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On the generalization of learning-based 3D reconstruction
State-of-the-art learning-based monocular 3D reconstruction methods lear...
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Set Distribution Networks: a Generative Model for Sets of Images
Images with shared characteristics naturally form sets. For example, in ...
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Collegial Ensembles
Modern neural network performance typically improves as model size incre...
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Adversarial Fisher Vectors for Unsupervised Representation Learning
We examine Generative Adversarial Networks (GANs) through the lens of de...
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Skip-Clip: Self-Supervised Spatiotemporal Representation Learning by Future Clip Order Ranking
Deep neural networks require collecting and annotating large amounts of ...
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Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment
In most machine learning training paradigms a fixed, often handcrafted, ...
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A Deep Learning Approach for Expert Identification in Question Answering Communities
In this paper, we describe an effective convolutional neural network fra...
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Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records
The rapid growth of Electronic Health Records (EHRs), as well as the acc...
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Structural Correspondence Learning for Cross-lingual Sentiment Classification with One-to-many Mappings
Structural correspondence learning (SCL) is an effective method for cros...
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Fully-adaptive Feature Sharing in Multi-Task Networks with Applications in Person Attribute Classification
Multi-task learning aims to improve generalization performance of multip...
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S3Pool: Pooling with Stochastic Spatial Sampling
Feature pooling layers (e.g., max pooling) in convolutional neural netwo...
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Deep Structured Energy Based Models for Anomaly Detection
In this paper, we attack the anomaly detection problem by directly model...
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