Results 41 to 50 of about 2,079,458 (324)
Feature Selection for Transfer Learning [PDF]
, 2011 Common assumption in most machine learning algorithms is that, labeled (source) data and unlabeled (target) data are sampled from the same distribution. However, many real world tasks violate this assumption: in temporal domains, feature distributions may vary over time, clinical studies may have sampling bias, or sometimes sufficient labeled data for ...
Selen Uguroglu, Jaime Carbonell
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Deep transfer network of heterogeneous domain feature in machine translation
High-Confidence Computing, 2022 In order to address the shortcoming of feature representation limitation in machine translation(MT) system, this paper presents a feature transfer method in MT.
Yupeng Liu, Yanan Zhang, Xiaochen Zhang
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EFANet: Exchangeable Feature Alignment Network for Arbitrary Style Transfer
, 2019 Style transfer has been an important topic both in computer vision and graphics. Since the seminal work of Gatys et al. first demonstrates the power of stylization through optimization in the deep feature space, quite a few approaches have achieved real ...
Gong, Minglun +4 more
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Scalable Greedy Algorithms for Transfer Learning
, 2016 In this paper we consider the binary transfer learning problem, focusing on how to select and combine sources from a large pool to yield a good performance on a target task.
Caputo, Barbara +2 more
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A Flexible Simple Thermostat for Small Objects and the Range of 100 to 400 K [PDF]
, 1970 A flexible, inexpensive thermostat for the temperature range 100 to 400 K is described. Liquid nitrogen is the coolant and a gas serves as transfer medium.
Bilger, H. R., Nicolet, M.-A.
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Feature space transformation for transfer learning [PDF]
The 2012 International Joint Conference on Neural Networks (IJCNN), 2012 In this paper, we propose a study on the use of weighted topological learning and matrix factorization methods to transform the representation space of a sparse dataset in order to increase the quality of learning, and adapt it to the case of transfer learning.
Nistor Grozavu +2 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Bone tumours present significant challenges for affected patients, as multimodal therapy often leads to prolonged physical limitations. This is particularly critical during childhood and adolescence, as it can negatively impact physiological development and psychosocial resilience.
Jennifer Queisser +5 more
wiley +1 more source
Understanding Slow Feature Analysis: A Mathematical Framework [PDF]
, 2008 Slow feature analysis is an algorithm for unsupervised learning of invariant representations from data with temporal correlations. Here, we present a mathematical analysis of slow feature analysis for the case where the input-output functions are not ...
Sprekeler, Henning +1 more
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Revealing the structure of land plant photosystem II: the journey from negative‐stain EM to cryo‐EM
FEBS Letters, EarlyView.Advances in cryo‐EM have revealed the detailed structure of Photosystem II, a key protein complex driving photosynthesis. This review traces the journey from early low‐resolution images to high‐resolution models, highlighting how these discoveries deepen our understanding of light harvesting and energy conversion in plants.
Roman Kouřil
wiley +1 more source
Dual-Space Transfer Learning Based on an Indirect Mutual Promotion Strategy
International Journal of Computational Intelligence Systems, 2022 Transfer learning is designed to leverage knowledge in the source domain with labels to help build classification models in the target domain where labels are scarce or even unavailable. Previous studies have shown that high-level concepts extracted from
Teng Cui +3 more
doaj +1 more source