We are interested in the problem of reasoning over very large common sense knowledge bases. When such a knowledge base contains noisy and subjective data, it is important to have ...
Large-margin structured estimation methods minimize a convex upper bound of loss functions. While they allow for efficient optimization algorithms, these convex formulations are n...
Olivier Chapelle, Chuong B. Do, Quoc V. Le, Alexan...
To study PP attachment disambiguation as a benchmark for empirical methods in natural language processing it has often been reduced to a binary decision problem (between verb or n...
Multi-view learners reduce the need for labeled data by exploiting disjoint sub-sets of features (views), each of which is sufficient for learning. Such algorithms assume that eac...
Abstract— This paper presents i-AA1 , a constructive, incremental learning algorithm for a special class of weightless, self-organizing networks. In i-AA1 , learning consists of ...