About the DMML group
The Data Mining and Machine Learning group of Geneva was established in 2011 by Prof. Alexandros Kalousis. It operates as a collaboration between the Department of Information Systems of the University of Applied Sciences, Western Switzerland, Geneva, and the VIPER group of the Computer Science Department of the University of Geneva. Many of the members currently follow a PhD under the joint supervision of Profs. Alexandros Kalousis and Stephane Marchand-Maillet.
We conduct research in various areas of data mining and machine learning, publishing at major international conferences (NeurIPS, ICML, etc.). In our latest work we focus on leveraging the power of modern deep learning architectures to address the problems of generative modeling, continual- and meta- learning, modelling of dynamical systems, and imitation and reinforcement learning. In these we also build on our experiences with metric and kernel learning, feature selection, structured regularization, and many other topics explored over the years by our members.
Many of our research directions have been defined on the basis of real world problems. We collaborate with multiple industrial and academic partners on joint projects providing the necessary machine learning expertise. The group receives funding from different sources, such as the Swiss National Science Foundation, SNSF, InnoSuisse (former CTI), the European Union, Horizon 2020, as well as directly from industrial partners.
Wednesday, January 22nd 2020, we have the pleasure to welcome Guillaume Obozinski, the Deputy Chief Data Scientist at the Swiss Data Science Center, to give us a talk on "Convex unmixing and learning the effect of latent variables in Gaussian Graphical models with unobserved variables". The talk will take place in the HEG building B ...Read more
As we are approaching the beginning of 2020, it is worth taking a minute to reflect over the year 2019. People first! We are thrilled to have welcomed two new PhD students in our group this year: Sooho Kim , who is a PhD candidate at the Seoul National University, has joined our team as a visiting ...Read more
We have several PhD openings in machine learning research for exploring methods to combine learning with process-driven modeling and simulations. The interaction and cooperation between a simulator and a machine learning model can be exploited in a number of areas where data are expensive or difficult to obtain, and/or where domain knowledge within the process-driven ...Read more