Results 241 to 250 of about 178,877 (269)

Generalization in Unsupervised Learning

2015
We are interested in the following questions. Given a finite data set S, with neither labels nor side information, and an unsupervised learning algorithm A, can the generalization of A be assessed on S? Similarly, given two unsupervised learning algorithms, A1 and A2, for the same learning task, can one assess whether one will generalize "better" on ...
Karim T. Abou-Moustafa, Dale Schuurmans
openaire   +1 more source

Unsupervised evidence integration

Proceedings of the 22nd international conference on Machine learning - ICML '05, 2005
Many biological propositions can be supported by a variety of different types of evidence. It is often useful to collect together large numbers of such propositions, together with the evidence supporting them, into databases to be used in other analyses.
Philip M. Long, Vinay Varadan, Sarah Gilman, Mark Treshock, Rocco A. Servedio   +4 more
openaire   +1 more source

Unsupervised coding with lococode

1997
Traditional approaches to sensory coding use code component-oriented objective functions (COCOFs) to evaluate code quality. Previous COCOFs do not take into account the information-theoretic complexity of the code-generating mapping itself. We do: “Low-complexity coding and decoding” (LOCOCODE) generates so-called lococodes that (1) convey information ...
Sepp Hochreiter, Jürgen Schmidhuber
openaire   +1 more source

XAI for unsupervised learning

Unsupervised learning algorithms detect inherent patterns and relationships in data without requiring predefined target variables. Although unsupervised learning algorithms have great capabilities, their decisions remain largely opaque, driving the need for explainability.
openaire   +2 more sources

A Survey of Unsupervised Generative Models for Exploratory Data Analysis and Representation Learning

ACM Computing Surveys, 2022
Mohanad Abukmeil, Stefano Ferrari, Angelo Genovese   +2 more
exaly  

Autoencoders for unsupervised anomaly segmentation in brain MR images: A comparative study

Medical Image Analysis, 2021
Christoph Baur, Stefan Denner, Benedikt Wiestler   +2 more
exaly  

Cluster-Guided Asymmetric Contrastive Learning for Unsupervised Person Re-Identification

IEEE Transactions on Image Processing, 2022
Mingkun Li, Chun-Guang Li, Jun Guo
exaly  

Unsupervised attribute reduction for mixed data based on fuzzy rough sets

Information Sciences, 2021
Zhong Yuan, Hongmei Chen, Zeng Yu
exaly  

Unsupervised K-Means Clustering Algorithm

IEEE Access, 2020
Kristina P Sinaga, Miin-Shen Yang
exaly  

Hybrid Dynamic Contrast and Probability Distillation for Unsupervised Person Re-Id

IEEE Transactions on Image Processing, 2022
Jingyu Zhou, Nannan Wang, Xinbo Gao
exaly