Nearest Neighbour
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
Distributional Approximate Nearest Neighbour Search for Uncertainty-Aware Retrieval
Announce Type: new Abstract: Approximate Nearest Neighbour search indices form the backbone of real-world recommender systems, enabling real-time candidate retrieval over million-item catalogues. Typically, a single point estimate embedding is learnt for every user and every item. At serving time, the user embedding queries the index for relevant items.
Universal consistency of the $k$-NN rule in metric spaces and Nagata dimension. III
Announce Type: replace Abstract: We establish the last missing link allowing to describe those complete separable metric spaces $X$ in which the $k$ nearest neighbour classifier is universally consistent, both in combinatorial terms of dimension theory and via a fundamental property of real analysis. The following are equivalent: (1) The $k$-nearest neighbour classifier is universally consistent in $X$, (2) The strong Lebesgue--Besicovitch differentiation property holds in $X$ for every...
Projection and Quantisation: A Unifying View of Learning to Hash, from Random Projections to the RAG Era
arXiv:2510.04127v2 Announce Type: replace Abstract: Approximate nearest neighbour (ANN) search underpins large-scale retrieval, increasingly within the retrieval-augmented generation pipelines that ground large language models, yet the methods that address it have multiplied across communities until they are seldom read as a single field. We argue they form one field with three design choices, and develop the projection-quantisation-organisation (PQO) lens, under which locality-sensitive...
Fitting scattered data with optional monotonicity constraints on GPU: LipFit package
arXiv:2606.04670v1 Announce Type: new Abstract: This paper presents a method of multivariate scattered data interpolation and approximation that produces optimal Lipschitz-continuous approximation, subject to the desired monotonicity constraints. This method relies on tight upper and lower approximations to the data, and is similar in its spirit to the nearest-neighbour approximation but does not suffer from discontinuities. Local Lipschitz interpolation and Lipschitz smoothing are also...
Knowledge Graphs and Reasoning LLMs for Finding Simple Yet Effective Transcriptomic Perturbation Predictors
arXiv:2606.08816v1 Announce Type: new Abstract: Predicting the effect of an unseen gene knockout perturbation on transcriptomic gene expression remains a highly challenging problem for virtual cell models. Recent progress has been made by leveraging biological knowledge graphs to provide a notion of similar perturbation, allowing for improved extrapolation beyond the set of training perturbations. In this work, we demonstrate that the simplest model to leverage these assumptions - a...
PlayStation Architecture
Supporting imagery A quick introduction Sony knew that 3D hardware could get very messy to develop for. Thus, their debuting console will keep its design simple and practical… Although this may come at a cost!
Bearing Only Distributed Circumnavigation with Limited Target Information for Asymmetric Dubins Vehicles
arXiv:2606.04519v1 Announce Type: new Abstract: In this paper, we present a class of bearing based distributive nonlinear guidance laws for the cooperative circumnavigation of a stationary target by a heterogeneous team of asymmetric Dubins vehicles. In such a vehicle, the maximal left and right turn capabilities are non uniform. In the given framework, the location of the target is known only to a small subset of the vehicles, called the leaders.
Rachel Reeves says Labour must stick to Brexit promise as party splits emerge
Rachel Reeves says Labour must stick to Brexit promise as party splits emerge EXCLUSIVE: Rachel Reeves said Labour must stick to its manifesto, which ruled out joining the single market and the customs union, and allowing freedom of movement Rachel Reeves has said Labour must stick to its Brexit red lines amid growing splits over the UK's relationship with the EU. The Chancellor said quitting the bloc has driven up prices and clobbered businesses on both sides of the Channel.
Mathematical Morphology in Machine Learning
arXiv:2605.30700v1 Announce Type: new Abstract: This work introduces mathematical morphology-an established visual computing theory-into machine learning to exploit shape and density aspects often overlooked by standard techniques. We propose a fast clustering algorithm based on morphological reconstruction that accurately preserves cluster shapes and density. This scheme offers unique features: an intrinsic sense of maximal clusters, cost-free noise removal, and diverse growth patterns...
The Unreasonable Redundancy of Nature's Protein Folds
The Unreasonable Redundancy of Nature's Protein Folds Over the last few years, deep neural networks have made generative language modeling dramatically more powerful, giving us large language models. A similar leap happened for continuous modalities like images and videos.