基本信息
浏览量:176
职业迁徙
个人简介
I am a Lecturer in machine learning at the Electrical and Electronics Engineering Department at Imperial College. My research is at the boundary between theory and practice in machine learning, where the goal is to infer a functional relation between an "input" and "output" domain, given only a finite number of observations.
My main focus is to develop efficient algorithms for machine learning in contexts with "structured" data, ranging from multitask, learning-to-learn and structured prediction problems to name but a few. The underlying assumption guiding my research is that most real-world learning problems are often enriched by “structural information” (e.g. the similarity between separate learning problems, or the constraints imposed by a specific input-output domain). This structure can be leveraged to significantly reduce the complexity of the overall learning process leading to algorithms that learn faster and better than those that work in isolation.
My main focus is to develop efficient algorithms for machine learning in contexts with "structured" data, ranging from multitask, learning-to-learn and structured prediction problems to name but a few. The underlying assumption guiding my research is that most real-world learning problems are often enriched by “structural information” (e.g. the similarity between separate learning problems, or the constraints imposed by a specific input-output domain). This structure can be leveraged to significantly reduce the complexity of the overall learning process leading to algorithms that learn faster and better than those that work in isolation.
研究兴趣
论文共 64 篇作者统计合作学者相似作者
按年份排序按引用量排序主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
CoRR (2024)
引用0浏览0EI引用
0
0
IEEE transactions on pattern analysis and machine intelligenceno. 4 (2024): 1996-2010
IEEE International Conference on Robotics and Automationno. 1 (2022): 2459-2465
arXiv (Cornell University) (2022)
引用0浏览0引用
0
0
ICLR 2023 (2022)
引用0浏览0EI引用
0
0
加载更多
作者统计
合作学者
合作机构
D-Core
- 合作者
- 学生
- 导师
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn