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PatternNet: Visual Pattern Mining with Deep Neural Network
In this paper, we study the problem of visual pattern mining and propose a novel deep neural network architecture called PatternNet for discovering these patterns that are both discriminative and representative.
Event Specific Multimodal Pattern Mining with Image-Caption Pairs
In this paper we describe a novel framework and algorithms for discovering image patch patterns from a large corpus of weakly supervised image-caption pairs generated from news events.
Objective Variables for Probabilistic Revenue Maximization in Second-Price Auctions with Reserve
In this paper, we develop a probabilistic method to learn a profitable strategy to set the reserve price.
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