Development of Fast and Highly Effective Feature Subset Selection Algorithms based on Novel Integration of Quantum Computing and Machine Learning

今年我们总结了到目前为止取得的研究成果。我们严格地检查了我们的研究方法和我们开发的算法，这些算法使用更大的数据集进行评估。我们总结了到目前为止研究成果的优缺点和成功与失败，并撰写了一篇综述论文。我们现在正在修改草案，以使最终版本作为期刊论文提交。我们意识到，我们需要在量子计算机平台上扩展更多的模拟实验来验证我们的结果。我们将项目延长了一年，今年我们计划与外国大学合作，利用他们的资源进行模拟实验。我还在几次会议上发表了主题演讲，并将我们的研究成果传达给了更多的受众。

This year we have summarized our research results we have acheived so far. We critically examined our research methodology and the algorithms we developed with larger data sets for evaluation of the algorithms. We summarized the merits and demerits, success and failure of our research outcome so far and wrote a review paper. We are now revising the draft to make the final version to submit as a journal paper. We realized that we need to extend some more simulation experiments in quantum computer platform to validate our results. We extended the projects fore one more year and this year we are planning to collaborate with foreign universities to use their resources to conduct simulation experiments. I also gave keynote lectures in several conferences and conveyed our research outcomes to wider audience.