15,418 technical terms and definitions
Machine Learning Foundations: Loss Functions, Gradient Descent, Regularization, and Kernel Methods Machine learning builds predictive models from data by minimizing a loss…
metrology, scatterometry, RCWA simulation, library matching, neural network inference, critical dimension measurement, GAA CFET metrology, optical critical dimension, synthetic training data
Machine learning-based optical critical dimension measurement (ML-OCD) replaces the traditional library-matching or regression math behind scatterometry with a trained machine…
ml-ocd, metrology
ML-OCD (Machine Learning Optical Critical Dimension) is the application of machine learning to scatterometry data analysis — using neural networks, random forests, or other ML…
machine learning test generation, machine learning test, learning test generation, machine learning, learning test, test generation
Machine Learning Test Generation Introduction & Motivation Machine Learning Test Generation addresses a central problem in verification process control…
machine learning training convergence speed prediction, machine learning training, learning training convergence, training convergence speed, machine learning
Machine Learning Training Convergence Speed Prediction with Machine Learning Introduction & Motivation Machine Learning Training Convergence Speed Prediction with Machine Learning…
machine model mm, esd test model, mm esd standard
Machine Model testing stresses a device with a discharge that looks nothing like a person touching a pin: it models a charged piece of automated equipment, a test handler…
machine model esd charging discharge prediction, machine model esd, model esd charging, esd charging discharge, charging discharge prediction, machine model, model esd
Machine Model ESD Charging Discharge Prediction with Machine Learning Introduction & Motivation Machine Model ESD Charging Discharge Prediction with Machine Learning addresses…
machine reading comprehension, machine reading, reading comprehension
Machine Reading Comprehension Introduction & Motivation Machine Reading Comprehension addresses a central problem in nlp process control and reading-comprehension-span-extraction…
machine translation low resource, machine translation low, translation low resource, machine translation, translation low, low resource
Machine Translation Low Resource Introduction & Motivation Machine Translation Low Resource addresses a central problem in nlp process control…
machine translation neural, machine translation, translation neural
Machine Translation Neural Introduction & Motivation Machine Translation Neural addresses a central problem in nlp process control and translation-accuracy-metric prediction: how…
machine translation quality evaluation, machine translation quality, translation quality evaluation, machine translation, translation quality, quality evaluation
Machine Translation Quality Evaluation Introduction & Motivation Machine Translation Quality Evaluation addresses a central problem in nlp process control…
machine translation, seq2seq neural machine, bleu bpe cat meteor nlp nmt, machine translation seq2seq & neural machine translation, machine translation seq2seq, translation seq2seq
Machine Translation: Seq2Seq & Neural Machine Translation Introduction & Motivation Machine Translation: translate text between languages. Neural Machine Translation: end-to-end…
machine vision lighting uniformity drift prediction machine learning, machine vision, lighting uniformity drift, led, machine vision lighting, vision lighting
Machine Vision Lighting Uniformity Drift Prediction with Machine Learning Introduction & Motivation Machine Vision Lighting Uniformity Drift Prediction with Machine Learning…
macro inspection false positive rate prediction machine learning, macro inspection, false positive rate, macro inspection false positive rate prediction, false positive
Macro Inspection False Positive Rate Prediction with Machine Learning Introduction & Motivation Macro Inspection False Positive Rate Prediction with Machine Learning addresses…
neural architecture search
Macro Search Space is architecture-search design over global network structure such as stage depth and connectivity. - It controls high-level skeleton choices beyond local…
Macro Search Space Exploration Introduction & Motivation Macro Search Space Exploration addresses a central problem in automated design of nas architectures: how to Automatically…
Macro Search Space Exploration (Extended Study) Introduction & Motivation Macro Search Space Exploration (Extended Study) addresses a central problem in automated design of nas…
Macro Search Space Exploration (Extended Study) Introduction & Motivation Macro Search Space Exploration (Extended Study) addresses a central problem in automated design of nas…
Masked Autoencoders MAE Are Scalable Vision Learners Introduction & Motivation Masked Autoencoders MAE Are Scalable Vision Learners addresses a central problem in selfsupervised…
mae, computer vision
MAE pre-training (Masked Autoencoders) is the efficient MIM approach that encodes only visible patches and reconstructs masked patches with a lightweight decoder - by avoiding…
code ai
Magic Number Detection is the automated identification of literal numeric constants and undocumented string literals hardcoded directly in program logic — detecting the code smell…
failure analysis advanced
Magnetic Field Imaging is a technique that maps magnetic emissions from current flow to localize active failure sites - It reveals abnormal current paths and hotspots without…
magnetic tunnel junction, magnetic tunnel, tunnel junction
Magnetic Tunnel Junction Introduction & Motivation Magnetic Tunnel Junction addresses a central problem in emerging-storage process control and tunneling-magnetoresistance-ratio…
magnetic tunnel junction read disturb and retention, magnetic tunnel junction, tunnel junction read, junction read disturb, read disturb retention, magnetic tunnel, read disturb
Magnetic Tunnel Junction Read Disturb and Retention Introduction & Motivation Magnetic Tunnel Junction Read Disturb and Retention addresses a central problem in memory process…
dielectric permeability tensor magnetic field bias, polar longitudinal transverse kerr effect geometry, complex faraday rotation angle ellipticity, magnetic thin film domain metrology spintronics
Magneto-Optical Kerr Effect (MOKE) Formalism: Complex Faraday Rotation Tensors and In-Situ Magnetic Thin-Film Metrology 1. Introduction: Magneto-Optical Effects in Magnetic…
magnetoresistive ram design, magnetoresistive ram, ram design
Magnetoresistive RAM Design Introduction & Motivation Magnetoresistive RAM Design addresses a central problem in emerging-storage process control and write-latency-nanoseconds…
magnetoresistive sensor offset drift prediction machine learning, magnetoresistive sensor, offset drift prediction, gmr mr, magnetoresistive sensor offset, sensor offset
Magnetoresistive Sensor Offset Drift Prediction with Machine Learning Introduction & Motivation Magnetoresistive Sensor Offset Drift Prediction with Machine Learning addresses…
Magnitude-Based Weight Pruning Introduction & Motivation Magnitude-Based Weight Pruning addresses a central problem in reducing the size and cost of compression models: how…
Magnitude-Based Weight Pruning (Extended Study) Introduction & Motivation Magnitude-Based Weight Pruning (Extended Study) addresses a central problem in reducing the size and cost…
Magnitude-Based Weight Pruning (Extended Study) Introduction & Motivation Magnitude-Based Weight Pruning (Extended Study) addresses a central problem in reducing the size and cost…
model optimization
Neural network pruning removes weights, channels, or entire structural units from a trained model to reduce its size and computational cost while preserving as much of its…
model optimization
Neural network pruning removes weights, channels, or entire structural units from a trained model to reduce its size and computational cost while preserving as much of its…
magnn, graph neural networks
MAGNN is metapath aggregated graph neural networks for heterogeneous graph representation learning. - It captures semantic context by aggregating along multiple typed metapath…
magnonic computing and circuits, magnonic computing circuits, magnonic computing, computing circuits
Magnonic Computing and Circuits Introduction & Motivation Magnonic Computing and Circuits addresses a central problem in magnonic-computing process control and magnon-latency…
Mahalanobis Distance Anomaly Detection Introduction & Motivation Mahalanobis Distance Anomaly Detection addresses a central problem in anomaly detection and {target} scoring: how…
Robust Mahalanobis Distance with Shrinkage Covariance Introduction & Motivation Robust Mahalanobis Distance with Shrinkage Covariance addresses a central problem in anomaly…
Mahalanobis Distance in Deep Feature Space for OOD Introduction & Motivation Mahalanobis Distance in Deep Feature Space for OOD addresses a central problem in anomaly detection…
reasoning
Maieutic prompting is a reasoning technique inspired by the Socratic method where the model recursively generates explanations for its own statements, building a tree of logically…
doe
A main effect in DOE is the direct impact of changing a single factor on the response variable, averaged across all levels of the other factors. It answers the question: "What…
quality & reliability
Main Effect is the average response change attributable to one factor across levels of other factors - It is a core method in modern semiconductor statistical experimentation…
etch
The main etch is the primary phase of a plasma etch process responsible for bulk material removal — etching through the majority of the target film's thickness with the required…
production
The mainframe is the main body of a cluster tool housing the transfer chamber, vacuum system, and module interfaces, serving as the structural and functional core of the equipment…
manufacturing operations
Maintainability is the ease and speed with which equipment can be inspected, serviced, and restored to operation - It strongly affects downtime duration and maintenance labor…
code ai
Maintainability Index (MI) is a composite software metric that aggregates Halstead Volume, Cyclomatic Complexity, and Lines of Code into a single 0-100 score representing…
manufacturing operations
Maintenance Prevention is designing equipment and processes to eliminate recurrent maintenance burdens at the source - It shifts reliability improvement upstream into equipment…
maintenance technician response time prediction, maintenance technician response, technician response time, response time prediction, maintenance technician, response time
Maintenance Technician Response Time Prediction with Machine Learning Introduction & Motivation Maintenance Technician Response Time Prediction with Machine Learning addresses…
maintenance technician task duration prediction machine learning, maintenance technician, task duration prediction, cmms pm, maintenance technician task, technician task
Maintenance Technician Task Duration Prediction with Machine Learning Introduction & Motivation Maintenance Technician Task Duration Prediction with Machine Learning addresses…
production
Maintenance time tracking is the measurement of end-to-end maintenance cycle durations to identify where downtime is consumed and how repair response can be accelerated - it…
manufacturing operations
Maintenance Window is a planned time slot reserved for equipment maintenance activities with minimal production disruption - It is a core method in modern semiconductor operations…
maintenance work order backlog risk prediction, maintenance work order, work order backlog, order backlog risk, backlog risk prediction, maintenance work, work order
Maintenance Work Order Backlog Risk Prediction with Machine Learning Introduction & Motivation Maintenance Work Order Backlog Risk Prediction with Machine Learning addresses…