Semi-supervised learning (SSL) is an important research problem in machine learning. While it is usually expected that the use of unlabeled data can improve performance, in many cases SSL is outperformed by supervised learning using only labeled data. To this end, the construction of a performance-safe SSL method has become a key issue of SSL study. To alleviate this problem, we propose in this...

In the paper by Mattikalli et al.[5], the stability of an assemblage of frictionless contacting bodies with uniform gravity was considered. The problem of finding a stable orientation for such an assembly was formulated as a constrained maximin problem. A solution to the maximin problem yielded an orientation of the assembly that was stable under gravity; however, if no such orientation existed...

We consider maximin and Bayesian D-optimal designs for nonlinear regression models. The maximin criterion requires the specification of a region for the nonlinear parameters in the model, while the Bayesian optimality criterion assumes that a prior distribution for these parameters is available. It was observed empirically by many authors that an increase of uncertainty in the prior information...

The Multi-Armed Bandit(MAB) problem is named after slot machine games. When playing slot machines, one player has to decide which machine to play, in which order to play them and how many times to play each machine. After the choice, that specific machine will offer a random reward from a probability distribution, and the player’s target is to maximize the sum of rewards earned through a sequen...

The knowledge-based rational decision model (KBR-model), developed in [1], offers an approach to rational decision making in a non-probabilistic setting, e.g., in perfect information games with deterministic payoffs. The KBR-model is an epistemically explicit form of standard game-theoretical assumptions, e.g., Harsanyi’s Maximin Postulate. This model suggests following maximin strategy over al...

In this paper, we describe an adjusted method to facilitate a non-inferiority trial by a three-arm robust design. Because local optimal designs derived in Hasler et al. [2007] require knowledge about the ratios of the population variances and are not necessarily robust with respect to possible misspecifications, a maximin approach is adopted. This method requires only the specification of an in...

This paper analyzes decisions on emissions of a stock pollutant under uncertainty in a two period model. Decisions are based on a weighted average of expected utility (EU) and the MaxiMin criterion. I first show that more weight on the worst case (less weight on EU) may lead to increased first period emissions. The effect of learning possibilities on emissions is not clear in general, but depen...

This paper is concerned with the problem of finding a vector from a given set in a Euclidean space that maximizes the worst-case correlation with vectors in this set, where ‘worst’ means smallest. This problem, called the maximin correlation problem (MCP), comes up in several disciplines including pattern classification, portfolio selection, statistics, and signal processing. With a general inf...