We consider an online learning scenario in which the learner can make predictions on the basis of a fixed set of experts. We derive upper and lower relative loss bounds for a class of universal learning algorithms involving a switching dynamics over the choice of the experts. On the basis of the performance bounds we provide the optimal a priori discretization of the switching-rate parameter that governs the switching dynamics. We demonstrate the algorithm in the context of wireless networks.

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The study of social withdrawal continues to grow among younger samples, including childhood, adolescence, and emerging adulthood. Little research has addressed socially withdrawn older adults, despite the various losses, declines, and changes experienced by those in later life and their known benefits resulting from social interactions. Shy, avoidant, or unsocial individuals at younger ages may withdraw and possibly miss out on important opportunities; as a result, when they are grown, these same socially withdrawn individuals may experience greater regret and lower fulfillment in later life. Further, socially withdrawn older adults residing in long-term care (LTC) facilities may have more time to reminisce of past regret or fulfillment. Data was collected from 45 older participants (Mage = 83.07) residing in a long-term care facility on O'ahu. The current study used Bayesian linear regression models to examine ways that three subtypes of withdrawal (shyness, avoidance, and unsociability) may relate to regret and fulfillment in later life; with an exploratory qualitative portion assessing withdrawn participant's biggest regrets and accomplishments. Results indicated that higher levels of shyness significantly predicted higher levels of regret, while higher levels of unsociability were related to higher levels of fulfillment. The findings may help us to understand the role of ability to choose in the lives of socially withdrawn individuals, as shy individuals who may withdraw because of fear could be missing out on desired life experiences, while unsocial individuals appear able to participate in their desired activities.

This research proposes a new construct, post-purchase anticipated regret (PPAR), to expand the existing retailing and regret theory literature streams. Specifically, the purpose of this research is to understand the antecedents and consequences of post-purchase anticipated regret in an online retailing context. Study 1 uses qualitative data drawn from depth-interviews with online shoppers to investigate the pre-purchase factors that contribute to PPAR formation. Building from these results, studies 2 and 3 empirically test an original conceptual model to holistically understand PPAR. Additionally, the role of online shopping self-affirmation and regret coping strategies are explored as means to combat PPAR formation. Managerial and theoretical implications are offered, as well as research limitations and future research directions.

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