Average Precision
Average precision (AP) is an evaluation metric that summarizes the precision-recall curve of a ranked list into a single number between 0 and 1, equal to the area under that curve.
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Showing 1-14 of 14 articles
Candidate Generation
Candidate generation is the first stage in a multi-stage recommendation system or information retrieval pipeline.
Embeddings
In machine learning, an embedding is a learned representation that maps an input into a vector, usually so that a downstream model or comparison rule can use relationships encoded in the vector's geometry.
HNSW
Hierarchical Navigable Small World (HNSW) is an approximate nearest-neighbor search algorithm that indexes high-dimensional vectors in a multi-layer proximity graph and answers similarity queries in expected…
Hashing
Hashing in machine learning is the use of hash functions to map data of arbitrary size (a word, a URL, a document, a vector) into a fixed-size integer range, trading a small and controllable amount of…
Information Retrieval
Information retrieval (IR) is the study and engineering of systems that identify material likely to satisfy an information need.
Matryoshka representation learning
Matryoshka Representation Learning (MRL) is a representation learning technique that trains a single neural model to produce embedding vectors which remain useful when truncated to many smaller dimensionalities
Question answering
Question answering (QA) is the task of producing an answer to a question, usually expressed in natural language.
Ranking
Ranking in machine learning, often called learning to rank (LTR), is the supervised task of ordering a set of items by relevance to a query
Recommender System
A recommender system (also called a recommendation system or recommendation engine) is an information filtering system that predicts the preference a user would give to an item and uses those predictions to…
Similarity Measure
A similarity measure (also called a similarity function or similarity metric) is a real-valued function that quantifies the degree of resemblance between two objects, returning a large value when the objects…
Tower
In deep learning, a tower is a self-contained sub-network inside a larger model that encodes one specific input or feature group into an output, usually an embedding
Two-Tower Model
The two-tower model, also known as the dual encoder, bi-encoder, or Siamese network for retrieval, is a neural network architecture that encodes a query and a candidate item with two separate sub-networks…
Vector database
A vector database is a database that stores data as high-dimensional vectors (numerical embeddings produced by a machine learning model) and retrieves records by similarity rather than exact match