Graph Convolutional Neural Networks for Web-Scale Recommender Systems

Recent advancements in deep neural networks for graph-structured data have led to state-of-the-art performance on recommender system benchmarks. However, making these methods practical and scalable to web-scale recommendation tasks with billions of items and hundreds of millions of users remains a challenge. Here we describe a large-scale deep recommendation engine that we developed and deployed at Pinterest. We develop a data-efficient Graph Convolutional Network (GCN) algorithm PinSage, which combines efficient random walks and graph convolutions to generate embeddings of nodes (i.e., items) that incorporate both graph structure as well as node feature information. Compared to prior GCN approaches, we develop a novel method based on highly efficient random walks to structure the convolutions and design a novel training strategy that relies on harder-and-harder training examples to improve robustness and convergence of the model. We also develop an efficient MapReduce model inference algorithm to generate embeddings using a trained model. We deploy PinSage at Pinterest and train it on 7.5 billion examples on a graph with 3 billion nodes representing pins and boards, and 18 billion edges. According to offline metrics, user studies and A/B tests, PinSage generates higher-quality recommendations than comparable deep learning and graph-based alternatives. To our knowledge, this is the largest application of deep graph embeddings to date and paves the way for a new generation of web-scale recommender systems based on graph convolutional architectures.Comment: KDD 201

Remarks on the extension of the Ricci flow

We present two new conditions to extend the Ricci flow on a compact manifold over a finite time, which are improvements of some known extension theorems.Comment: 9 pages, to appear in Journal of Geometric Analysi

Combining Diffusion NMR and Small-Angle Neutron Scattering Enables Precise Measurements of Polymer Chain Compression in a Crowded Environment

The effect of particles on the behavior of polymers in solution is important in a number of important phenomena such as the effect of “crowding” proteins in cells, colloid-polymer mixtures, and nanoparticle “fillers” in polymer solutions and melts. In this Letter, we study the effect of spherical inert nanoparticles (which we refer to as “crowders”) on the diffusion coefficient and radius of gyration of polymers in solution using pulsed-field-gradient NMR and small-angle neutron scattering (SANS), respectively. The diffusion coefficients exhibit a plateau below a characteristic polymer concentration, which we identify as the overlap threshold concentration c⋆. Above c⋆, in a crossover region between the dilute and semidilute regimes, the (long-time) self-diffusion coefficients are found, universally, to decrease exponentially with polymer concentration at all crowder packing fractions, consistent with a structural basis for the long-time dynamics. The radius of gyration obtained from SANS in the crossover regime changes linearly with an increase in polymer concentration, and must be extrapolated to c⋆ in order to obtain the radius of gyration of an individual polymer chain. When the polymer radius of gyration and crowder size are comparable, the polymer size is very weakly affected by the presence of crowders, consistent with recent computer simulations. There is significant chain compression, however, when the crowder size is much smaller than the polymer radius gyration

Quaternion-Based Self-Attentive Long Short-Term User Preference Encoding for Recommendation

Quaternion space has brought several benefits over the traditional Euclidean space: Quaternions (i) consist of a real and three imaginary components, encouraging richer representations; (ii) utilize Hamilton product which better encodes the inter-latent interactions across multiple Quaternion components; and (iii) result in a model with smaller degrees of freedom and less prone to overfitting. Unfortunately, most of the current recommender systems rely on real-valued representations in Euclidean space to model either user's long-term or short-term interests. In this paper, we fully utilize Quaternion space to model both user's long-term and short-term preferences. We first propose a QUaternion-based self-Attentive Long term user Encoding (QUALE) to study the user's long-term intents. Then, we propose a QUaternion-based self-Attentive Short term user Encoding (QUASE) to learn the user's short-term interests. To enhance our models' capability, we propose to fuse QUALE and QUASE into one model, namely QUALSE, by using a Quaternion-based gating mechanism. We further develop Quaternion-based Adversarial learning along with the Bayesian Personalized Ranking (QABPR) to improve our model's robustness. Extensive experiments on six real-world datasets show that our fused QUALSE model outperformed 11 state-of-the-art baselines, improving 8.43% at HIT@1 and 10.27% at NDCG@1 on average compared with the best baseline

Anomalous Stability of nu=1 Bilayer Quantum Hall State

We have studied the fractional and integer quantum Hall (QH) effects in a high-mobility double-layer two-dimensional electron system. We have compared the "stability" of the QH state in balanced and unbalanced double quantum wells. The behavior of the n=1 QH state is found to be strikingly different from all others. It is anomalously stable, though all other states decay, as the electron density is made unbalanced between the two quantum wells. We interpret the peculiar features of the nu=1 state as the consequences of the interlayer quantum coherence developed spontaneously on the basis of the composite-boson picture.Comment: 5 pages, 6 figure

Self-assembly and charge transport properties of a benzobisthiazole end-capped with dihexylthienothiophene units

The synthesis of a new conjugated material is reported; BDHTT–BBT features a central electron-deficient benzobisthiazole capped with two 3,6-dihexyl-thieno[3,2-b]thiophenes. Cyclic voltammetry was used to determine the HOMO (−5.7 eV) and LUMO (−2.9 eV) levels. The solid-state properties of the compound were investigated by X-ray diffraction on single-crystal and thin-film samples. OFETs were constructed with vacuum deposited films of BDHTT–BBT. The films displayed phase transitions over a range of temperatures and the morphology of the films affected the charge transport properties of the films. The maximum hole mobility observed from bottom-contact, top-gate devices was 3 × 10−3 cm2 V−1 s−1, with an on/off ratio of 104–105 and a threshold voltage of −42 V. The morphological and self-assembly characteristics versus electronic properties are discussed for future improvement of OFET devices

Cardiac hypertrophy is inhibited by a local pool of cAMP regulated by phosphodiesterase 2

Rationale: Chronic elevation of 3'-5'-cyclic adenosine monophosphate (cAMP) levels has been associated with cardiac remodelling and cardiac hypertrophy. However, enhancement of particular aspects of cAMP/protein kinase A (PKA) signalling appears to be beneficial for the failing heart. cAMP is a pleiotropic second messenger with the ability to generate multiple functional outcomes in response to different extracellular stimuli with strict fidelity, a feature that relies on the spatial segregation of the cAMP pathway components in signalling microdomains. Objective: How individual cAMP microdomains impact on cardiac pathophysiology remains largely to be established. The cAMP-degrading enzymes phosphodiesterases (PDEs) play a key role in shaping local changes in cAMP. Here we investigated the effect of specific inhibition of selected PDEs on cardiac myocyte hypertrophic growth. Methods and Results: Using pharmacological and genetic manipulation of PDE activity we found that the rise in cAMP resulting from inhibition of PDE3 and PDE4 induces hypertrophy whereas increasing cAMP levels via PDE2 inhibition is anti-hypertrophic. By real-time imaging of cAMP levels in intact myocytes and selective displacement of PKA isoforms we demonstrate that the anti-hypertrophic effect of PDE2 inhibition involves the generation of a local pool of cAMP and activation of a PKA type II subset leading to phosphorylation of the nuclear factor of activated T cells (NFAT). Conclusions: Different cAMP pools have opposing effects on cardiac myocyte cell size. PDE2 emerges as a novel key regulator of cardiac hypertrophy in vitro and in vivo and its inhibition may have therapeutic applications

The relative importance of electron-electron interactions compared to disorder in the two-dimensional "metallic" state

The effect of substrate bias and surface gate voltage on the low temperature resistivity of a Si-MOSFET is studied for electron concentrations where the resistivity increases with increasing temperature. This technique offers two degrees of freedom for controlling the electron concentration and the device mobility, thereby providing a means to evaluate the relative importance of electron-electron interactions and disorder in this so-called ``metallic'' regime. For temperatures well below the Fermi temperature, the data obey a scaling law where the disorder parameter ($k_{\rm{F}}l$), and not the concentration, appears explicitly. This suggests that interactions, although present, do not alter the Fermi-liquid properties of the system fundamentally. Furthermore, this experimental observation is reproduced in results of calculations based on temperature-dependent screening, in the context of Drude-Boltzmann theory.Comment: 5 pages, 6 figure

Sulforaphane Protects the Liver against CdSe Quantum Dot-Induced Cytotoxicity.

The potential cytotoxicity of cadmium selenide (CdSe) quantum dots (QDs) presents a barrier to their use in biomedical imaging or as diagnostic and therapeutic agents. Sulforaphane (SFN) is a chemoprotective compound derived from cruciferous vegetables which can up-regulate antioxidant enzymes and induce apoptosis and autophagy. This study reports the effects of SFN on CdSe QD-induced cytotoxicity in immortalised human hepatocytes and in the livers of mice. CdSe QDs induced dose-dependent cell death in hepatocytes with an IC50 = 20.4 μM. Pre-treatment with SFN (5 μM) increased cell viability in response to CdSe QDs (20 μM) from 49.5 to 89.3%. SFN induced a pro-oxidant effect characterized by depletion of intracellular reduced glutathione during short term exposure (3-6 h), followed by up-regulation of antioxidant enzymes and glutathione levels at 24 h. SFN also caused Nrf2 translocation into the nucleus, up-regulation of antioxidant enzymes and autophagy. siRNA knockdown of Nrf2 suggests that the Nrf2 pathway plays a role in the protection against CdSe QD-induced cell death. Wortmannin inhibition of SFN-induced autophagy significantly suppressed the protective effect of SFN on CdSe QD-induced cell death. Moreover, the role of autophagy in SFN protection against CdSe QD-induced cell death was confirmed using mouse embryonic fibroblasts lacking ATG5. CdSe QDs caused significant liver damage in mice, and this was decreased by SFN treatment. In conclusion, SFN attenuated the cytotoxicity of CdSe QDs in both human hepatocytes and in the mouse liver, and this protection was associated with the induction of Nrf2 pathway and autophagy