Neural Collaborative Filtering

In recent years, deep neural networks have yielded immense success on speech recognition, computer vision and natural language processing. However, the exploration of deep neural networks on recommender systems has received relatively less scrutiny. In this work, we strive to develop techniques based on neural networks to tackle the key problem in recommendation -- collaborative filtering -- on the basis of implicit feedback. Although some recent work has employed deep learning for recommendation, they primarily used it to model auxiliary information, such as textual descriptions of items and acoustic features of musics. When it comes to model the key factor in collaborative filtering -- the interaction between user and item features, they still resorted to matrix factorization and applied an inner product on the latent features of users and items. By replacing the inner product with a neural architecture that can learn an arbitrary function from data, we present a general framework named NCF, short for Neural network-based Collaborative Filtering. NCF is generic and can express and generalize matrix factorization under its framework. To supercharge NCF modelling with non-linearities, we propose to leverage a multi-layer perceptron to learn the user-item interaction function. Extensive experiments on two real-world datasets show significant improvements of our proposed NCF framework over the state-of-the-art methods. Empirical evidence shows that using deeper layers of neural networks offers better recommendation performance.Comment: 10 pages, 7 figure

Meta-analysis: Which Components of Parent Training Work for Children With Attention-Deficit/Hyperactivity Disorder?

Objective: Behavioral parent training is an evidence-based intervention for children with attention-deficit/hyperactivity disorder (ADHD), but it is unknown which of its components are most effective. This meta-regression analysis investigated which specific behavioral techniques that parents learn in parent training are associated with effects on parental outcomes. Method: A search was performed for randomized controlled trials on parent training for children with ADHD, with positive parenting, negative parenting, parenting sense of competence, parent–child relationship quality, and parental mental health as outcome measures. After screening 23,026 publications, 29 studies contributing 138 effect sizes were included (N = 2,345). For each study, the dosage of 39 behavioral techniques was derived from intervention manuals, and meta-regression determined which techniques were related to outcomes. Results: Parent training had robust small- to medium-sized positive effects on all parental outcomes relative to control conditions, both for unblinded and probably blinded measures. A higher dosage of techniques focusing on the manipulation of antecedents of behavior was associated with better outcomes on parenting sense of competence and parental mental health, and a higher dosage of techniques focusing on reinforcement of desired behaviors was related to larger decreases in negative parenting. Higher dosages of psychoeducation were negatively related to parental outcomes. Conclusion: Although techniques were not investigated in isolation, the results suggested that manipulation of antecedents of behavior and reinforcement techniques are key components of parent training for children with ADHD in relation to parental outcomes. These exploratory findings may help to strengthen and tailor parent training interventions for children with ADHD

Where Are The M Dwarf Disks Older Than 10 Million Years?

We present 11.7-micron observations of nine late-type dwarfs obtained at the Keck I 10-meter telescope in December 2002 and April 2003. Our targets were selected for their youth or apparent IRAS 12-micron excess. For all nine sources, excess infrared emission is not detected. We find that stellar wind drag can dominate the circumstellar grain removal and plausibly explain the dearth of M Dwarf systems older than 10 Myr with currently detected infrared excesses. We predict M dwarfs possess fractional infrared excess on the order of L_{IR}/L_{*}\sim10^{-6} and this may be detectable with future efforts.Comment: 24 pages, 2 figures, accepted to Ap

X-Ray Spectroscopy of II Pegasi: Coronal Temperature Structure, Abundances, and Variability

We have obtained high resolution X-ray spectra of the coronally active binary, II Pegasi (HD 224085), covering the wavelength range of 1.5-25 Angstroms. For the first half of our 44 ksec observation, the source was in a quiescent state with constant X-ray flux, after which it flared, reaching twice the quiescent flux in 12 ksec, then decreasing. We analyze the emission-line spectrum and continuum during quiescent and flaring states. The differential emission measure derived from lines fluxes shows a hot corona with a continuous distribution in temperature. During the non-flare state, the distribution peaks near log T = 7.2, and when flaring, near 7.6. High-temperature lines are enhanced slightly during the flare, but most of the change occurs in the continuum. Coronal abundance anomalies are apparent, with iron very deficient relative to oxygen and significantly weaker than expected from photospheric measurements, while neon is enhanced relative to oxygen. We find no evidence of appreciable resonant scattering optical depth in line ratios of iron and oxygen. The flare light curve is consistent with Solar two-ribbon flare models, but with a very long reconnection time-constant of about 65 ks. We infer loop lengths of about 0.05 stellar radii, to about 0.25 in the flare, if the flare emission originated from a single, low-density loop.Comment: 25 pages, 5 figures, 3 tables, accepted by ApJ (scheduled for the v559 n2 p1 Oct 1, 2001 issue