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Found 7 papers, 1 papers with code
Deep Learning as Ricci Flow
To illustrate this idea, we present a computational framework to quantify the geometric changes that occur as data passes through successive layers of a DNN, and use this framework to motivate a notion of `global Ricci network flow' that can be used to assess a DNN's ability to disentangle complex data geometries to solve classification problems.
Learning from data with structured missingness
Missing data are an unavoidable complication in many machine learning tasks.
Contrastive Fairness in Machine Learning
How can one ensure that the decisions were taken based on merit and not on protected attributes like race or sex?
Distance Metric Learned Collaborative Representation Classifier
We present a simple effective way of achieving this by learning a generic Mahalanabis distance in a collaborative loss function in an end-to-end fashion with any standard convolutional network as the feature learner.
PProCRC: Probabilistic Collaboration of Image Patches
We present a conditional probabilistic framework for collaborative representation of image patches.
CoCoNet: A Collaborative Convolutional Network
We present an end-to-end deep network for fine-grained visual categorization called Collaborative Convolutional Network (CoCoNet).
Fine-Grained Visual Categorization
Fine-Grained Visual Recognition
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LOOP Descriptor: Local Optimal Oriented Pattern
This letter introduces the LOOP binary descriptor (local optimal oriented pattern) that encodes rotation invariance into the main formulation itself.
