High utility itemset mining (HUIM) is a new emerging field in data mining which has gained growing interest due to its various applications. The goal of this problem is to discover all itemsets whose utility exceeds minimum threshold. The basic HUIM problem does not consider length of itemsets in its utility measurement and utility values tend to become higher for itemsets containing more items...

Empirical Estimation Results of a Collective Household Time Allocation Model In this paper an empirical model is developed where the collective household model is used as a basic framework to describe the time allocation problem. The collective model views household behavior as the outcome of maximizing a household utility function which is a weighted sum of the utility functions of the male an...

Collecting labeled data is costly and thus is a critical bottleneck in real-world classification tasks. To mitigate the problem, we consider a complementary label, which specifies a class that a pattern does not belong to. Collecting complementary labels would be less laborious than ordinary labels since users do not have to carefully choose the correct class from many candidate classes. Howeve...

at+1 = (1 + r)(at + yt − ct), t = 0, 1, . . . , T r > 0, a0 given Where at denotes assets (or wealth) held at the beginning of period t, yt is labor income in period t, ct denotes consumption expenditure incurred in period t, β is the discount factor, r is the interest rate, and u() represents the period-by-period utility function, assumed to be twice continuously differentiable, strictly incre...

We show, in the Choquet expected utility model, that preference for diversi cation, that is, convex preferences, is equivalent to a concave utility index and a convex capacity. We then introduce a weaker notion of diversi cation, namely \sure diversication." We show that this implies that the core of the capacity is non-empty. The converse holds under concavity of the utility index. This proper...

In uence diagrams have become a popular tool for representing and solving complex decision-making problems under uncertainty. In this paper, we focus on the task of building probability models from expert knowledge, and also on the challenging and less known task of constructing utility models in in uence diagrams. Our goal is to review the state of the art and list some challenges. Similarly t...

Power allocation across users in two adjacent cells is studied for a wireless Code Division Multiple Access (CDMA) network with mixed voice and data services. We assume that each user has a utility function that measures the user’s satisfaction, or utility, as a function of the received Signal-to-Interference-plusNoise-Ratio (SINR). Each particular service (voice or data) is associated with a d...

The optimization problem of general utility case is considered for countable state semi-Markov decision processes. The regret-utility function is introduced as a function of two variables, one is a target value and the other is a present value. We consider the expectation of the regret-utility function incured until the reaching time to a given absorbing set. In order to characterize the regret...

A function u(z) is a utility function if u′(z) ≥ 0. It is called risk averse if we also have u′′(z) ≤ 0. Some authors, however, require that u(i)(z) ≥ 0 if i is odd and u(i)(z) ≤ 0 if i is even. The notion of a multiattribute utility function can be defined by requiring that it is increasing in each variable and concave as an s-variate function. A stronger condition, similar to the one in case ...