Recommender system, Machine learning, Artificial intelligence, World Wide Web and Social network are his primary areas of study. His Recommender system study integrates concerns from other disciplines, such as Knowledge base, Vertical search, Search engine and Dialog box. His work focuses on many connections between Machine learning and other disciplines, such as Information retrieval, that overlap with his field of interest in Probabilistic logic.
His work in Social network tackles topics such as Web application which are related to areas like Social network analysis and Probabilistic matrix factorization. His Collaborative filtering research integrates issues from Matrix decomposition and Data mining. Hao Ma has researched Matrix decomposition in several fields, including Theoretical computer science and Approximation algorithm.
His primary areas of study are Information retrieval, Recommender system, Artificial intelligence, World Wide Web and Machine learning. Hao Ma has included themes like Ranking, Web page, The Internet and Range in his Information retrieval study. His study in Recommender system is interdisciplinary in nature, drawing from both Matrix decomposition, Web application, Probabilistic logic and Social network.
His research in the fields of Web modeling, Data Web and Knowledge base overlaps with other disciplines such as Heuristics. As a part of the same scientific study, Hao Ma usually deals with the Web modeling, concentrating on Web standards and frequently concerns with Web navigation. His work on Regularization as part of his general Machine learning study is frequently connected to Downstream and Empirical research, thereby bridging the divide between different branches of science.
Hao Ma spends much of his time researching Artificial intelligence, Language model, Machine learning, Question answering and Self attention. His research in Artificial intelligence is mostly concerned with Representation. To a larger extent, Hao Ma studies Natural language processing with the aim of understanding Language model.
His Natural language processing study integrates concerns from other disciplines, such as Word, Leverage and Explicit knowledge. His research in Machine learning intersects with topics in Text corpus and Automatic summarization. Hao Ma has researched Self attention in several fields, including Paragraph, Inference, Algorithm and Benchmark.
The scientist’s investigation covers issues in Self attention, Algorithm, Linear complexity, Transformer and Theoretical computer science. His Self attention research is multidisciplinary, relying on both Question answering, Paragraph, Machine learning and Inference. The Theoretical computer science study combines topics in areas such as Embedding, Sparse matrix, Representation and Bounded function.
In his works, Hao Ma undertakes multidisciplinary study on Factorization and Approximation error.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Recommender systems with social regularization
Hao Ma;Dengyong Zhou;Chao Liu;Michael R. Lyu.
web search and data mining (2011)
SoRec: social recommendation using probabilistic matrix factorization
Hao Ma;Haixuan Yang;Michael R. Lyu;Irwin King.
conference on information and knowledge management (2008)
Learning to recommend with social trust ensemble
Hao Ma;Irwin King;Michael R. Lyu.
international acm sigir conference on research and development in information retrieval (2009)
QoS-Aware Web Service Recommendation by Collaborative Filtering
Zibin Zheng;Hao Ma;M R Lyu;I King.
IEEE Transactions on Services Computing (2011)
An Overview of Microsoft Academic Service (MAS) and Applications
Arnab Sinha;Zhihong Shen;Yang Song;Hao Ma.
the web conference (2015)
Effective missing data prediction for collaborative filtering
Hao Ma;Irwin King;Michael R. Lyu.
international acm sigir conference on research and development in information retrieval (2007)
WSRec: A Collaborative Filtering Based Web Service Recommender System
Zibin Zheng;Hao Ma;Michael R. Lyu;Irwin King.
international conference on web services (2009)
Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec
Jiezhong Qiu;Yuxiao Dong;Hao Ma;Jian Li.
web search and data mining (2018)
Collaborative Web Service QoS Prediction via Neighborhood Integrated Matrix Factorization
Zibin Zheng;Hao Ma;M. R. Lyu;Irwin King.
IEEE Transactions on Services Computing (2013)
Linformer: Self-Attention with Linear Complexity
Sinong Wang;Belinda Z. Li;Madian Khabsa;Han Fang.
arXiv: Learning (2020)
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