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IDA Machine Learning Seminars - Spring 2019




Wednesday, February 27, 3.15 pm, 2019

Reliable Semi-Supervised Learning when Labels are Missing at Random
Dave Zachariah
, Department of Information Technology, Division of Systems and Control, Uppsala University
Abstract: Semi-supervised learning methods are motivated by the availability of large datasets with unlabeled features in addition to labeled data. Unlabeled data is, however, not guaranteed to improve classification performance and has in fact been reported to impair the performance in certain cases. In this talk we discuss some fundamental limitations to semi-supervised learning and restrictive assumptions which result in unreliable classifiers. We also propose a learning approach that relaxes such assumptions and is capable of providing classifiers that reliably quantify the label uncertainty.
Location: Ada Lovelace (Visionen)
Organizer: Fredrik Lindsten


Wednesday, March 27, 3.15 pm, 2019

Conformal prediction
Henrik Boström
, Department of Software and Computer Systems, KTH Royal Institute of Technology
Abstract: Conformal prediction is a framework for quantifying the uncertainty of predictions provided by standard machine learning algorithms. When employing the framework, the probability of making incorrect predictions is bounded by a user-provided confidence threshold. In this talk, we will briefly introduce the framework and illustrate its use in conjunction with both interpretable models, such as decision trees, and highly predictive models, such as random forests.
Location: Ada Lovelace (Visionen)
Organizer: Oleg Sysoev


Wednesday, April 24, 3.15 pm, 2019

Evaluating the Performance of Soccer Players
Jesse Davis
, Department of Computer Science, KU Leuven
Abstract: Over the last 25 years, there has been tremendous interest in applying computational techniques to analyze sports. This area has exploded in the past decade as modern data collection techniques have enabled collecting large of amounts of data about games and athletes. From a computer science perspective, sports data are very rich and complicated, which poses a number of interesting analysis challenges such as the lack of ground truth labels, the need to construct relevant features, and changing contexts. I will begin the talk by highlighting some of the most important general challenges. Then I will focus on our efforts to assess the performance of soccer players during a match. First, I will describe our approach for assigning values to all on-ball actions during a match. This goes beyond standard approaches such as expected goals and assists that only value on a small subset of actions. Second, I will describe our recent research on trying to understand how mental pressure affects performance. I will explain our mental pressure model, which assigns a pressure level to each minute of match by considering both the match context as well as the current game state. This enables comparing soccer players' performances across different levels of mental pressure. Finally, I will show our approach’s ability to provide actionable insights for soccer clubs in four relevant use cases: player acquisition, training, tactical decisions, and lineups and substitutions.
Location: Ada Lovelace (Visionen)
Organizer: Patrick Lambrix


Wednesday, May 8, 3.15 pm, 2019 (Extra seminar)

TBA
Francisco Ruiz
, Department of Computer Science, Columbia University and Dept of Engineering, University of Cambridge.
Abstract: TBA
Location: Ada Lovelace (Visionen)
Organizer: Fredrik Lindsten


Wednesday, May 15, 3.15 pm, 2019 (Note the date)

TBA
Florian T. Pokorny
, Robotics, Perception and Learning Lab, KTH Royal Institute of Technology.
Abstract: TBA
Location: Ada Lovelace (Visionen)
Organizer: Mattias Villani



Future Seminars

Fall 2019   |   Spring 2020


Past Seminars

Fall 2018   |   Spring 2018   |   Fall 2017   |   Spring 2017   |   Fall 2016   |   Spring 2016  |   Fall 2015  
Spring 2015   |   Fall 2014



The seminars are typically held every fourth Wednesday at 15.15-16.15 in Ada Lovelace (Visionen).
For further information, or if you want to be notified about the seminars by e-mail, please contact Mattias Villani.


Page responsible: Mattias Villani
Last updated: 2019-03-25