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Found 7 papers, 0 papers with code
Tracking Dynamic Gaussian Density with a Theoretically Optimal Sliding Window Approach
Dynamic density estimation is ubiquitous in many applications, including computer vision and signal processing.
Conditional Deformable Image Registration with Spatially-Variant and Adaptive Regularization
The proposed method introduces a spatially-variant regularization and learns its effect of achieving spatially-adaptive regularization by conditioning the registration network on the hyperparameter matrix via CSAIN.
TAP: The Attention Patch for Cross-Modal Knowledge Transfer from Unlabeled Modality
This paper addresses a cross-modal learning framework, where the objective is to enhance the performance of supervised learning in the primary modality using an unlabeled, unpaired secondary modality.
TAKDE: Temporal Adaptive Kernel Density Estimator for Real-Time Dynamic Density Estimation
Kernel density estimation is arguably one of the most commonly used density estimation techniques, and the use of "sliding window" mechanism adapts kernel density estimators to dynamic processes.
Learning from Non-Random Data in Hilbert Spaces: An Optimal Recovery Perspective
Then, for any Hilbert space, we show that Optimal Recovery provides a formula which is user-friendly from an algorithmic point-of-view, as long as the hypothesis class is linear.
ORCCA: Optimal Randomized Canonical Correlation Analysis
We prove that this method, called ORCCA, can outperform (in expectation) the corresponding Kernel CCA with a default kernel.
Distributed Parameter Estimation in Randomized One-hidden-layer Neural Networks
This paper addresses distributed parameter estimation in randomized one-hidden-layer neural networks.
