1,686 technical terms and definitions
data reordering and prefetch generation in compiler, data reordering prefetch, reordering prefetch generation, prefetch generation compiler, data reordering, reordering prefetch
Data Reordering and Prefetch Generation in Compiler Introduction & Motivation Data Reordering and Prefetch Generation in Compiler addresses a central problem in ml-compiler…
training
Data replay is reintroduction of selected past data during later training phases to preserve learned capabilities - Replay buffers protect important knowledge when models continue…
training techniques
Data Retention is policy framework that defines how long data is stored before deletion or archival - It is a core method in modern semiconductor AI serving and trustworthy-ML…
Data Science in Medicine & Biomedical Analysis: Statistical Learning and Clinical Applications 1. Epidemiology and Statistical Analysis Epidemiology studies disease distribution…
data serialization formats, data serialization, serialization formats
Data Serialization Formats Introduction & Motivation Data Serialization Formats addresses a central problem in programming process control and format-overhead-size prediction: how…
documentation
Data sheets for datasets is the dataset documentation framework that records origin, composition, collection process, and ethical constraints - it provides provenance and context…
distributed training
Data shuffling at scale is the large-distributed randomization of sample order to prevent correlation bias during training - it must balance statistical randomness quality…
Data Smells Automated Antipattern Static Analysis Introduction & Motivation Data Smells Automated Antipattern Static Analysis addresses a central problem in {subject} assurance…
Data Standardization and Normalization Introduction & Motivation Data Standardization and Normalization addresses a central problem in {subject} assurance and {target} management…
legal
Data subject rights are the legal rights granted to individuals under GDPR (and similar regulations) regarding the personal data that organizations collect and process about them.…
nlp
Data-to-text is the NLP task of generating natural language descriptions from structured data — automatically converting tables, databases, knowledge bases, and other structured…
Data Type and Format Consistency Introduction & Motivation Data Type and Format Consistency addresses a central problem in {subject} assurance and {target} management: how…
Data Completeness Validation Introduction & Motivation Data Completeness Validation addresses a central problem in {subject} assurance and {target} management: how to Improve…
Data Validation Rules and Constraints Introduction & Motivation Data Validation Rules and Constraints addresses a central problem in {subject} assurance and {target} management…
Data Valuation for Active Learning Introduction & Motivation Data Valuation for Active Learning addresses a central problem in {subject} learning and efficient {target}…
dataset versioning, data version control, dvc, lakefs, data lineage versioning
Data versioning definition and system boundary. Data versioning records the identity, content, metadata, parentage, and lifecycle of datasets so a team can reproduce what existed…
data versioning and reproducibility, data versioning reproducibility, data versioning, versioning reproducibility
Data Versioning and Reproducibility Introduction & Motivation Data Versioning and Reproducibility addresses a central problem in ml-ops process control…
cloud data warehouse, enterprise data warehouse, analytical database, olap warehouse
Data warehouse definition and system boundary. A data warehouse is a centralized analytical database that publishes structured, governed, historically consistent data for complex…
data warehouse olap, data warehouse, warehouse olap
Data Warehouse OLAP Introduction & Motivation Data Warehouse OLAP addresses a central problem in systems process control and query-latency-optimization prediction: how to Predict…
data2vec General Self-Supervised Learning Across Modalities Introduction & Motivation data2vec General Self-Supervised Learning Across Modalities addresses a central problem…
database backup recovery plan, database backup recovery, backup recovery plan, database backup, backup recovery, recovery plan
Database Backup Recovery Plan Introduction & Motivation Database Backup Recovery Plan addresses a central problem in cloud process control and backup-strategy-full-incremental…
database connection pooling, database connection, connection pooling
Database Connection Pooling Introduction & Motivation Database Connection Pooling addresses a central problem in ml-inference process control and connection-acquisition-latency…
database migration strategy, database migration, migration strategy
Database Migration Strategy Introduction & Motivation Database Migration Strategy addresses a central problem in ml-ops process control and migration-time-hours prediction: how…
database migration strategy, database migration, migration strategy
Database Migration Strategy Introduction & Motivation Database Migration Strategy addresses a central problem in cloud process control and migration-downtime-zero-downtime…
tool use
Database querying is structured retrieval of information from databases using generated query operations - The model constructs queries against schemas retrieves records…
database replication consistency, database replication, replication consistency
Database Replication Consistency Introduction & Motivation Database Replication Consistency addresses a central problem in ml-inference process control…
database replication consistency, database replication, replication consistency
Database Replication Consistency Introduction & Motivation Database Replication Consistency addresses a central problem in cloud process control…
database sharding strategy, database sharding, sharding strategy
Database Sharding Strategy Introduction & Motivation Database Sharding Strategy addresses a central problem in cloud process control and shard-key-distribution-balance prediction…
Relational Databases, Transactions, Concurrency, and B+ Trees A database management system turns shared persistent storage into a dependable abstraction. Applications issue…
lakehouse, mlflow
Databricks is the unified data intelligence platform founded by the creators of Apache Spark that combines data engineering, data warehousing, and machine learning — pioneering…
architecture, deep, learning, processing
Dataflow is an execution model in which a computation is expressed as a graph of operations, and each operation runs as soon as its input data is available, rather than in a fixed…
computing, paradigm, architecture, execution
Dataflow Computing Paradigm is an execution model where computation is driven by data availability rather than program counter sequencing, enabling massive parallelism through…
dataflow accelerator architecture design, dataflow accelerator architecture, accelerator architecture design, dataflow accelerator, accelerator architecture, architecture design
Dataflow Accelerator Architecture Design Introduction & Motivation Dataflow Accelerator Architecture Design addresses a central problem in ml-hardware process control…
dataflow analysis in compilers, dataflow analysis compilers, dataflow analysis, analysis compilers
Dataflow Analysis in Compilers Introduction & Motivation Dataflow Analysis in Compilers addresses a central problem in compiler-optimization process control and analysis-precision…
dataflow programming, dataflow graph, stream processing, dataflow execution
Dataflow architecture definition and engineering boundary. executes an operation when its required data tokens are available rather than advancing primarily through a single…
spatial computing hardware, coarse grain reconfigurable, cgra dataflow, dataflow processor design
Dataflow Architecture Computing is the processor design paradigm where instructions execute as soon as their input operands are available (data-driven execution) rather than…
dataflow computing and architectures, dataflow computing architectures, dataflow computing, computing architectures
Dataflow Computing and Architectures Introduction & Motivation Dataflow Computing and Architectures addresses a central problem in dataflow-computing process control…
wave computing, spatial architecture computing, coarse grain reconfigurable array cgra, stream dataflow architecture
Dataflow Processor Architecture: Spatial Computing via Coarse-Grained Reconfigurable Arrays — compute elements directly mapped to hardware nodes with data-driven execution model…
corpus, training data
Training Data for LLMs Pretraining Datasets Large language models are pretrained on massive text corpora—often trillions of tokens from diverse sources. Common Pretraining Sources…
data quality
Dataset Bias refers to systematic errors or skews in training data that cause models to learn unintended, misleading patterns — the model captures the bias in the data rather than…
Dataset Cartography and Data Maps for Training Dynamics Introduction & Motivation Dataset Cartography and Data Maps for Training Dynamics addresses a central problem…
distributed training
Dataset sharding is the partitioning of training data into non-overlapping subsets assigned across distributed workers - it ensures balanced workload distribution, minimizes…
mlops
Dataset versioning is the practice of creating immutable, traceable dataset snapshots for every training and evaluation run - it ensures model results can be reproduced even when…
huggingface, loading
Hugging Face Datasets is a lightweight Python library for efficiently loading, processing, and sharing datasets for machine learning — using Apache Arrow as its in-memory backend…
dataset, documentation
Datasheets for Datasets is the standardized documentation framework for machine learning training datasets that captures motivation, composition, collection process…
packaging
Date code is the encoded manufacturing-time identifier printed or marked on packages to indicate production period for traceability - it supports quality control, inventory…
Date-Time Parsing and Normalization Introduction & Motivation Date-Time Parsing and Normalization addresses a central problem in {subject} assurance and {target} management: how…
evaluation
Date Understanding is the NLP task and benchmark category that evaluates a model's ability to reason about temporal expressions, calendar arithmetic, event ordering, and duration…
d2d variation, daily drift
Day-to-Day Variation (D2D) in semiconductor manufacturing refers to process parameter fluctuations between production days caused by environmental, equipment, or operational…
dbn, recommendation systems
DBN is dynamic Bayesian network click model that captures sequential examination and satisfaction behavior - It extends simpler click models with richer latent user-state…