Active learning is a generic approach to accelerate training of classifiers in order to achieve a higher accuracy with a small number of training examples. In the past, simple ac...
The capacity scaling property specifies the changes in network throughput when network size increases and serves as an essential performance evaluation metric for large-scale wir...
9, IO]. However, unlike the case with static timing, it is not so easy We show how recent advances in the handling of correlated interval representations of range uncertainty can b...
Many NLP tasks rely on accurately estimating word dependency probabilities P(w1|w2), where the words w1 and w2 have a particular relationship (such as verb-object). Because of the...
Kristina Toutanova, Christopher D. Manning, Andrew...
Embeddings of random variables in reproducing kernel Hilbert spaces (RKHSs) may be used to conduct statistical inference based on higher order moments. For sufficiently rich (char...
Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur G...