Optimization algorithms for large margin multiclass recognizers are often too costly to handle ambitious problems with structured outputs and exponential numbers of classes. Optim...
Classifier learning methods commonly assume that the training data consist of randomly drawn examples from the same distribution as the test examples about which the learned model...
Directed test program-based verification or formal verification methods are usually quite ineffective on large cachecoherent, non-uniform memory access (CC-NUMA) multiprocessors b...
— A novel criterion is introduced for assessing the diversity of a collection of paths or trajectories. The main idea is the notion of survivability, which measures the likelihoo...
We present a multiscale unsupervised segmenter for automatic detection of potentially cancerous regions of interest containing fibroglandular tissue in digital screening mammogra...