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06/02/2022
Machine Learning for Detection of 3D Features using sparse X-ray data
In many inertial confinement fusion experiments, the neutron yield and o...
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05/12/2022
Orthogonal Gromov-Wasserstein Discrepancy with Efficient Lower Bound
Comparing structured data from possibly different metric-measure spaces ...
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03/13/2022
Euclidean Invariant Recognition of 2D Shapes Using Histograms of Magnitudes of Local Fourier-Mellin Descriptors
Because the magnitude of inner products with its basis functions are inv...
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03/13/2022
Similarity Equivariant Linear Transformation of Joint Orientation-Scale Space Representations
Convolution is conventionally defined as a linear operation on functions...
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06/14/2020
Proximal Mapping for Deep Regularization
Underpinning the success of deep learning is effective regularizations t...
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04/25/2020
Convex Representation Learning for Generalized Invariance in Semi-Inner-Product Space
Invariance (defined in a general sense) has been one of the most effecti...
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02/11/2020
Generalised Lipschitz Regularisation Equals Distributional Robustness
The problem of adversarial examples has highlighted the need for a theor...
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12/18/2018
Consistent Robust Adversarial Prediction for General Multiclass Classification
We propose a robust adversarial prediction framework for general multicl...
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11/07/2018
Distributionally Robust Graphical Models
In many structured prediction problems, complex relationships between va...
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05/20/2018
Exp-Concavity of Proper Composite Losses
The goal of online prediction with expert advice is to find a decision s...
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04/16/2016
DS-MLR: Exploiting Double Separability for Scaling up Distributed Multinomial Logistic Regression
Scaling multinomial logistic regression to datasets with very large numb...
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10/17/2014
Generalized Conditional Gradient for Sparse Estimation
Structured sparsity is an important modeling tool that expands the appli...
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09/26/2013
Convex Relaxations of Bregman Divergence Clustering
Although many convex relaxations of clustering have been proposed in the...
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06/27/2012
Regularizers versus Losses for Nonlinear Dimensionality Reduction: A Factored View with New Convex Relaxations
We demonstrate that almost all non-parametric dimensionality reduction m...
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02/14/2012
Smoothing Multivariate Performance Measures
A Support Vector Method for multivariate performance measures was recent...
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09/07/2009
