Learning Machines Seminars

Weekly presentations on current topics in machine learning research. Meet people and listen to AI experts at RISE as well as invited speakers from academia and industry.

The seminar series is currently online only. Join our video presentations at Zoom, on Thursdays at 15.

Connect with Zoom at this link: https://rise.zoom.us/j/208117140

Upcoming seminars:

• 2022-01-27: Aleksis Pirinen, RISE. AI and Climate Change.
  Abstract: This talk is divided into two parts. In the first part I provide a brief overview of how artificial intelligence (AI) is being or can be used to mitigate and adapt to the effects of climate change. The content here will to some extent be based on the report "Tackling Climate Change with Machine Learning" by Rolnick et al. In the second part I outline some potential considerations and discussion topics regarding AI before and/or during a potential (climate change-induced) societal collapse, which hundreds of scholars now say we should discuss and prepare for (see e.g. https://www.theguardian.com/environment/2020/dec/06/a-warning-on-climate-and-the-risk-of-societal-collapse). The purpose of this second part is to initiate dialogue on how AI may be used to mitigate and adapt to (parts of) collapse, as well as to highlight risks with and limits of AI in this context.
• 2022-02-03: Josephine Sullivan, KTH. Title TBA.
• 2022-02-10: Jerk Rönnols, RISE. Title TBA.
• 2022-02-24: Dan Stowell, Tilburg University. Deep models of animal listening perceptual tasks
• 2022-03-10: Megan Stanley, Microsoft Research Cambridge. Title TBA.

Previous seminars:

All recorded seminars have also been put into a YouTube playlist

• 2022-01-20: Jon Nordby, Soundsensing. Monitoring noise, machinery and processes using Machine Learning.
  2022-01-13: Andrew Jesson, Oxford Applied and Theoretical Machine Learning Group OATML. Head in the clouds? Why decision making is hard.(YouTube)
• 2021-12-16: Stéphane d'Ascoli, FAIR Paris and ENS Paris. Double descent: insights from the random feature model.

2021 Seminars

• 2021-12-09: Arman Rahbar, Chalmers University of Technology. Online Learning of Decision Trees.
• 2021-12-02: Ebba Ekblom, RISE. Federated learning with generative adversarial networks (YouTube).
• 2021-11-25: Maria Priisalu, Lund University. Semantically Reasoning Pedestrian Models in Generative Autonomous Vehicle Testing. (YouTube)
• 2021-11-18: Martin Willbo, RISE. Few-shot learning for sound event detection.
• 2021-11-11: Diarmuid Corcoran, Ericsson and KTH. Reinforcement Learning for Automated Energy Efficient Mobile Network Performance Tuning (YouTube)
• 2021-11-04: Tuomas Virtanen, Tampere University. Machine learning for acoustic scene analysis (YouTube).
• 2021-10-28: Maria Bånkestad, RISE & Uppsala University. Variational inference overview (YouTube)
• 2021-10-21: Nikunj Saunshi, Princeton University. Theory for self-supervised learning (YouTube)
• 2021-10-14: Alan Said, University of Gothenburg. What we talk about when we talk about recommender systems. A brief and biased overview (YouTube).
• 2021-10-07: Arash Vahidi, RISE. Security for Machine Learning for Security.
• 2021-09-30: Anders Holst, RISE & KTH.
• 2021-09-23: Nishat Mowla, RISE. The role of AI/ML for the cybersecurity evolution: A brief review and challenges ahead.
• 2021-09-16: Learning Machines Flash Talks: 5 ML papers by 5 speakers in 5² minutes (YouTube).
• 2021-09-09: Björn Gambäck, RISE&NTNU. Hate speech in social media. (YouTube)
• 2021-06-10: Debabrota Basu, Inria. SENTINEL: Quantifying Composite Uncertainty and Its Application in Risk-sensitive Reinforcement Learning (YouTube)
• 2021-05-27: Alireza Salehi, RISE. Biochemical Analysis and Metabolomics study of Biofluids: Combination of Omics data and Patients information
• 2021-05-20: Divya Grover, Chalmers University of Technology. Sample Efficient Bayesian Reinforcement Learning (YouTube)
• 2021-05-06: Rajkumar Saini, Luleå University of Technology. Electroencephalography (EEG) in various applications
• 2021-04-22: Aleksis Pirinen, Lund University. Intro to Policy-Based RL and Applications in Computer Vision (YouTube)
• 2021-04-29: Ariel Ekgren, RISE. (Art from the weights), CLIP: Connecting text and images (YouTube)
• 2021-04-15: Rami Mochaourab, RISE. Robust explanations for private support vector machines (YouTube)
• 2021-04-08: Easter break: No seminar this week
• 2021-04-01: Han Wang, RISE. Federated Learning for IoT Security (slides)
• 2021-03-25: Learning Machines Flash Talks
• 2021-03-18: Daniel F. Perez-Ramirez, RISE. Introduction and recent advances on graph representation learning (YouTube)
• 2021-03-11: Maria Bånkestad, RISE/Uppsala University. Geometric deep learning with graph neural networks (YouTube) (slides)
• 2021-02-25: Sepideh Pashami, RISE/Halmstad University. Causal-Aware Machine Learning (YouTube)
• 2021-02-11: Jesper Derehag, Ericsson. Machine learning in practice – the engineering perspective (YouTube)
• 2021-02-04: Olof Görnerup, RISE. Evolution in natural and artificial systems
• 2021-01-28: Marinos Koutsomichalis, Technological University of Cyprus: Non-solutionist and Post-optimal approaches to AI Research
• 2021-01-21: Learning Machines Flash Talks

2020 seminars:

• 2020-12-10: Zekarias Tilahun, KTH. Dynamic Embeddings for Interaction Prediction (YouTube)
• 2020-12-03: Learning Machines Flash Talks
• 2020-11-26: Rickard Brännvall, RISE: Machine learning with homomorphic encryption
• 2020-11-19: Edvin Listo Zec, RISE. Promises and challenges of federated learning (YouTube) (slides)
• 2020-11-12: Erik Ylipää, RISE. Unsquared Transformers (YouTube)
• 2020-11-05: Olof Mogren, RISE. Uncertainty in deep learning (YouTube) + (Slides)  
• 2020-10-22: Fredrik Carlsson, RISE. State of the art Sentence Embeddings with Contrastive Tension (YouTube)
• 2020-10-15: Leon René Sütfeld, RISE. Deep Reinforcement Learning: Applications in Traffic Light Control