Carbon pricing has emerged as a prominent policy tool to mitigate climate change due to its
proclaimed high efficiency and effectiveness. However, the successful and sustainable …

Metalearning is the study of principled methods that exploit metaknowledge to obtain
efficient models and solutions by adapting machine learning and data mining processes …

This paper examines the problem of aggregating ordinal preferences on a set of alternatives
into a consensus. This problem has been the subject of study for more than two centuries …

In the multiple-attribute group decision-making (MAGDM), the decision objective is to obtain
a complete ranking of the alternatives from best to worst. In the real world, however …

In group decision making, it is inevitable that the individual decision maker's subjectivity is
involved, which causes difficulty in reaching a group decision. One of the difficulties is to …

Cardinal scores (numeric ratings) collected from people are well known to suffer from
miscalibrations. A popular approach to address this issue is to assume simplistic models of …

This paper mainly proposes a new method for clustering linear ordinal ranking (LOR)
information by agglomerative hierarchical clustering (AHC) algorithm. Considering that the …

Preference rankings virtually appear in all fields of science (political sciences, behavioral
sciences, machine learning, decision making and so on). The well-known social choice …

Preference aggregation mechanisms help decision-makers combine diverse preference
rankings produced by multiple voters into a single consensus ranking. Prior work has …

Empirical analysis serves as an important complement to theoretical analysis for studying
practical Bayesian optimization. Often empirical insights expose strengths and weaknesses …