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Found 9 papers, 2 papers with code
Informative Sample-Aware Proxy for Deep Metric Learning
Among various supervised deep metric learning methods proxy-based approaches have achieved high retrieval accuracies.
Empirical Study on Optimizer Selection for Out-of-Distribution Generalization
Modern deep learning systems do not generalize well when the test data distribution is slightly different to the training data distribution.
Feature Space Particle Inference for Neural Network Ensembles
Ensembles of deep neural networks demonstrate improved performance over single models.
Takeuchi's Information Criteria as Generalization Measures for DNNs Close to NTK Regime
Generalization measures are intensively studied in the machine learning community for better modeling generalization gaps.
Proper Straight-Through Estimator: Breaking symmetry promotes convergence to true minimum
By considering the scale symmetry of the network and specific properties of the STEs, we find that STE with clipped Relu is superior to STEs with identity function and vanilla Relu.
CorsNet: 3D Point Cloud Registration by Deep Neural Network
For comparison, we also developed a novel deep learning approach (DirectNet) that directly regresses the pose between point clouds.
Breaking Inter-Layer Co-Adaptation by Classifier Anonymization
This study addresses an issue of co-adaptation between a feature extractor and a classifier in a neural network.
Multiple-Hypothesis Affine Region Estimation With Anisotropic LoG Filters
We propose a method for estimating multiple-hypothesis affine regions from a keypoint by using an anisotropic Laplacian-of-Gaussian (LoG) filter.
Pairwise Rotation Hashing for High-dimensional Features
Binary Hashing is widely used for effective approximate nearest neighbors search.
