Integrating Reasoning on Combinatorial Optimisation Problems into Machine Learning
|Title:||Integrating Reasoning on Combinatorial Optimisation Problems into Machine Learning|
|Date:||August 19, 2019 (Monday)|
|Time:||11:00 am - 12:00 pm|
|Venue:||Room 121, 1/F, Ho Sin-Hang Engineering Building, The Chinese University of Hong Kong, Shatin, N.T.|
|Speaker:|| Dr. Emir Demirovic
School of Computing and Information Systems University of Melbourne
We study the predict+optimise problem, where machine learning and combinatorial optimisation must interact to achieve a common goal. These problems are important when optimisation needs to be performed on input parameters that are not fully observed but must instead be estimated using machine learning. Our aim is to develop machine learning algorithms that take into account the underlying combinatorial optimisation problem. While a plethora of sophisticated algorithms and approaches are available in machine learning and optimisation respectively, an established methodology for solving problems which require both machine learning and combinatorial optimisation remains an open question. In this talk, we introduce the problem, discuss its difficulties, and present our progress based on our papers from CPAIOR'19 and IJCAI'19.
Dr. Emir Demirovic is an associate lecturer and postdoctoral researcher (research fellow) at the University of Melbourne in Australia. He received his PhD from the Vienna University of Technology (TU Wien) and worked at a production planning and scheduling company MCP for seven months. Dr. Demirovic's primary research interest lies in solving complex real-world problems through combinatorial optimisation and combinatorial machine learning, which combines optimisation and machine learning. His work includes both developing general-purpose algorithms and applications. An example of such a problem is to design algorithms to generate high-quality timetables for high schools based on the curriculum, teacher availability, and pedagogical requirements. Another example is to optimise a production plan while only having an estimate of costs rather than precise numbers.
Enquiries: Ms. Shirley Lau at tel. 3943 8439
For more information, please refer to http://www.cse.cuhk.edu.hk/en/events