This paper presents the essential elements for developing objective methods of assessment of the performance of time-frequency signal analysis techniques. We define a measure for assessing the resolution performance of time-frequency distributions (TFDs) in separating closely spaced components in the time-frequency domain. The measure takes into account key attributes of TFDs, such as component...

| Visualization provides a means for exploratory analysis of large scale, complex data. In domains such as network management, these data often have categorical attributes, such as host names and event types. Unfortunately, large scale visualiza-tions of categorical data are diicult to construct since categorical values have no inherent order. We consider two visual tasks: nding groups of simil...

In this paper we develop a neural network which learns intermodal representations for fashion attributes to be utilized in a cross-modal search tool. Our neural network learns from organic e-commerce data, which is characterized by clean image material, but noisy and incomplete product descriptions. First, we experiment with techniques to segment ecommerce images and their product descriptions ...

Hedonic pricing models attempt to model a relationship between object attributes and the object’s price. Traditional hedonic pricing models are often parametric models that suffer from misspecification. In this paper we create these models by means of boosted CART models. The method is explained in detail and applied to various datasets. Empirically, we find substantial reduction of errors on o...