Active learning may hold the key for solving the data scarcity problem in supervised learning, i.e., the lack of labeled data. Indeed, labeling data is a costly process, yet an ac...
The increasing complexity of today’s systems makes fast and accurate failure detection essential for their use in mission-critical applications. Various monitoring methods provi...
We present a novel framework for multi-label learning that explicitly addresses the challenge arising from the large number of classes and a small size of training data. The key a...
In adding syntax to statistical MT, there is a tradeoff between taking advantage of linguistic analysis, versus allowing the model to exploit linguistically unmotivated mappings l...
In this paper, we tackle the problem of learning a user's interest from his photo collections and suggesting relevant ads. We address two key challenges in this work: 1) unde...