In many inertial confinement fusion experiments, the neutron yield and o...
Comparing structured data from possibly different metric-measure spaces ...
Because the magnitude of inner products with its basis functions are
inv...
Convolution is conventionally defined as a linear operation on functions...
Underpinning the success of deep learning is effective regularizations t...
Invariance (defined in a general sense) has been one of the most effecti...
The problem of adversarial examples has highlighted the need for a theor...
We propose a robust adversarial prediction framework for general multicl...
In many structured prediction problems, complex relationships between
va...
The goal of online prediction with expert advice is to find a decision
s...
Scaling multinomial logistic regression to datasets with very large numb...
Structured sparsity is an important modeling tool that expands the
appli...
Although many convex relaxations of clustering have been proposed in the...
We demonstrate that almost all non-parametric dimensionality reduction
m...
A Support Vector Method for multivariate performance measures was recent...
Regularized risk minimization with the binary hinge loss and its variant...