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ICML
2009
IEEE
15 years 4 months ago
Supervised learning from multiple experts: whom to trust when everyone lies a bit
We describe a probabilistic approach for supervised learning when we have multiple experts/annotators providing (possibly noisy) labels but no absolute gold standard. The proposed...
Vikas C. Raykar, Shipeng Yu, Linda H. Zhao, Anna K...
91
Voted
RECSYS
2009
ACM
15 years 3 months ago
Learning to recommend with trust and distrust relationships
With the exponential growth of Web contents, Recommender System has become indispensable for discovering new information that might interest Web users. Despite their success in th...
Hao Ma, Michael R. Lyu, Irwin King
WEBI
2009
Springer
15 years 4 months ago
Adapting Reinforcement Learning for Trust: Effective Modeling in Dynamic Environments
—In open multiagent systems, agents need to model their environments in order to identify trustworthy agents. Models of the environment should be accurate so that decisions about...
Özgür Kafali, Pinar Yolum
SIGIR
2009
ACM
15 years 3 months ago
Learning to recommend with social trust ensemble
As an indispensable technique in the field of Information Filtering, Recommender System has been well studied and developed both in academia and in industry recently. However, mo...
Hao Ma, Irwin King, Michael R. Lyu
81
Voted
CCS
2004
ACM
15 years 2 months ago
Lessons learned using alloy to formally specify MLS-PCA trusted security architecture
In order to solve future Multi Level Security (MLS) problems, we have developed a solution based on the DARPA Polymorphous Computing Architecture (PCA). MLS-PCA uses a novel distr...
Brant Hashii