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We describe the 1st place winning approach for the CIKM Cup 2016 Challenge.In this paper, we provide an approach to reasonably identify same users acrossmultiple devices based on browsing logs. Our approach regards a candidateranking problem as pairwise classification and utilizes an unsupervised neuralfeature ensemble approach to learn latent features of users. Combined withtraditional hand crafted features, each user pair feature is fed into asupervised classifier in order to perform pairwise classification. Lastly, wepropose supervised and unsupervised inference techniques.

Cross Device Matching for Online Advertising with Neural Feature Ensembles : First Place Solution at CIKM Cup 2016