Lots of efforts in the last decades have been done to prove or disprove whether the set of polynomially bounded problems is equal to the set of polynomially verifiable problems. T...
Sina Jafarpour, Mohammad Ghodsi, Keyvan Sadri, Zuh...
In this paper, we present a method for data classification with application to car/non-car objects. We first developed a sample based car/non-car maximal mutual information low di...
This paper describes the training of classifiers entirely based on virtual images, rendered by a ray-tracing software. Two classifiers, a support vector machine and a polynomial c...
We present a novel technique for automated problem decomposition to address the problem of scalability in reinforcement learning. Our technique makes use of a set of near-optimal ...
Peng Zang, Peng Zhou, David Minnen, Charles Lee Is...
We propose a new penalty function which, when used as regularization for empirical risk minimization procedures, leads to sparse estimators. The support of the sparse vector is ty...