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Motif Enhanced Recommendation over Heterogeneous Information Network
Huan Zhao, Yingqi Zhou, Yangqiu Song, Dik Lun Lee
Machine Learning, Recommendation
diversity, heterogeneous information networks
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Diversity in recommender systems – A survey
Matevz Kunaver, Tomaz Pozrl
Machine Learning, Recommendation
diversity
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Semantic Path based Personalized Recommendation on Weighted Heterogeneous Information Networks
Chuan Shi, Zhiqiang Zhang, Ping Luo, Philip S. Yu, Yading Yue, Bin Wu
Machine Learning, Recommendation
heterogeneous information networks
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Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics
Mark Weber, Giacomo Domeniconi, Jie Chen, Daniel Karl I. Weidele, Claudio Bellei, Tom Robinson, Charles E. Leiserson
Graph mining, Cyber security, Machine Learning, Data Analysis
bitcoins, learning, detection, aml, KDD2019
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Fusing Diversity in Recommendations in Heterogeneous Information Networks
Sharad Nandanwar, Aayush Moroney, M. N. Murty
Machine Learning, Recommendation
diversity, recommendation system, heterogeneous information networks
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Fine-grained Search Space Classification for Hard Enumeration Variants of Subset Problems
Juho Lauri, Sourav Dutta
Machine Learning, algorithmics
AAAI2019
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Deep Neural Networks for YouTube Recommendations
Paul Covington, Jay Adams, Emre Sargin
Machine Learning, Recommendation
deep learning, recommendation system
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Noise as a Resource for Computation and Learning in Networks of Spiking Neurons
Wolfgang Maas
Machine Learning
NP-hard, Graphs, IA, CSP, Statistics, Computer Vision, Brain, Computational Model
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Adding One Neuron Can Eliminate All Bad Local Minima
Shiyu Liang
Machine Learning, deep learning
Neural network
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Cauchy Graph Embedding
Dijun Luo, Chris Ding, Feiping Nie, Heng Huang
Machine Learning
embedding
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Why does deep and cheap learning work so well?
Henry W. Lin, Max Tegmark, David Rolnick
Machine Learning
Disordered Systems and Neural Networks, Learning, Neural and Evolutionary Computing, Machine Learning
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Diversity is All You Need: Learning Skills without a Reward Function
Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, Sergey Levine
Machine Learning
AI, machine learning, diversity