Molecular similarity is a pervasive concept in chemistry. It is essential to many aspects of chemical reasoning and analysis and is perhaps the fundamental assumption underlying medicinal chemistry. Dissimilarity, the complement of similarity, also plays a major role in a growing number of applications of molecular diversity in combinatorial chemistry, high-throughput screening, and related fie...

Transfer learning methods address the situation where little labeled training data from the “target” problem exists, but much training data from a related “source” domain is available. However, the overwhelming majority of transfer learning methods are designed for simple settings where the source and target predictive functions are almost identical, limiting the applicability of transfer learn...

Partitioning a data set and extracting hidden structure from the data arises in different application areas of pattern recognition, speech and image processing. Pairwise data clustering is a combinatorial optimization method for data grouping which extracts hidden structure from proximity data. We describe a deterministic annealing approach to pairwise clustering which shares the robustness pro...

This paper is about labelling regions of a mobile robot’s workspace using scene appearance similarity. We do this by operating on a single matrix which expresses the pairwise similarity between all captured scenes. We describe and motivate a sequence of algorithms which, in conjunction with spatial constraints provided by the continuous motion of the vehicle, produce meaningful workspace segmen...

This paper presents a novel symmetric graph regularization framework for pairwise constraint propagation. We first decompose the challenging problem of pairwise constraint propagation into a series of two-class label propagation subproblems and then deal with these subproblems by quadratic optimization with symmetric graph regularization. More importantly, we clearly show that pairwise constrai...

To uncover rules in a treebank grammar which are of dubious quality, we investigate two methods for detecting problematic structures, both based on the same notion of similarity. The first is based on the notion that similar rules should receive the same annotation. The second is based on the idea that rules which are dissimilar to other rules are likely problematic. We show these two methods t...

We propose a novel interest point detector stemming from the intuition that image patches which are highly dissimilar over a relatively large extent of their surroundings hold the property of being repeatable and distinctive. This concept of contextual self-dissimilarity reverses the key paradigm of recent successful techniques such as the Local Self-Similarity descriptor and the Non-Local Mean...

The similarity and dissimilarity is a corresponding relationship which is the base of cognitive judgments. The main purpose of this paper is to study the user perception by using similarity judgments. In this study, fifteen innovative products are used as the stimuli which divided into three groups: global, creative and local products. A total of 139 student volunteers participated in the vario...

Case-based reasoning (CBR) attempts to solve new problems by using previous experiences. However traditional CBR systems are restricted by the similarity requirement, i.e., the availability of similar cases to new problems. This paper proposes a novel CBR approach that exploits dissimilarity information in problem solving. A fuzzy dissimilarity model consisting of fuzzy rules has been developed...