诺库维普

LDA 笔记 2017-06-22 23:22:39

LDA 手写笔记；主题模型；topic model... || LDA; || 毕达几何...

Collaborative Denoising Auto-Encoders for Top-N Recommender Systems 2017-06-22 12:33:02

Most real-world recommender services measure their performance based on the top-N results shown to the end users. Thus, advances in top-N recommendation have far-ranging consequences in practical applications. In this paper, we present a novel method, called Collaborative Denoising Auto-Encoder (CDA... || Recommender Systems; Collaborative Filtering; Denoising Auto- Encoders; 有关于模型的分类总结; DAE; || Yao Wu Christopher DuBois Alice X. Zheng Martin Ester...

Convolutional Matrix Factorization for Document Context-Aware Recommendation 2017-06-21 17:09:00

Sparseness of user-to-item rating data is one of the major factors that deteriorate the quality of recommender system. To handle the sparsity problem, several recommendation techniques have been proposed that additionally consider auxiliary information to improve rating prediction accuracy. In parti... || Collaborative Filtering; Document Modeling; Contexual Information; Deep learning; CNN; || Donghyun Kim 1 , Chanyoung Park 1 , Jinoh Oh 1 , Sungyoung Lee 2 , Hwanjo Yu ∗1...

Probabilistic Matrix Factorization 2017-06-20 15:37:43

Many existing approaches to collaborative filtering can neither handle very large datasets nor easily deal with users who have very few ratings. In this paper we present the Probabilistic Matrix Factorization (PMF) model which scales linearly with the number of observations and, more importantly, pe... || PMF; probabilisitc graphical model; 矩阵系数问题; sparse; sparsity; 1659 citation; || Ruslan Salakhutdinov and Andriy Mnih...

A Hybrid Collaborative Filtering Model with Deep Structure for Recommender Systems 2017-06-19 20:57:28

Collaborative filtering(CF) is a widely used approach in recommender systems to solve many real-world problems. Traditional CF-based methods employ the user-item matrix which encodes the individual preferences of users for items for learning to make recommendation. In real applications, the rating m... || Deep learning ; DAE; AutoEncoder; MF: CF; || Xin Dong, Lei Yu, Zhonghuo Wu, Yuxia Sun, Lingfeng Yuan, Fangxi Zhang...

Restricted Boltzmann Machines for Collaborative Filtering 2017-06-17 21:47:56

Most of the existing approaches to collaborative filtering cannot handle very large data sets. In this paper we show how a class of two-layer undirected graphical mod- els, called Restricted Boltzmann Machines (RBM’s), can be used to model tabular data, such as user’s ratings of movies. We present e... ; || Ruslan Salakhutdinov, Andriy Mnih, Geoffrey Hinton...

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