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Many existing deep learning models for natural language processing tasks focus on learning the compositionality of their inputs , which requires many expensive computations. We present a simple deep neural network that competes with and, in some cases, outperforms such models on sentiment analysis and factoid question answering tasks while taking only a(More)
We present a supervised binary encoding scheme for image retrieval that learns projections by taking into account similarity between classes obtained from output embeddings. Our motivation is that binary hash codes learned in this way improve the visual quality of retrieval results by ranking related (or ``sibling'') class images before unrelated class(More)
Visual narrative is often a combination of explicit information and judicious omissions, relying on the viewer to supply missing details. In comics, most movements in time and space are hidden in the " gutters " between panels. To follow the story, readers logically connect panels together by inferring unseen actions through a process called " closure ".(More)
Fig. 1. MetroViz begins with a broad overview of any public transportation dataset with its map view and route view. Abstract— Understanding the quality and usage of public transportation resources is important for schedule optimization and resource allocation. Ridership and adherence are the two main dimensions for evaluating the quality of service. Using(More)
We present a supervised binary encoding scheme for image retrieval that learns projections by taking into account similarity between classes obtained from output em-beddings. Our motivation is that binary hash codes learned in this way improve both the visual quality of retrieval results and existing supervised hashing schemes. We employ a sequential greedy(More)
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