Neural Information Processing Systems http://nips.cc/

Can we incorporate discrete optimization algorithms within modern machine learning models?

Numerical results demonstrate the efficacy of the new penalties.

Precise expressions for the asymptotic performance of LASSO have been obtained for a number of different cases, in particular when the elements of the dictionary matrix are sampled independently from a Gaussian distribution.

It is however well known that GAN training suffers from instability due to the nature of its saddle point formulation. In this paper, we explore ways to tackle the instability problem by dualizing the discriminator.

As a consequence, BO is useful when function evaluation is time-consuming, such as when training and testing complex machine learning algorithms (e.g.

Neural Information Processing Systems http://nips.cc/

We consider robust optimization problems, where the goal is to optimize in the worst case over a class of objective functions.

The coordinate descent (CD) method is a classical optimization algorithm that has seen a revival of interest because of its competitive performance in machine learning applications.

We study the problem of learning probabilistic first-order logical rules for knowledge base reasoning.