GEAR
发表于 2025-3-23 11:55:42
https://doi.org/10.1007/978-3-319-43773-6ansfer knowledge from a completed source optimisation task to a new target task in order to overcome the cold start problem. We model source data as noisy observations of the target function. The level of noise is computed from the data in a Bayesian setting. This enables flexible knowledge transfer
Isometric
发表于 2025-3-23 17:28:02
Jignesh Patel MD, PhD,Jon Kobashigawa MD, degrade the performance of traditional online learning algorithms. Thus, many existing works focus on detecting concept drift based on statistical evidence. Other works use sliding window or similar mechanisms to select the data that closely reflect current concept. Nevertheless, few works study h
COUCH
发表于 2025-3-23 20:24:25
W. Kim Halford,Jemima Petch,Debra Creedytering methods by letting a user select samples based on his/her knowledge. However, due to knowledge limitation, a single user may only pick out the samples that s/he is familiar with while ignore the others, such that the selected samples are often biased. We propose a framework to address this is
CREST
发表于 2025-3-24 01:16:18
W. Kim Halford,Jemima Petch,Debra Creedyrd classification and regression problems where a domain expert can provide the labels for the data in a reasonably short period of time, training data in such longitudinal studies must be obtained only by waiting for the occurrence of sufficient number of events. The main objective of this work is
palliative-care
发表于 2025-3-24 04:35:34
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贪婪的人
发表于 2025-3-24 06:35:46
Patricia R. Recupero,Samara E. Harmsence between pair-wise consecutive frames at a specific time, we measure the divergence between two OCSVM classifiers, which are learnt from two contextual sets, i.e., immediate past set and immediate future set. To speed up the processing procedure, the two OCSVM classifiers are updated in an onlin
Emmenagogue
发表于 2025-3-24 13:16:31
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magnanimity
发表于 2025-3-24 17:15:06
Andrew Hecht,Jonathan S. Markowitzupervised nonlinear dimensionality reduction method that aims at lower space complexity is proposed. First, a positive and negative competitive learning strategy is introduced to the single layered Self-Organizing Incremental Neural Network (SOINN) to process partially labeled datasets. Then, we for
水槽
发表于 2025-3-24 22:38:03
Ryan Budwany,Tony K. George,Timothy R. Deer usually have different physical interpretations. It may be inappropriate to map multiple views of data onto a shared feature space and directly compare them. In this paper, we propose a simple yet effective Cross-View Feature Hashing (CVFH) algorithm via a “partition and match” approach. The featur
Reclaim
发表于 2025-3-25 01:08:38
Advances in Knowledge Discovery and Data Mining978-3-319-31753-3Series ISSN 0302-9743 Series E-ISSN 1611-3349