Hubs and Hyperspheres: Reducing Hubness and Improving Transductive
Few-shot Learning with Hyperspherical Embeddings

Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-shot Learning with Hyperspherical Embeddings

16 March 2023

Daniel J. Trosten

Rwiddhi Chakraborty

Kristoffer Wickstrøm

Michael C. Kampffmeyer

Papers citing "Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-shot Learning with Hyperspherical Embeddings"

9 / 9 papers shown

Title
Position: Beyond Euclidean -- Foundation Models Should Embrace Non-Euclidean Geometries Neil He Jiahong Liu Buze Zhang N. Bui Ali Maatouk Menglin Yang Irwin King Melanie Weber Rex Ying 29 0 0 11 Apr 2025
Unbiased Max-Min Embedding Classification for Transductive Few-Shot Learning: Clustering and Classification Are All You Need Yang Liu Feixiang Liu Jiale Du Xinbo Gao Jungong Han 37 0 0 28 Mar 2025
Improving Open-world Continual Learning under the Constraints of Scarce Labeled Data Heng Chang Xiangkun Wang Xin Yang Marcello Bonsangue Jun Zhang Tianrui Li CLL VLM 56 0 0 28 Feb 2025
Transductive Zero-Shot and Few-Shot CLIP Ségolène Martin Yunshi Huang Fereshteh Shakeri J. Pesquet Ismail Ben Ayed BDL VLM 38 13 0 08 Apr 2024
Robust Transductive Few-shot Learning via Joint Message Passing and Prototype-based Soft-label Propagation Jiahui Wang Qin Xu Bo Jiang Bin Luo 26 0 0 28 Nov 2023
Contrastive Tuning: A Little Help to Make Masked Autoencoders Forget Johannes Lehner Benedikt Alkin Andreas Fürst Elisabeth Rumetshofer Lukas Miklautz Sepp Hochreiter 26 18 0 20 Apr 2023
Alleviating the Sample Selection Bias in Few-shot Learning by Removing Projection to the Centroid Jing Xu Xu Luo Xinglin Pan Wenjie Pei Yanan Li Zenglin Xu 36 21 0 30 Oct 2022
The Role of Global Labels in Few-Shot Classification and How to Infer Them Ruohan Wang Massimiliano Pontil C. Ciliberto VLM 34 17 0 09 Aug 2021
Iterative label cleaning for transductive and semi-supervised few-shot learning Michalis Lazarou Tania Stathaki Yannis Avrithis 40 61 0 14 Dec 2020