Background. Parkinson’s disease (PD) is characterized by motor and non-motor symptoms that affect patients’ functional performances, especially while performing dual tasks which is a critical factor in connection with everyday living. There are many controversies about the benefits. Objectives. This study assessed the efficacy of motor and cognitive dual-task training programs for improving of ...

In this work we consider a setting where we have a very large number of related tasks with few examples from each individual task. Rather than either learning each task individually (and having a large generalization error) or learning all the tasks together using a single hypothesis (and suffering a potentially large inherent error), we consider learning a small pool of shared hypotheses. Each...

Background: Parkinson Disease (PD) is characterized by motor and non-motor symptoms that affect patients’ functions, especially while performing dual tasks--a critical factor in everyday living. However, many controversies exist about the benefits of dual-task training in patients with PD. Objectives: This study assessed the efficacy of motor and cognitive dual-task training in improving balanc...

The dimensional change card-sorting task (DCCS task) is frequently used to assess young children's executive abilities. However, the source of children's difficulty with this task is still under debate. In the standard DCCS task, children have to sort, for example, test cards with a red cherry or a blue banana into two boxes marked with target cards showing a blue cherry and a red banana. Typic...

Feature singleton search is faster when the target-defining dimension is repeated, rather than changed, across trials (Found & Müller, 1996). A similar dimension repetition benefit has been observed in a non-search (discrimination) task with a single stimulus (Mortier, Theeuwes, & Starreveld, 2005). Two experiments examined whether these effects in the two tasks originate from the same or diffe...

In this paper, we study the generalization performance of regularized multi-task learning (RMTL) in a vector-valued framework, where MTL is considered as a learning process for vector-valued functions. We are mainly concerned with two theoretical questions: 1) under what conditions does RMTL perform better with a smaller task sample size than STL? 2) under what conditions is RMTL generalizable ...

A significant challenge to make learning techniques more suitable for general purpose use is to move beyond i) complete supervision, ii) low dimensional data, iii) a single task and single view per instance. Solving these challenges allows working with “Big Data” problems that are typically high dimensional with multiple (but possibly incomplete) labelings and views. While other work has addres...

Mammals, and humans in particular, are endowed with an exceptional capacity for cumulative learning. This capacity crucially depends on the presence of intrinsic motivations, i.e. motivations that are not directly related to an organism’s survival and reproduction but rather to its ability to learn. Recently, there have been a number of attempts to model and reproduce intrinsic motivations in a...

Many product categories, from pizzas to real estate, present buyers with purchase decisions involving complex area judgments. Does a square look larger or smaller than a circle? How much smaller does a circle of 8-inch diameter look when compared to one with a 10-inch diameter? In this paper, we propose a psychophysical model of how consumers make area comparison judgments. The model involves c...