Faculty profile
Yafei Wang
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Latest papers
Intrinsic Benefits of Categorical Distributional Loss: Uncertainty-aware Regularized Exploration in Reinforcement Learning.
Advances in neural information processing systems · 2025
Sparse Multicategory Generalized Distance Weighted Discrimination in Ultra-High Dimensions.
Entropy (Basel, Switzerland) · 2020
Latest funding
- $26,000
Robust Statistical Modeling under Uncertainty
NSERC · 2024 · Principal investigator
- $12,500
Robust Statistical Modeling under Uncertainty
NSERC · 2024 · Principal investigator
2 publications.
Intrinsic Benefits of Categorical Distributional Loss: Uncertainty-aware Regularized Exploration in Reinforcement Learning.
Sun K, Zhao Y, Shi E, Wang Y, Yan X, Jiang B, Kong L
Sparse Multicategory Generalized Distance Weighted Discrimination in Ultra-High Dimensions.
Su T, Wang Y, Liu Y, Branton WG, Asahchop E, Power C, Jiang B, Kong L, Tang N
Robust Statistical Modeling under Uncertainty
Principal investigators: Wang, Yafei
Keywords: distributional roubst; conditional estimation; data-driven decision-making
Robust Statistical Modeling under Uncertainty
Principal investigators: Wang, Yafei
Keywords: distributional roubst; conditional estimation; data-driven decision-making
From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.
Frequent collaborators
- Linglong Kong and Bei Jiang: 12 shared papers
- Christopher Power and Linglong Kong: 4 shared papers
- Linglong Kong and Yafei Wang: 2 shared papers
- Bei Jiang and Yafei Wang: 2 shared papers
- Christopher Power and Bei Jiang: 1 shared paper
- Christopher Power and Yafei Wang: 1 shared paper
- Department of Mathematical and Statistical Sciences
- Mathematical and Statistical Sciences
- Medicine/Neurology
Co-authors at University of Alberta, colored by department. Thicker lines mean more shared papers; select anyone to open their profile and their own map.
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