… Authors reserve their rights to disseminate the work on their personal and corporate Web
sites with the appropriate attribution. WWW ’19, May 13–17, 2019, San Francisco, CA, USA © …

… the model pay more attention to the feature importance. For specifc CTR prediction task, we
… Concretely speaking, we use some pooling methods such as max or mean to squeeze the …

… attention-based graph embedding for relation prediction. For node classification, graph
attention … prediction, our model generalizes and extends the attention mechanism by guiding …

… to predict the target value ˆy for a new query instance x. A naive estimator will predict the …
the sensitivity of predictions to the change in attention weights and observed that changing …

… Formally, given a multimodal fashion dataset {U, V, O, F , W}, our task is to learn a predictive
function f , such that for each user, it can accurately rank all the fashion items according to his…

… After that, each session is represented as the combination of the global preference and
current interests of this session using an attention net. Finally, we predict the probability of each …

… XMTC can be found in many applications, such as item categorization, web page tagging, and
… prediction efficiency, we use beam search [13, 24]: for the d-th (d > 1) level we only predict …

… could use as an indication of focused attention; … Predictive validity is the degree to which
a measure predicts behavior [96]. If we asked people to rate their engagement with a website …

… step time prediction and short-term time prediction. In this paper, inspired by human attention
… -Ⅱ respectively for long-term time series prediction. Specifically, we first propose the DSTP-…

… the work on their personal and corporate Web sites with the appropriate attribution. WWW
’… flow prediction problem. We use graph neural networks with a position-wise attention mech…