We discuss a simple sparse linear problem that is hard to learn with any algorithm that uses a linear combination of the training instances as its weight vector. The hardness holds...
This paper focuses on perturbation-based distributed beamforming with 1-bit feedback for wireless amplify-and-forward relay networks. We propose to use multiplicative perturbation...
Non-negative matrix factorization (NMF) is a powerful feature extraction method for finding parts-based, linear representations of non-negative data . Inherently, it is unsupervis...
In many vision problems, rotation-invariant analysis is necessary or preferred. Popular solutions are mainly based on pose normalization or brute-force learning, neglecting the in...
Kun Liu, Qing Wang, Wolfgang Driever, Olaf Ronnebe...
We present a boolean constraint logic language clp(B/FD) built upon a language over finite domains clp(FD) which uses a local propagation constraint solver. It is based on a sing...