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Found 8 papers, 0 papers with code
Query-Based Selection of Optimal Candidates under the Mallows Model
We study the secretary problem in which rank-ordered lists are generated by the Mallows model and the goal is to identify the highest-ranked candidate through a sequential interview process which does not allow rejected candidates to be revisited.
Methodology Discrete Mathematics Information Theory Combinatorics Information Theory 05A
Adversarial Problems for Generative Networks
We are interested in the design of generative networks.
Image De-Quantization Using Generative Models as Priors
Image quantization is used in several applications aiming in reducing the number of available colors in an image and therefore its size.
Image Restoration from Parametric Transformations using Generative Models
When images are statistically described by a generative model we can use this information to develop optimum techniques for various image restoration problems as inpainting, super-resolution, image coloring, generative model inversion, etc.
Training Neural Networks for Likelihood/Density Ratio Estimation
In classical approaches the two densities are assumed known or to belong to some known parametric family.
Optimizing Shallow Networks for Binary Classification
Data driven classification that relies on neural networks is based on optimization criteria that involve some form of distance between the output of the network and the desired label.
Kernel-Based Training of Generative Networks
Generative adversarial networks (GANs) are designed with the help of min-max optimization problems that are solved with stochastic gradient-type algorithms which are known to be non-robust.
