Whole versus part methods in learning nonsensical syllables.

Whole-word versus part-word phonotactic probability/ neighborhood density in word learning by children

Connectionist Modeling of Part-Whole Analogy Learning

Analogical reasoning, along with inductive, deductive or abductive reasoning, belongs to the fundamental human mechanisms for the environment exploration, learning, or problem solving. Modeling this ability using computer simulations is important, as it might offer mechanistic explanation of these phenomena. In this work, we focus on the part–whole analogies in a separation task where the analo...

A Method for Learning Part-Whole Relations

In this paper we describe a method for finding part-whole relations. The method consists of two steps: (i) finding phrase patterns for both explicit and implicit part-whole relations, and (ii) applying these patterns to find part-whole relation instances. We show results of applying this method to a domain of finding sources of carcinogens.

Learning Distributed Representations for Syllables

This paper presents a connectionist model of how representations for syllables might be learned from sequences of phones. A simple recurrent network is trained to distinguish a set of words in an artificial language, which are presented to it as sequences of phonetic feature vectors. The distributed syllable representations that are learned as a side-effect of this task are used as input to oth...

Kan Extensions and Nonsensical Generalizations

The categorical concept of Kan extensions form a more general notion of both limits and adjoints. The general definition of Kan extensions is given and motivated by several concrete examples. After providing the necessary background on some basic categorical objects and theorems, the relationship between Kan extensions, limits, and adjoints is expressed through two theorems from [3]. 1. Some Pr...