3,135 articles
Meet-in-the-middle
Meet-in-the-middle is an algorithmic technique that splits a search space into two halves searched separately and combined by matching, reducing 2^n time to 2^(n/2) at the cost of memory.
Megatron-LM
Megatron-LM is an open-source PyTorch library from NVIDIA for training large transformer language models across many GPUs, built on tensor, pipeline, and data parallelism since 2019.
MEGNet
MEGNet (MatErials Graph Network) is a graph neural network for predicting properties of molecules and crystals, introduced in December 2018 by Shyue Ping Ong's Materials Virtual Lab at UC San Diego.
Meltano
Meltano is an open-source, MIT-licensed, Python declarative ELT engine running Singer taps and targets, created inside GitLab in 2018, spun out with a $4.2M GV seed in 2021, renamed Arch Data, and acquired by Matatika in December 2025.
Membership inference
Membership inference is a privacy attack on machine learning models that determines whether a given record was in the training data, first demonstrated by Reza Shokri and colleagues in 2016.
Membership inference attack
A membership inference attack (MIA) determines whether a data record was part of a machine learning model's training dataset, revealing sensitive information such as health conditions.
Memcached
Memcached is a free and open source distributed memory object caching system that speeds up dynamic web applications by reducing database load, created by Brad Fitzpatrick for LiveJournal in 2003.
Memetic algorithm
A memetic algorithm is a population-based metaheuristic combining an evolutionary framework with local-search operators that refine individual solutions, introduced by Pablo Moscato in 1989 for hard optimization problems.
Memoization
Memoization is an optimization technique in which a function stores results of previous calls and returns them instead of recomputing, as proposed by Donald Michie in 1967.
Memory network (machine learning)
A memory network, or memory-augmented neural network, is a neural network architecture with an external memory the model reads and writes, introduced for question answering in 2014.
Merge sort
Merge sort is a divide-and-conquer, comparison-based sorting algorithm that recursively sorts halves and merges them, with a guaranteed O(n log n) worst case and stable output.
Merge tree
A merge tree is a topological data analysis structure that records how the connected components of a scalar function's sublevel sets merge as the threshold value rises.
Merkle tree
A Merkle tree, also called a Merkle hash tree, is a hash-based binary tree, introduced by Ralph Merkle in 1979, whose root hash tamper-evidently commits to a dataset.
Mersenne Twister
The Mersenne Twister (MT) is a pseudorandom number generator invented by Makoto Matsumoto and Takuji Nishimura in 1997, producing uniform 32-bit integers with the prime period 2^19937−1.
Mesh generation
Mesh generation is the computational geometry technique that subdivides a geometric domain into discrete elements such as triangles and tetrahedra, so partial differential equations can be solved by finite element methods.
Mesh optimization
Mesh optimization is a family of computational geometry methods that improve polygonal meshes by changing vertex positions, connectivity, and element count, introduced by Hugues Hoppe and colleagues in 1993.
Message passing neural network
A message passing neural network (MPNN) is a graph neural network framework, formalized in 2017, that exchanges messages along edges and excels at molecular property prediction.
Message queue
A message queue is a named destination in a messaging system where messages sent by one program accumulate in storage until another program retrieves and processes them, letting the programs run at different speeds and times.
Meta-optimization
Meta-optimization is an optimization technique in which an outer optimization loop tunes the parameters, hyperparameters, or design of another optimization algorithm to improve its performance on a class of problems.
Meta-reinforcement learning
Meta-reinforcement learning (meta-RL) trains a reinforcement learning agent across a distribution of tasks so it can adapt to new tasks from small amounts of experience.
Metabase
Metabase is an open-source business intelligence platform founded in 2014 in San Francisco that connects to existing databases, letting non-technical users build queries, charts, and dashboards without writing SQL.
Metadata
Metadata, also known as metainformation, is structured information that describes the characteristics of data, such as a file's format or a dataset's schema, often summarized as data about data.
Metadata management
Metadata management: collecting, organizing, and governing metadata (data about data) describing an organization's data assets, typically via data catalogs. Covers active metadata, vendor landscape, Gartner Magic Quadrant history, standards barriers, and AI-driven context delivery.
Metaflow
Metaflow is Netflix's open-source Python framework for building and deploying AI/ML systems as flows of checkpointed steps, runtime-agnostic across AWS, Azure, GCP, Kubernetes, Argo, and Airflow, Apache 2.0 licensed.
Metamodeling (simulation)
Metamodeling builds a simplified mathematical surrogate that approximates the input–output behavior of an expensive computer simulation, so optimization, sensitivity analysis, and uncertainty quantification can run on the surrogate instead of the simulator.
Metaphone
Metaphone is a phonetic algorithm published by Lawrence Philips in 1990 that codes English words by pronunciation, so similarly sounding words and names match despite different spellings; it replaced Soundex.
Metaplane
Metaplane is a data observability platform founded in 2019 by Kevin Hu, Guru Mahendran, and Peter Casinelli (YC Winter 2020), offering ML anomaly detection and column-level lineage; raised $22.2M and was acquired by Datadog in April 2025.
Metric learning
Metric learning, also called distance metric learning, is a machine learning approach that learns a task-specific distance function, typically a Mahalanobis distance, for kNN, clustering, and retrieval.
Mi Zhang
Mi Zhang is a Chinese-born American computer scientist and Associate Professor at The Ohio State University whose research runs machine learning on resource-limited devices such as smartphones and IoT hardware.
Micro-batching
Micro-batching processes streaming data in small, frequent batches (roughly 100 ms to a few seconds), Spark Structured Streaming's default mode, offering exactly-once fault tolerance and batch-engine simplicity at the cost of batch-boundary latency.