诺库维普

A Review of Anticipatory Pleasure in Schizophrenia 2017-05-09 23:40:27

anhedonia; psychosis; cognition; memory;prospection; || Katherine H. Frost & Gregory P. Strauss

BPR: Bayesian Personalized Ranking from Implicit Feedback 2017-05-08 19:49:23

Item recommendation is the task of predict- ing a personalized ranking on a set of items (e.g. websites, movies, products). In this paper, we investigate the most common sce- nario with implicit feedback (e.g. clicks, purchases). There are many methods for item recommendation from implicit feedback ... || BPR; pairwise; 抑制过拟合使得排序成为可能; || Steffen Rendle, Christoph Freudenthaler, Zeno Gantner and Lars Schmidt-Thieme...

GREEDY FUNCTION APPROXIMATION: A GRADIENT BOOSTING MACHINE 2017-04-23 15:11:56

Function estimation/approximation is viewed from the perspective of numerical optimization in function space, rather than parameter space. A connection is made between stagewise additive expansions and steepest- descent minimization. A general gradient descent “boosting” paradigm is developed for ad... || 4000 citations; gradient boosting; || Jerome H. Friedman...

Ensemble Methods in Machine Learning 2017-04-23 12:05:27

Ensemble methods are learning algorithms that construct a set of classifiers and then classify new data points by taking a (weighted) vote of their predictions. The original ensemble method is Bayesian averaging, but more recent algorithms include error-correcting output coding, Bagging, and boostin... || Ensemble; 3000 citions; 集成学习; boosting; bootstrap; bagging (bootstap aggregating); gradient boosting; Adaboost 抽样方法; || Thomas G Dietterich...

COT: Contextual Operating Tensor for Context-aware Recommender Systems 2017-04-18 19:43:06

With rapid growth of information on the Internet, recommender systems become fundamental for helping users alleviate the problem of information overload. Since contextual information can be used as a significant factor in modeling user behavior, various context-aware recommendation methods are propo... || MF; Tensor; nlp; || Qiang Liu, Shu Wu, Liang Wang...

Model selection for medical diagnosis decision support systems 2017-04-14 21:51:30

In this paper, we examine the model section decision for a medical diagnostic decision support system (MDSS). Our purpose in doing this is to understand how model selection affects the accuracy of the decision support system. We explore two related research questions: (1) Do ensembles of models, act... || Model selection; Medical diagnosis; Neural networks; Bootstrap aggregating models; Diverse ensembles; Baseline ensembles; Bagging models; || Paul Mangiameli...

精神分裂症患者动机缺损研究总结 2017-04-13 16:13:25

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WWW 23

Austin, Texas, USA,

AAAI 23

Washington, DC, USA,

SIGIR2022

Madrid, Spain, July 11th to 15th, 2022

WSDM2023

TBD,

IJCAI2022

Austria, July 23-29, 2022