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In “Optimized slowdown in real-time task systems”, Jejurikar and Gupta investigated energy savings due to optimal slowdown of periodic tasks in real-time task systems, where tasks have varying power c...
The use of autonomous, mobile professional service robotsin diverse workplaces is expected to grow substantially over the next decade. These robots often will work side by side with people, collabor...
We propose a reinforcement learning solution to the \emph{soccer dribbling task}, a scenario in which a soccer agent has to go from the beginning to the end of a region keeping possession of the ball,...
Since its inception, the modus operandi of multi-task learning (MTL) has been to minimize the task-wise mean of the empirical risks. We introduce a generalized loss-compositional paradigm for MTL that...
We develop a highly scalable optimization method called “hierarchical group-thresholding”for solving a multi-task regression model with complex structured sparsity constraints on both input and output...
There is common consensus that executive compensation is strongly tied to firm size and much less so to financial performance. One suspects that observed strategic change in corporations may have an e...
In this commentary we argue that, while task shifting holds great promise, any long-term success of task shifting hinges on serious political and financial commitments. We reason...
The changing telecommunication environment means that service providers, and particularly those that were once State enterprises or protected monopolies, must renew their strategic vision in keeping w...
Kiasu reflects an “obsessive concern with gtting the most out of every transaction and a desire to get ahead of others” (Hwang, ng, & Francesco, 2002: 75). It can have both positive and negative ...
Adult attention deficit disorders (AAD) and stress are pervasive and significant experiences with mostly harmful consequences for both employees and organizations as a whole. This research study ...
We discuss multi-task online learning when a decision maker has to deal simultaneously with M tasks. The tasks are related, which is modeled by imposing that the M–tuple of actions taken by the de...
We study the problem of estimating multiple linear regression equations for the purpose of both prediction and variable selection. Following recent work on multi-task learning Argyriou et al. [2008]...
Groupthink is a problem that often plagues decision-making groups. Group support systems (GSS), an advanced computer-based technology for support decision-making and related group activities, may prov...
One of the most obvious trends over the last two decades has been the gradual erosion of central bank power by market forces. Central banks are operating under ever tighter constraints as financial ...

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