We present a fully four-dimensional, globally convergent, incremental gradient algorithm to estimate the continuous-time tracer density from list mode positron emission tomography...
Searching approximate nearest neighbors in large scale high dimensional data set has been a challenging problem. This paper presents a novel and fast algorithm for learning binary...
For many applied problems in the context of clustering via mixture models, the estimates of the component means and covariance matrices can be affected by observations that are at...
The paper presents a new data partitioning algorithm for parallel computing on heterogeneous processors. Like traditional functional partitioning algorithms, the algorithm assumes ...
Abstract. In our previous work we have shown that Mahalanobis kernels are useful for support vector classifiers both from generalization ability and model selection speed. In this ...