37 citations
- Princeton UniversityUS9 papers
- Fudan UniversityCN2 papers
- Tsinghua UniversityCN2 papers
- Academy of Mathematics and Systems ScienceCN1 paper
- Capital Group (United States)US1 paper
- Changwon National UniversityKR1 paper
- Chinese Academy of SciencesCN1 paper
- City University of Hong KongHK1 paper
- Decision Sciences (United States)US1 paper
- Délégation Paris 7FR1 paper
- Discover Financial Services (United States)1 paper
- École Normale SupérieureBI1 paper
19 papers
Safe and Policy-Compliant Multi-Agent Orchestration for Enterprise AI
Vinil Pasupuleti, Shyalendar Reddy Allala, Siva Rama Krishna Varma Bayyavarapu +1
Enterprise AI systems increasingly deploy multiple intelligent agents across mission-critical workflows that must satisfy hard policy constraints, bounded risk exposure, and compre…
Conditional Generative Modeling for Enhanced Credit Risk Management in Supply Chain Finance
Qingkai Zhang, L. Jeff Hong, Houmin Yan
The rapid expansion of cross-border e-commerce (CBEC) has created significant opportunities for small- and medium-sized sellers, yet financing remains a critical challenge due to t…
RSEA-MVGNN: Multi-View Graph Neural Network with Reliable Structural Enhancement and Aggregation
Junyu Chen, Long Shi, Badong Chen
Graph Neural Networks (GNNs) have exhibited remarkable efficacy in learning from multi-view graph data. In the framework of multi-view graph neural networks, a critical challenge l…
Unicorn: U-Net for Sea Ice Forecasting with Convolutional Neural Ordinary Differential Equations
Jaesung Park, Sungchul Hong, Yoonseo Cho +1
Sea ice at the North Pole is vital to global climate dynamics. However, accurately forecasting sea ice poses a significant challenge due to the intricate interaction among multiple…
On marginal feature attributions of tree-based models
Khashayar Filom, Alexey Miroshnikov, Konstandinos Kotsiopoulos +1
Due to their power and ease of use, tree-based machine learning models, such as random forests and gradient-boosted tree ensembles, have become very popular. To interpret them, loc…
Adaptive Low-Nonnegative-Rank Approximation for State Aggregation of Markov Chains
Yaqi Duan, Mengdi Wang, Zaiwen Wen +1
This paper develops a low-nonnegative-rank approximation method to identify the state aggregation structure of a finite-state Markov chain under an assumption that the state space…