Zobrazeno 1 - 10
of 203
pro vyhledávání: '"Wirjanto, Tony"'
Autor:
Chen, Jiazhen, Fu, Sichao, Zhang, Zhibin, Ma, Zheng, Feng, Mingbin, Wirjanto, Tony S., Peng, Qinmu
Few-shot graph anomaly detection (GAD) has recently garnered increasing attention, which aims to discern anomalous patterns among abundant unlabeled test nodes under the guidance of a limited number of labeled training nodes. Existing few-shot GAD ap
Externí odkaz:
http://arxiv.org/abs/2410.08629
This paper extends the application of ESG score assessment methodologies from large corporations to individual farmers' production, within the context of climate change. Our proposal involves the integration of crucial agricultural sustainability var
Externí odkaz:
http://arxiv.org/abs/2404.13818
Autor:
He, Shiyu, Bui, Trang, Huang, Yuying, Zhang, Wenling, Jian, Jie, Wong, Samuel W. K., Wirjanto, Tony S.
To assess the impact of climate change on the Canadian economy, we investigate and model the relationship between seasonal climate variables and economic growth across provinces and economic sectors. We further provide projections of climate change i
Externí odkaz:
http://arxiv.org/abs/2311.03497
The widespread confusion among investors regarding Environmental, Social, and Governance (ESG) rankings assigned by rating agencies has underscored a critical issue in sustainable investing. To address this uncertainty, our research has devised metho
Externí odkaz:
http://arxiv.org/abs/2310.02163
Detecting anomalies in temporal data is challenging due to anomalies being dependent on temporal dynamics. One-class classification methods are commonly used for anomaly detection tasks, but they have limitations when applied to temporal data. In par
Externí odkaz:
http://arxiv.org/abs/2304.07898
Anomalies in univariate time series often refer to abnormal values and deviations from the temporal patterns from majority of historical observations. In multivariate time series, anomalies also refer to abnormal changes in the inter-series relations
Externí odkaz:
http://arxiv.org/abs/2302.02051
Publikováno v:
In Energy Economics March 2024 131
Publikováno v:
In Journal of Commodity Markets December 2023 32
Numerical challenges inherent in algorithms for computing worst Value-at-Risk in homogeneous portfolios are identified and solutions as well as words of warning concerning their implementation are provided. Furthermore, both conceptual and computatio
Externí odkaz:
http://arxiv.org/abs/1505.02281
We study the problem of finding the worst-case joint distribution of a set of risk factors given prescribed multivariate marginals and a nonlinear loss function. We show that when the risk measure is CVaR, and the distributions are discretized, the p
Externí odkaz:
http://arxiv.org/abs/1505.02292