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Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation
TLDR
We propose Deep Reconstruction-Classification Network (DRCN), a convolutional network that jointly learns two tasks: i) supervised source label prediction and ii) unsupervised target data reconstruction. Expand
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Domain Generalization for Object Recognition with Multi-task Autoencoders
TLDR
The problem of domain generalization is to take knowledge acquired from a number of related domains, where training data is available, and to then successfully apply it to previously unseen domains. Expand
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Scatter Component Analysis: A Unified Framework for Domain Adaptation and Domain Generalization
TLDR
We propose Scatter Component Analyis (SCA), a fast representation learning algorithm that can be applied to both domain adaptation and domain generalization. Expand
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Strongly-Typed Recurrent Neural Networks
TLDR
This paper imports ideas from physics and functional programming into RNN design to provide guiding principles. Expand
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Domain Adaptive Neural Networks for Object Recognition
TLDR
We propose a simple neural network model to deal with the domain adaptation problem in object recognition. Expand
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Compatible Value Gradients for Reinforcement Learning of Continuous Deep Policies
TLDR
This paper proposes GProp, a deep reinforcement learning algorithm for continuous policies with compatible function approximation. Expand
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Sparse representations in deep learning for noise-robust digit classification
TLDR
We present a comparison of several sparse regularization methods in deep learning with respect to the performance of a noisy digit classification task under varying size of training samples. Expand
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Deep hybrid networks with good out-of-sample object recognition
TLDR
We introduce Deep Hybrid Networks that are robust to the recognition of out-of-sample objects, i.e., ones that are drawn from a different probability distribution from the training data distribution. Expand
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Domain Adaptation and Domain Generalization with Representation Learning
TLDR
This thesis proposes a fast kernel-based representation learning algorithm for both domain adaptation and domain generalization, Scatter Component Analysis. Expand
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Dimensi Social Capital yang Memengaruhi Kinerja Pegawai Bpjs Kesehatan
Social capital dipandang dari perspektif sumber daya manusia merupakan upaya mengelola sumber daya menjadi aspek penting dalam pembentukan organisasi. Social capital didefinisikan sebagai serangkaianExpand
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