive coding (LPC) audio compression algorithms. WhatsApp uses Opus at 8–16 kHz sampling rates. On November 14, 2016,
Class of reinforcement learning algorithm
In reinforcement learning (RL), a model-free algorithm is an algorithm which does not estimate the transition probability distribution (and the reward
Model-free (reinforcement learning)
Model-free_(reinforcement_learning)
Statistics and machine learning technique
multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone. Unlike
Ensemble_learning
Property of a model
learning algorithms from generalizing beyond their training set: The bias error is an error from erroneous assumptions in the learning algorithm. High bias
Bias–variance_tradeoff
Subfield of computer science and mathematics
Group on Algorithms and Computation Theory (SIGACT) provides the following description: TCS covers a wide variety of topics including algorithms, data structures
Theoretical_computer_science
2012 video game
and received three nominations at the 16th Annual D.I.C.E. Awards. At the Spike Video Game Awards 2011, it was announced that Deadmau5 would be contributing
Sound_Shapes
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
Method in machine learning
learning (ML) ensemble meta-algorithm designed to improve the stability and accuracy of ML classification and regression algorithms. It also reduces variance
Bootstrap_aggregating
Pornographic video sharing website
Although nudity is officially banned on TikTok, the platform's monitoring algorithm is not perfect, sometimes leading to pornographic content being made publicly
XHamster
Type of clustering of data points
improved by J.C. Bezdek in 1981. The fuzzy c-means algorithm is very similar to the k-means algorithm: Choose a number of clusters. Assign coefficients
Fuzzy_clustering
Type of imaging sensor
incorporation of motion-compensation models and traditional clustering algorithms. Potential applications include most tasks classically fitting conventional
Event_camera
Social platform
and algorithmic choice as core features of Bluesky. The platform offers a "marketplace of algorithms" where users can choose or create algorithmic feeds
Bluesky
International volleyball tournament
three weeks, each team plays four times in a table that is set up by an algorithm, with all teams playing 12 times in total at the end of the first phase
2026 FIVB Men's Volleyball Nations League
2026_FIVB_Men's_Volleyball_Nations_League
is a supervised synaptic learning algorithm which is applied when the information is encoded in spatiotemporal spiking patterns. This is an advancement
Tempotron
Decompression algorithm
The reduced gradient bubble model (RGBM) is an algorithm developed by Bruce Wienke for calculating decompression stops needed for a particular dive profile
Reduced_gradient_bubble_model
Journalistic adage on questions in headlines
Spiral of silence Digital divide/ Political polarization Algorithmic radicalization Youth Algorithmic amplification Echo chamber Fake news website Post-truth
Betteridge's_law_of_headlines
Statistical method
interpreted as an outlier detection method. It is a non-deterministic algorithm in the sense that it produces a reasonable result only with a certain
Random_sample_consensus
Machine-learning process
pattern languages. The simplest form of learning is where the learning algorithm merely receives a set of examples drawn from the language in question:
Grammar_induction
Increase in stock value
different goals issuers and investors have. The problem with developing algorithms to determine underpricing is dealing with noisy, complex, and unordered
IPO_underpricing_algorithm
International volleyball tournament
three weeks, each team plays four times in a table that is set up by an algorithm, with all teams playing 12 times in total at the end of the first phase
2026 FIVB Women's Volleyball Nations League
2026_FIVB_Women's_Volleyball_Nations_League
speed and modularity Deeplearning4j – Java library for deep learning algorithms on the Java virtual machine DeepSpeed – deep learning optimization library
Lists of open-source artificial intelligence software
Lists_of_open-source_artificial_intelligence_software
Term in computer science
(including autonomous driving), and computational physics. Collision detection algorithms can be divided into operating on 2D or 3D spatial objects. Collision detection
Collision_detection
American singer and songwriter (1958–2009)
Murray. His death caused unprecedented surges in internet traffic and a spike in music sales. Posthumous Jackson releases include the documentary Michael
Michael_Jackson
Mathematical function conceived as a crude model
Hebbian learning, known as spike-timing-dependent plasticity, was developed to account for the precise timing of neuron spikes. This form of learning has
Artificial_neuron
Branch of artificial intelligence
system called SPSS[link removed] and a long-term planning system called Spike [citation needed]. Action description language – Robot programming language
Automated planning and scheduling
Automated_planning_and_scheduling
Flaw in mathematical modelling
learning algorithm is trained using some set of "training data": exemplary situations for which the desired output is known. The goal is that the algorithm will
Overfitting
Social trading platform based in Singapore
machine-reading algorithms to scan stock exchange filings. The scan is done every minute, and the information is posted almost instantly on the app. Spiking users
Spiking_(fintech)
Voters who are poorly informed
Spiral of silence Digital divide/ Political polarization Algorithmic radicalization Youth Algorithmic amplification Echo chamber Fake news website Post-truth
Low_information_voter
Israeli made smartphone application
user's exposure to phone radiation, and alerts users when radiation levels spike. Tawkon was founded by Israeli entrepreneurs Gil Friedlander, Amit Lubovsky
Tawkon
Type of artificial neural network
change according to the derivative of the activation function, and so this algorithm represents a backpropagation of the activation function. Circa 1800, Legendre
Feedforward_neural_network
Adaptive algorithm
Constant false alarm rate (CFAR) detection is a common form of adaptive algorithm used in radar systems to detect target returns against a background of
Constant_false_alarm_rate
Email service developed by Google
lot like the future of email", Pierce wrote that there was "plenty of algorithm tweaking and design condensing to do", with particular attention needed
Inbox_by_Gmail
travel, tourism, insurance
SPIKE ALGORITHM
SPIKE ALGORITHM
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SPIKE ALGORITHM
SPIKE ALGORITHM
SPIKE ALGORITHM
travel, tourism, insurance