Imagen de Portada

kNN-Graph: An adaptive graph model for $k$-nearest neighbors

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Li, Jiaye, Chen, Gang, Xu, Hang, Zhang, Shichao
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

kNN Classification of Malware Data Dependency Graph Features
por: Musgrave, John, et al.
Publicado: (2024)

Adaptive $k$-nearest neighbor classifier based on the local estimation of the shape operator
por: Levada, Alexandre Luís Magalhães, et al.
Publicado: (2024)

kNN Retrieval for Simple and Effective Zero-Shot Multi-speaker Text-to-Speech
por: Hajal, Karl El, et al.
Publicado: (2024)

kNN-SVC: Robust Zero-Shot Singing Voice Conversion with Additive Synthesis and Concatenation Smoothness Optimization
por: Shao, Keren, et al.
Publicado: (2025)

This EEG Looks Like These EEGs: Interpretable Interictal Epileptiform Discharge Detection With ProtoEEG-kNN
por: Tang, Dennis, et al.
Publicado: (2025)

SCoRE: Streamlined Corpus-based Relation Extraction using Multi-Label Contrastive Learning and Bayesian kNN
por: Mariotti, Luca, et al.
Publicado: (2025)

Routing by Analogy: kNN-Augmented Expert Assignment for Mixture-of-Experts
por: Lyu, Boxuan, et al.
Publicado: (2026)

Surprisal Driven $k$-NN for Robust and Interpretable Nonparametric Learning
por: Banerjee, Amartya, et al.
Publicado: (2023)

Improved convergence rate of kNN graph Laplacians: differentiable self-tuned affinity
por: Cheng, Xiuyuan, et al.
Publicado: (2024)

Conformal and kNN Predictive Uncertainty Quantification Algorithms in Metric Spaces
por: Lugosi, Gábor, et al.
Publicado: (2025)

Optimizing Parallel Schemes with Lyapunov Exponents and kNN-LLE Estimation
por: Shams, Mudassir, et al.
Publicado: (2026)

Efficient Quantum Approximate $k$NN Algorithm via Granular-Ball Computing
por: Xia, Shuyin, et al.
Publicado: (2025)

TRAKNN: Efficient Trajectory Aware Spatiotemporal kNN for Rare Meteorological Trajectory Detection
por: Coulaud, Guillaume, et al.
Publicado: (2026)

C-kNN-LSH: A Nearest-Neighbor Algorithm for Sequential Counterfactual Inference
por: Wang, Jing, et al.
Publicado: (2026)

Rethinking Predictive Modeling for LLM Routing: When Simple kNN Beats Complex Learned Routers
por: Li, Yang
Publicado: (2025)

Exploring the Limitations of kNN Noisy Feature Detection and Recovery for Self-Driving Labs
por: Shi, Qiuyu, et al.
Publicado: (2025)

NN-Former: Rethinking Graph Structure in Neural Architecture Representation
por: Xu, Ruihan, et al.
Publicado: (2025)

Deep k-grouping: An Unsupervised Learning Framework for Combinatorial Optimization on Graphs and Hypergraphs
por: Bai, Sen, et al.
Publicado: (2025)

$\mathbb{R}^{2k}$ is Theoretically Large Enough for Embedding-based Top-$k$ Retrieval
por: Wang, Zihao, et al.
Publicado: (2026)

k-Maximum Inner Product Attention for Graph Transformers and the Expressive Power of GraphGPS
por: De Schouwer, Jonas, et al.
Publicado: (2026)

Integrating kNN with Foundation Models for Adaptable and Privacy-Aware Image Classification
por: Doerrich, Sebastian, et al.
Publicado: (2024)

DeNoise: Learning Robust Graph Representations for Unsupervised Graph-Level Anomaly Detection
por: Chen, Qingfeng, et al.
Publicado: (2025)

kNN-CLIP: Retrieval Enables Training-Free Segmentation on Continually Expanding Large Vocabularies
por: Gui, Zhongrui, et al.
Publicado: (2024)

RSPO: Risk-Seeking Policy Optimization for Pass@k and Max@k Metrics in Large Language Models
por: Zhang, Kaichen, et al.
Publicado: (2025)

ZETA: Leveraging Z-order Curves for Efficient Top-k Attention
por: Zeng, Qiuhao, et al.
Publicado: (2025)

Fast and Eager k-Medoids Clustering: O(k) Runtime Improvement of the PAM, CLARA, and CLARANS Algorithms
por: Schubert, Erich, et al.
Publicado: (2020)

Kimi k1.5: Scaling Reinforcement Learning with LLMs
por: Kimi Team, et al.
Publicado: (2025)

Optimizing $k$ in $k$NN Graphs with Graph Learning Perspective
por: Tamaru, Asuka, et al.
Publicado: (2024)

Embedding Graphs as Euclidean kNN-Graphs
por: Schibler, T., et al.
Publicado: (2025)

Doubly robust nearest neighbors in factor models
por: Dwivedi, Raaz, et al.
Publicado: (2022)

A Mathematical Theory of Top-$k$ Sparse Attention via Total Variation Distance
por: Tzachristas, Georgios, et al.
Publicado: (2025)

$k$-server-bench: Automating Potential Discovery for the $k$-Server Conjecture
por: Brilliantov, Kirill, et al.
Publicado: (2026)

Optimizing Partial Area Under the Top-k Curve: Theory and Practice
por: Wang, Zitai, et al.
Publicado: (2022)

Theoretical Analysis of Sparse Optimization with Reparameterization, Weight Decay, and Adaptive Learning Rate
por: Xu, Huangyu, et al.
Publicado: (2026)

Turn Waste into Worth: Rectifying Top-$k$ Router of MoE
por: Zeng, Zhiyuan, et al.
Publicado: (2024)

HATA: Trainable and Hardware-Efficient Hash-Aware Top-k Attention for Scalable Large Model Inference
por: Gong, Ping, et al.
Publicado: (2025)

Irredundant $k$-Fold Cross-Validation
por: Aguilar-Ruiz, Jesus S.
Publicado: (2025)

SIMPLE: A Gradient Estimator for $k$-Subset Sampling
por: Ahmed, Kareem, et al.
Publicado: (2022)

Explaining k-Nearest Neighbors: Abductive and Counterfactual Explanations
por: Barceló, Pablo, et al.
Publicado: (2025)

Lookbehind-SAM: k steps back, 1 step forward
por: Mordido, Gonçalo, et al.
Publicado: (2023)