In "Opinion pooling on general agendas", we characterize linear and neutral opinion pooling functions F : P ! P, where unlike in the classical opinion pooling problem the agenda X of relevant events need not form a -algebra. These characterizations are based on two conditions on the pooling function: independence and implication-preservation. The latter condition is stronger than the standard (...

Spatial pooling strategies used in recent Image Quality Assessment (IQA) algorithms have generally been that of simply averaging the values of the obtained scores across the image. Given that certain regions in an image are perceptually more important than others, it is not unreasonable to suspect that gains can be achieved by using an appropriate pooling strategy. In this paper, we explore two...

Pooling designs are used in clone library screening to efficiently distinguish positive clones from negative clones. Mathematically, a pooling design is just a nonadaptive group testing scheme which has been extensively studied in the literature. In some applications, there is a third category of clones called "inhibitors" whose effect is to neutralize positives. Specifically, the presence of a...

Hierarchical feed-forward networks have been successfully applied in object recognition. At each level of the hierarchy, features are extracted and encoded, followed by a pooling step. Within this processing pipeline, the common trend is to learn the feature coding templates, often referred as codebook entries, filters, or over-complete basis. Recently, an approach that apparently does not use ...

Learning invariant representations from images is one of the hardest challenges facing computer vision. Spatial pooling is widely used to create invariance to spatial shifting, but it is restricted to convolutional models. In this paper, we propose a novel pooling method that can learn soft clustering of features from image sequences. It is trained to improve the temporal coherence of features,...

The connections between information pooling and adaptability as well as superefficiency are considered. Separable rules, which figure prominently in wavelet and other orthogonal series methods, are shown to lack adaptability; they are necessarily not rate-adaptive. A sharp lower bound on the cost of adaptation for separable rules is obtained. We show that adaptability is achieved through inform...

Transitive distance is an ultrametric with elegant properties for clustering. Conventional transitive distance can be found by referring to the minimum spanning tree (MST). We show that such distance metric can be generalized onto a minimum spanning random forest (MSRF) with element-wise max pooling over the set of transitive distance matrices from an MSRF. Our proposed approach is both intuiti...

Feature extraction, coding and pooling, are important components on many contemporary object recognition paradigms. In this paper we explore novel pooling techniques that encode the second-order statistics of local descriptors inside a region. To achieve this effect, we introduce multiplicative second-order analogues of average and maxpooling that together with appropriate non-linearities lead ...