Compatibility Family Learning for Item Recommendation and Generation

Compatibility between items, such as clothes and shoes, is a major factor among customer's purchasing decisions. However, learning "compatibility" is challenging due to (1) broader notions of compatibility than those of similarity, (2) the asymmetric nature of compatibility, and (3) only a small set of compatible and incompatible items are observed. We propose an end-to-end trainable system to embed each item into a latent vector and project a query item into K compatible prototypes in the same space. These prototypes reflect the broad notions of compatibility. We refer to both the embedding and prototypes as "Compatibility Family". In our learned space, we introduce a novel Projected Compatibility Distance (PCD) function which is differentiable and ensures diversity by aiming for at least one prototype to be close to a compatible item, whereas none of the prototypes are close to an incompatible item. We evaluate our system on a toy dataset, two Amazon product datasets, and Polyvore outfit dataset. Our method consistently achieves state-of-the-art performance. Finally, we show that we can visualize the candidate compatible prototypes using a Metric-regularized Conditional Generative Adversarial Network (MrCGAN), where the input is a projected prototype and the output is a generated image of a compatible item. We ask human evaluators to judge the relative compatibility between our generated images and images generated by CGANs conditioned directly on query items. Our generated images are significantly preferred, with roughly twice the number of votes as others.Comment: 9 pages, accepted to AAAI 201

Motor neuron-derived Thsd7a is essential for zebrafish vascular development via the Notch-dll4 signaling pathway.

BackgroundDevelopment of neural and vascular systems displays astonishing similarities among vertebrates. This parallelism is under a precise control of complex guidance signals and neurovascular interactions. Previously, our group identified a highly conserved neural protein called thrombospondin type I domain containing 7A (THSD7A). Soluble THSD7A promoted and guided endothelial cell migration, tube formation and sprouting. In addition, we showed that thsd7a could be detected in the nervous system and was required for intersegmental vessels (ISV) patterning during zebrafish development. However, the exact origin of THSD7A and its effect on neurovascular interaction remains unclear.ResultsIn this study, we discovered that zebrafish thsd7a was expressed in the primary motor neurons. Knockdown of Thsd7a disrupted normal primary motor neuron formation and ISV sprouting in the Tg(kdr:EGFP/mnx1:TagRFP) double transgenic zebrafish. Interestingly, we found that Thsd7a morphants displayed distinct phenotypes that are very similar to the loss of Notch-delta like 4 (dll4) signaling. Transcript profiling further revealed that expression levels of notch1b and its downstream targets, vegfr2/3 and nrarpb, were down-regulated in the Thsd7a morphants. These data supported that zebrafish Thsd7a could regulate angiogenic sprouting via Notch-dll4 signaling during development.ConclusionsOur results suggested that motor neuron-derived Thsd7a plays a significant role in neurovascular interactions. Thsd7a could regulate ISV angiogenesis via Notch-dll4 signaling. Thus, Thsd7a is a potent angioneurin involved in the development of both neural and vascular systems

Depth, balancing, and limits of the Elo model

-Much work has been devoted to the computational complexity of games. However, they are not necessarily relevant for estimating the complexity in human terms. Therefore, human-centered measures have been proposed, e.g. the depth. This paper discusses the depth of various games, extends it to a continuous measure. We provide new depth results and present tool (given-first-move, pie rule, size extension) for increasing it. We also use these measures for analyzing games and opening moves in Y, NoGo, Killall Go, and the effect of pie rules

A mutant tat protein inhibits HIV-1 reverse transcription by targeting the reverse transcription complex

Previously, we reported that a mutant of Tat referred to as Nullbasic inhibits HIV-1 reverse transcription although the mechanism of action is unknown. Here we show that Nullbasic is a reverse transcriptase (RT) binding protein that targets the reverse transcription complex rather than directly inhibiting RT activity. An interaction between Nullbasic and RT was observed by using coimmunoprecipitation and pulldown assays, and a direct interaction was measured by using a biolayer interferometry assay. Mixtures of recombinant 6 x His-RT and Nullbasic-FLAG-V5-6 x His at molar ratios of up to 1:20,000 did not inhibit RT activity in standard homopolymer primer template assays. An analysis of virus made by cells that coexpressed Nullbasic showed that Nullbasic copurified with virus particles, indicating that it was a virion protein. In addition, analysis of reverse transcription complexes (RTCs) isolated from cells infected with wild type or Nullbasic-treated HIV-1 showed that Nullbasic reduced the levels of viral DNA in RTC fractions. In addition, a shift in the distribution of viral DNA and CAp24 to less-dense non-RTC fractions was observed, indicating that RTC activity from Nullbasic-treated virus was impaired. Further analysis showed that viral cores isolated from Nullbasic-treated HIV undergo increased disassembly in vitro compared to untreated HIV-1. To our knowledge, this is the first description of an antiviral protein that inhibits reverse transcription by targeting the RTC and affecting core stability

Customer Active Probability and Customer Lifetime Value Analysis in Internet

As the age of digital information, marketers are in information overload. A mass of customers’ data is available but may be useless only if it can be turned into business intelligence and implement appropriate database marketing. This research aims to assist managers in discriminating and learning from their right customers that helps to serve high value customers and create successful marketing programs targeted at the prospected ones. Transaction data on the purchasing of VCD at an online retailer was used as empirical analysis; Pareto/NBD model and customer lifetime value model were applied to capture customer active probability and construct profitable customer profile. The results demonstrated four priority ranks of online customers for managers to choose the prospects that best match the profitable customer profile by observing their purchase behaviors