Search Results for author:
Found 7 papers, 3 papers with code
Stackelberg reinsurance and premium decisions with MV criterion and irreversibility
We study a reinsurance Stackelberg game in which both the insurer and the reinsurer adopt the mean-variance (abbr.
Consumption-investment decisions with endogenous reference point and drawdown constraint
We propose a consumption-investment decision model where past consumption peak $h$ plays a crucial role.
The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights
Combinatorial optimization is a well-established area in operations research and computer science.
Bayesian Methods for the Analysis of Early-Phase Oncology Basket Trials with Information Borrowing across Cancer Types
We did simulation studies to compare CBHM with independent analysis and three information borrowing approaches: the conventional Bayesian hierarchical model, the EXNEX approach and Liu's two-stage approach.
Applications
A Simulation-free Group Sequential Design with Max-combo Tests in the Presence of Non-proportional Hazards
The integration and application of maxcombo tests in interim analyses often require extensive simulation studies.
Methodology
FTGAN: A Fully-trained Generative Adversarial Networks for Text to Face Generation
With a novel fully-trained generative network, FTGAN can synthesize higher-quality images and urge the outputs of the FTGAN are more relevant to the input sentences.
Ensemble-based kernel learning for a class of data assimilation problems with imperfect forward simulators
For demonstration, we apply the ensemble-based learning framework and the integrated, ensemble-based data assimilation framework to a supervised learning problem and a data assimilation problem with an imperfect forward simulator, respectively.
