Talk by prof. Byeng Dong YOUN
1.11.2019In developing our collaborations with experts and scholars around the globe, we were happy to welcome Dr. Byeng Dong YOUN, Professor of Mechanical and Aerospace Engineering at Seoul National University (SNU), the founder and CEO of OnePredict Inc. (onepredict.com), and the President of the Korean Society of Prognostics and Health Management (PHM). Prof. Youn presented ...
Read moreVariational saccading
20.12.2019Ever tried to train a deep neural network over high resolution images taken by modern smartphone cameras or smart devices? The memory and inferential costs when working with inputs of such large dimensions (e.g. 4000x3000) increase rapidly and often prohibitively. Jason Ramapuram proposes a solution in his new paper "Variational Saccading: Efficient Inference for Large ...
Read moreML research on the move
20.12.2019Though ML labs may seem to outsiders as rather nerdy isolated groups, it is not our case! We are on the move, visiting and welcoming ML researchers, sometimes near and sometimes further away. Discussing, collaborating, making friends, having fun!
Read moreLionel Blonde in AISTATS
20.12.2019AISTATS 2019 is well under way and Lionel Blonde is there to present his work on Sample-Efficient Imitation Learning via Generative Adversarial Nets. You can check his poster Th79 at the poster session tomorrow (Thursday, April 18, 13h30-16h30). He will be happy to explain how he improves upon GAIL by reducing the sample complexity by ...
Read moreNew machine learning courses
7.4.2019The HEG (HES-SO Geneva) opened a new Data Science branch in its Master's programe in Information Studies. Our group is responsible for the two major modules on machine learning spanning over two semesters (16 credits in total). Building a new machine learning course is a challenge we are happy to embrace.
Read moreNIPS 2018
20.12.2019Meet us at the NIPS workshops were we will be presenting the following works: Sample-Efficient Imitation Learning via Generative Adversarial Nets (Lionel Blondé, Alexandros Kalousis), in the Deep RL and in the Imitation Learning and its Challenges in Robotics workshops. Continual Classification Learning Using Generative Models (Frantzeska Lavda, Jason Ramapuram, Magda Gregorova, Alexandros Kalousis), in the Continual Learning workshop. Variational Saccading: Efficient ...
Read moreThe blog is live!
27.11.2018Read the blog to know about the latest endeavours of the DMML group!
Read moreWelcome to Ye!
13.11.2018Warm welcomes to our new colleague, Ye Yuan, who started his PhD with us in September 2018 to work on our gait project. Ye has got a master's degree in Computer Science from the Institute of Computing Technology of the University of Chinese Academy of Science and has got some experience with NLP and stock ...
Read moreBusy Monday, 12 November 2018
29.10.2018On Monday 12/November we will host a talk of Dr. Julien Mairal, Inria, Grenoble on: "Invariance and Stability to Deformations of Deep Convolutional Representations". Later the same day, Magda will defend her thesis on "Sparse Learning for variable selection with structures and nonlinearities".
Read moreLionel to speak at SMLD2018
15.11.2018Lionel Blondé will present his work on "Sample-Efficient Imitation Learning via Generative Adversarial Nets" at the 2018 edition of the Swiss Machine Learning Day.
Read more