Results 61 to 70 of about 4,969,023 (298)
Fluctuation domains in adaptive evolution [PDF]
Theoretical Population Biology, 2010 We derive an expression for the variation between parallel trajectories in phenotypic evolution, extending the well known result that predicts the mean evolutionary path in adaptive dynamics or quantitative genetics. We show how this expression gives rise to the notion of fluctuation domains - parts of the fitness landscape where the rate of evolution ...
Boettiger, Carl +2 more
openaire +3 more sources
Domain-Agnostic Mutual Prompting for Unsupervised Domain Adaptation [PDF]
Computer Vision and Pattern RecognitionConventional Unsupervised Domain Adaptation (UDA) strives to minimize distribution discrepancy between do-mains, which neglects to harness rich semantics from data and struggles to handle complex domain shifts.
Zhekai Du +5 more
semanticscholar +1 more source
Background-Aware Domain Adaptation for Plant Counting
Frontiers in Plant Science, 2022 Deep learning-based object counting models have recently been considered preferable choices for plant counting. However, the performance of these data-driven methods would probably deteriorate when a discrepancy exists between the training and testing ...
Min Shi, Xing-Yi Li, Hao Lu, Zhi-Guo Cao
doaj +1 more source
Learning the Roots of Visual Domain Shift [PDF]
, 2016 In this paper we focus on the spatial nature of visual domain shift, attempting to learn where domain adaptation originates in each given image of the source and target set.
A Gretton +5 more
core +2 more sources
Unsupervised Domain Adaptation with Adapter
, 2021 Unsupervised domain adaptation (UDA) with pre-trained language models (PrLM) has achieved promising results since these pre-trained models embed generic knowledge learned from various domains. However, fine-tuning all the parameters of the PrLM on a small domain-specific corpus distort the learned generic knowledge, and it is also expensive to ...
Zhang, Rongsheng +3 more
openaire +2 more sources
Self-Adaptive Partial Domain Adaptation
, 2021 Partial Domain adaptation (PDA) aims to solve a more practical cross-domain learning problem that assumes target label space is a subset of source label space. However, the mismatched label space causes significant negative transfer. A traditional solution is using soft weights to increase weights of source shared domain and reduce those of source ...
Hu, Jian +8 more
openaire +2 more sources
Semi-Supervised Domain Adaptation via Minimax Entropy [PDF]
IEEE International Conference on Computer Vision, 2019 Contemporary domain adaptation methods are very effective at aligning feature distributions of source and target domains without any target supervision. However, we show that these techniques perform poorly when even a few labeled examples are available ...
Kuniaki Saito +4 more
semanticscholar +1 more source
Distribution matching and structure preservation for domain adaptation
Complex & Intelligent Systems, 2022 Cross-domain classification refers to completing the corresponding classification task in a target domain which lacks label information, by exploring useful knowledge in a related source domain but with different data distribution.
Ping Li, Zhiwei Ni, Xuhui Zhu, Juan Song
doaj +1 more source
Domain Adaptation for Neural Networks by Parameter Augmentation
, 2016 We propose a simple domain adaptation method for neural networks in a supervised setting. Supervised domain adaptation is a way of improving the generalization performance on the target domain by using the source domain dataset, assuming that both of the
Hashimoto, Kazuma +2 more
core +1 more source
Kernel Manifold Alignment for Domain Adaptation. [PDF]
PLoS ONE, 2016 The wealth of sensory data coming from different modalities has opened numerous opportunities for data analysis. The data are of increasing volume, complexity and dimensionality, thus calling for new methodological innovations towards multimodal data ...
Devis Tuia, Gustau Camps-Valls
doaj +1 more source