In recent years supervised representation learning has provided state of the art or close to the state of the art results in semantic analysis tasks including ranking and information retrieval. The core idea is to learn how to embed items into a latent space such that they optimize a supervised objective in that latent space. The dimensions of the latent space have no clear semantics, and this ...

A useful way to explain the notions of implicit and explicit learning in ACT-R is to define implicit learning as learning by ACT-R's learning mechanisms, and explicit learning as the results of learning goals. This idea complies with the usual notion of implicit learning as unconscious and always active and explicit learning as intentional and conscious. Two models will be discussed to illustra...

The hippocampus is crucial for conscious, explicit memory, but whether it is also involved in nonconscious, implicit memory is uncertain. We investigated with functional magnetic resonance imaging whether implicit learning engages the hippocampus and interacts with subsequent explicit learning. The presentation of subliminal faces-written profession pairs for implicit learning was followed by t...

This study investigated the amount of incidental vocabulary learning through comprehension-focused reading of short stories and explicit instruction to this goal.  Forty male high school students were selected randomly, and divided into two groups of twenty.  One group of these students was given five 400-word-level short stories to read with the purpose of comprehension, and the students in th...

This study attempted to investigate the impact of teacher’s code-switching on the acquisition of a problematic grammatical structure, namely, object relative clauses, by intermediate EFL learners. Moreover, a secondary objective of the study was to determine the EFL learners’ attitudes and opinions regarding the effectiveness of teacher’s code-switching in their learning of a specific aspect of...

A popular distinction in the learning literature is the distinction between implicit and explicit learning. Although many studies elaborate on the nature of implicit learning, little attention is left for explicit learning. The unintentional aspect of implicit learning corresponds well to the mechanistic view of learning employed in architectures of cognition. But how to account for deliberate,...

In Genetic Programming (GP) and most other evolutionary computing approaches, the knowledge learned during the evolutionary processing is implicitly encoded in the population. A small family of approaches, known as Estimation of Distribution Algorithms, learn this knowledge directly in the form of probability distributions. In this research, we proposed a new approach for program synthesis – Pr...

We use a graphical model of the supervised learning problem to explore the theoretical effect of utility in the form of end use and sample cost on supervised learning, No-Free-Lunch, sample complexity, and active learning. There are two sources of utility that can affect the above problems: utility that comes from end use and utility that comes from sample costs. We explore which parts of these...