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We propose a method for understanding the 3D geometry of indoor environments (e.g. bedrooms, kitchens) while simultaneously identifying objects in the scene (e.g. beds, couches, doors). We focus on how modeling the geometry and location of specific objects is helpful for indoor scene understanding. For example, beds are shorter than they are wide, and are(More)
Recombinant polypeptides and protein domains containing two cysteine pairs located distal in primary sequence but proximal in the native folded or assembled state are labeled selectively in vitro and in mammalian cells using the profluorescent biarsenical reagents FlAsH-EDT2 and ReAsH-EDT2. This strategy, termed bipartite tetracysteine display, enables the(More)
Lexical semantic models provide robust performance for question answering, but, in general, can only capitalize on direct evidence seen during training. For example, monolingual alignment models acquire term alignment probabilities from semi-structured data such as question-answer pairs; neural network language models learn term embeddings from unstructured(More)
We investigate the hypothesis that word representations ought to incorporate both distributional and relational semantics. To this end, we employ the Alternating Direction Method of Multipliers (ADMM), which flexibly optimizes a distribu-tional objective on raw text and a relational objective on WordNet. Preliminary results on knowledge base completion,(More)
—We investigate the predictive power behind the language of food on social media. We collect a corpus of over three million food-related posts from Twitter and demonstrate that many latent population characteristics can be directly predicted from this data: overweight rate, diabetes rate, political leaning, and home geographical location of authors. For all(More)
Figure 1: Map of TVCG based on 1,343 TVCG titles in DBLP, heatmap overlay based on 34 papers by the most prolific TVCG author. The terms in the map are contained in 1,041 TVCG titles (78% coverage). ABSTRACT We describe a practical approach for visual exploration of research papers. Specifically, we use the titles of papers from the DBLP database to create(More)
Challenging environments have guided nature in the development of ultrastable protein complexes. Specialized bacteria produce discrete multi-component protein networks called cellulosomes to effectively digest lignocellulosic biomass. While network assembly is enabled by protein interactions with commonplace affinities, we show that certain cellulosomal(More)
NIR imaging methods do not require ionizing radiation and have great potential for detecting caries lesions (tooth decay) on high-risk proximal and occlusal tooth surfaces and at the earliest stages of development. Previous in vitro and in vivo studies at 1300-nm demonstrated that high contrast reflectance and transillumination images could be acquired of(More)
Several compositional distributional semantic methods use tensors to model multi-way interactions between vectors. Unfortunately, the size of the tensors can make their use impractical in large-scale implementations. In this paper, we investigate whether we can match the performance of full tensors with low-rank approximations that use a fraction of the(More)
Cellulosic waste represents a significant and underutilized carbon source for the biofuel industry. Owing to the recalcitrance of crystalline cellulose to enzymatic degradation, it is necessary to design economical methods of liberating the fermentable sugars required for bioethanol production. One route towards unlocking the potential of cellulosic waste(More)