诺库维普

The Most Common Habits from more than 200 English Papers written by Graduate Chinese Engineering Students 2018-07-14 14:41:11

This paper presents some of the most common Chinese-English habits observed from over two hundred English technical papers by Chinese writers. The habits are explained and in most cases, example text from an actual paper is given along with preferred text. An attempt is made to explain how to correc... || 写作指导；老外总结的中国人写英语文章最常犯的错误总结; || Felicia Brittman...

理解矩阵分解几个不同角度 2018-07-13 11:14:44

矩阵分解，MF；NMF；【小结】; || Betageek...

Transfer Learning in Collaborative Filtering for Sparsity Reduction 2018-07-12 20:19:11

Data sparsity is a major problem for collaborative filtering (CF) techniques in recommender systems, especially for new users and items. We observe that, while our target data are sparse for CF systems, related and relatively dense auxiliary data may already exist in some other more mature applicati... || cross domain; learn and transfer the latent vectors; principled matrix; heterogeneous； intrinsic preference structure; Y_{u:}行,Y_{:i}列，y_{ui}实体; 将ratings 处理成implicit feedback； coordinate systems; || Weike Pan, Evan W. Xiang, Nathan N. Liu and Qiang Yang...

Semi-Supervised Nonnegative Matrix Factorization 2018-07-11 16:30:17

Nonnegative matrix factorization (NMF) is a popular method for low-rank approximation of nonnegative matrix, pro- viding a useful tool for representation learning that is valuable for clustering and classification. When a portion of data are la- beled, the performance of clustering or classification... || semi-supervised NMF；分解方法求解NMF; || Hyekyoung Lee, Jiho Yoo, and Seungjin Choi...

Matching Users and Items Across Domains to Improve the Recommendation Quality 2018-07-11 14:53:18

Given two homogeneous rating matrices with some overlapped users/items whose mappings are unknown, this paper aims at an- swering two questions. First, can we identify the unknown map- ping between the users and/or items? Second, can we further utilize the identified mappings to improve the quality ... || Collaborative Filtering; Transfer Learning; Matrix Factorization; cross domain； constraint;奇异值分解；CBT；RMGM; || Chung-Yi Li...

Can Movies and Books Collaborate? Cross-Domain Collaborative Filtering for Sparsity Reduction 2018-07-11 14:50:08

The sparsity problem in collaborative filtering (CF) is a major bottleneck for most CF methods. In this paper, we consider a novel approach for alleviat- ing the sparsity problem in CF by transferring user- item rating patterns from a dense auxiliary rating matrix in other domains (e.g., a popular m... || cross-domain; transfer；codebook；CBT; || Bin Li；Qiang Yang; Xiangyang Xue...

Little Is Much: Bridging Cross-Platform Behaviors through Overlapped Crowds 2018-07-11 14:44:39

People often use multiple platforms to fulfill their different information needs. With the ultimate goal of serving people intelligently, a fundamental way is to get comprehensive understanding about user needs. How to organically integrate and bridge cross-platform information in a human-centric wa... || cross-domain; overlapped; transfer；semi- supervised NMF; || Meng Jiang, Peng Cui...

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