We develop techniques for learning the meanings of unknown words in context. Working within a com-positional semantics framework, we write down equations in which a sentence's meaning is some combination function of the meaning of its words. When one of the words is unknown, we ask for a paraphrase of the sentence. We then compute the meaning of the unknown word by inverting parts of the semant...

Economic conditions at the time of entering the labour market can induce wage differentials between entry cohorts. While there exists much empirical evidence on the existence and persistence of these cohort effects, little is known about their impact on employees’ mobility behaviour. Using a large data set derived from German administrative data, this paper analyzes the determinants of job mobi...

Business process reengineering has made revolutionary changes in the personal banking sector. It is the Technological Innovations that improved the service quality, responsiveness and business efficiency. This study focuses on different user profiles (Earning/Non Earning), their perception of risk and confidence in technological innovations in personal banking sector. Required data were collect...

Teaching plays a very important role in our society, by spreading human knowledge and educating our next generations. A good teacher will select appropriate teaching materials, impact suitable methodologies, and set up targeted examinations, according to the learning behaviors of the students. In the field of artificial intelligence, however, one has not fully explored the role of teaching, and...

Inference models, which replace an optimization-based inference procedure with a learned model, have been fundamental in advancing Bayesian deep learning, the most notable example being variational auto-encoders (VAEs). In this paper, we propose iterative inference models, which learn how to optimize a variational lower bound through repeatedly encoding gradients. Our approach generalizes VAEs ...