Abstract: Approximate K Nearest Neighbor (AKNN) search in high-dimensional spaces is a critical yet challenging problem. In AKNN search, distance computation is the core task that dominates the ...

Embedding-based search outperforms traditional keyword-based methods across various domains by capturing semantic similarity using dense vector representations and approximate nearest neighbor (ANN) ...

How's your moon knowledge? Full, half, or total eclipse? When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. It's no surprise that throughout the ...

KEYWORDS: Vehicle Routing Problem (VRP), Google Maps Distance Matrix API, Python, Pulp, Mixed Integer Linear Programming, Transportation, Optimisation Problem, Time Window, Mathematical Modelling ...

A sophisticated cyber-espionage attack used by notorious Russian advanced persistent threat (APT) Fancy Bear at the outset of the current Russia-Ukraine war demonstrates a novel attack vector that a ...

The bleeding edge: In-memory processing is a fascinating concept for a new computer architecture that can compute operations within the system's memory. While hardware accommodating this type of ...

Graph-based methods have become increasingly important in data retrieval and machine learning, particularly in nearest neighbor (NN) search. NN search helps identify data points closest to a given ...

ABSTRACT: Using resting-state functional magnetic resonance imaging (fMRI) technology to assist in identifying brain diseases has great potential. In the identification of brain diseases, graph-based ...

PyTorch + HuggingFace code for RetoMaton: "Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval" (ICML 2022), including an implementation of kNN-LM and kNN-MT ...