Context: Different theoretical frameworks

New Theoretical Frameworks for Machine Learning

Machine Learning, a natural outgrowth at the intersection of Computer Science and Statistics, has evolvedinto a broad, highly successful, and extremely dynamic discipline. Over the past twenty years, machinelearning methods have been applied in an ever increasing range of areas from natural language processingto speech recognition to computer vision to computational biology, just to...

Theoretical frameworks for neuroeconomics of intertemporal choice

Intertemporal choice has drawn attention in behavioral economics, econophysics, and neuroeconomics. Recent studies in mainstream economics have mainly focused on inconsistency in intertemporal choice (dynamic inconsistency); while impulsivity/impatience in intertemporal choice has been extensively studied in behavioral economics of addiction. However, recent advances in neuroeconomic and econop...

Generalized hidden Markov models. I. Theoretical frameworks

This is the first paper in a series of two papers describing a novel generalization of classical hidden Markov models using fuzzy measures and fuzzy integrals. In this paper, we present the theoretical framework for the generalization and, in the second paper, we describe an application of the generalized hidden Markov models to handwritten word recognition. The main characteristic of the gener...

Conceptual and Theoretical Frameworks for Organised Violence

Incorporating immigrants: integrating theoretical frameworks of adaptation.

OBJECTIVES To encourage research on immigrants and aging by analyzing theoretical commonalities in the two fields and identifying potential contributions of aging theories, specifically to the understanding of neglected age differences in the pace of immigrant incorporation. METHODS Survey of the historical development of assimilation theory and its successors and systematic comparison of key...