Oct
23
12:00 PM12:00

WEDNESDAY lunch: Mette Langaas

The lunch starts at 12:00, and the talk will start around 12:20.

NB: Wednesday BigInsight Lunches are open to staff and students from any of the BigInsight partners, including UiO, but not to others.

Speaker: Mette Langaas, Norwegian University of Science and Technology and Norwegian Computing Centre Big Insights SFI

Location: Spiseriet at Norsk Regnesentral.

Title: The future of teaching statistics

Abstract: Today, statistics is everywhere in society. It appears in our media, in jobs, and in advertising. Especially, it affects statisticians and non-statisticians alike. At university, we have the same story. Students in a variety of different fields are required to take statistics. Some of these students may go on to become statisticians, while others will only meet statistics in the news or at work.

Common jobs are also being “statistically charged”. More than ever, skills in scientific computation and data analysis are highly sought after. Within these jobs, statisticians and the like are required to “think on their feet, solve problems and analyze data” often with state-of-the-art statistical methods.  The requirement of being “lifelong learners” is increasing.

But educating and learning is also changing. For example, “the death of the lecture” has been proclaimed for many years now. This has resulted in campuses and lecture halls changing to “active learning areas”. At the same time, top ranked universities abroad advertise massive online open (and paid for) courses available to “everyone”.

Due to the digitalization of society, need for continued education, and diverse student population, (statistics) teaching at the university level is facing new challenges. In this presentation I will elaborate on some of these challenges and talk about my experience with developing (open) learning materials and implementing and running active learning sessions at the Norwegian University of Science and Technology.

Hopefully, the talk will inspire active discussions in the audience. Participation and feedback from (lifelong learners) outside the university is highly welcome! 

Before you come to the talk: please spend a few minutes (5-10) to fill in this questionnaire  (44 a/b-questions) - and take a screen shot of your scores (the four scores will only be shown to you on your screen), this will (hopefully) give you some insight into your own learning style and make observations in my presentation more easy to relate  to. https://www.webtools.ncsu.edu/learningstyles/

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Nov
14
8:30 AM08:30

Big Insight Day 2019

The yearly 2019 meeting of all researchers and partners of BigInsight will be on Thursday 14th November. Registration and breakfast will be from 08:30. Lunch will be served.

While we announce our yearly workshop openly, participation is restricted only to all staff from all the BigInsight partners including UiO.

Registration is free but obligatory and required by Friday 1st November.

Place: Norwegian Institute of Public Health (Folkehelsa)
Address: Lovisenberggata 8, 0456 Oslo

Programme with registration can be found here.

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Oct
9
12:00 PM12:00

WEDNESDAY lunch: Berent Lunde

The lunch starts at 12:00, and the talk will start around 12:20.

NB: Wednesday BigInsight Lunches are open to staff and students from any of the BigInsight partners, including UiO, but not to others.

Speaker: Berent Lunde, PhD, Universitet i Stavanger

Location: 8. floor Niels Henrik Abel’s building.

Title: An information criterion for gradient boosted trees

Abstract: Gradient boosting has been highly successful in machine-learning competitions for structured/tabular data since the introduction of XGBoost in 2014. Gradient boosting may be seen as a way of doing functional gradient descent to the supervised learning problem. As a consequence, in gradient tree boosting, the functional form of the model-ensemble constantly changes during training. To be able to choose the optimal functional complexity, the leading implementations offer a high number of regularization hyperparameters, available for manual tuning. This tuning typically require a combination of computationally costly cross validation on a grid of hyperparameters, coupled with some expert knowledge. To combat this, we propose an information criterion for gradient boosted trees, applicable to both the learning of the topology of trees, and as a stopping criterion for the boosting algorithm. This makes the algorithm adaptive to the dataset at hand; it is completely automatic and with minimal worries of overfitting. Moreover, as the algorithm only has to run once, the computational cost is drastically reduced.

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Sep
25
12:00 PM12:00

WEDNESDAY lunch: Andreas Buschermöhle

The lunch starts at 12:00, and the talk will start around 12:20.

NB: Wednesday BigInsight Lunches are open to staff and students from any of the BigInsight partners, including UiO, but not to others.

Speaker: Andreas Buschermöhle, Head of Data Science, Lyric

Location: Spiseriet at Norsk Regnesentral.

Title: Price recommendations for the vacation rental market

Abstract: At Lyric, we design and operate accommodations for the modern business traveler. The data science team supports these efforts by enabling strong economics as well as inventory scale via data and automation. We analyze a vast amount of data we gather from different vacation rental platforms to understand the booking process, guest price sensitivity, and the impact of changing demand. This enables us to automatically generate price recommendations for our units and a growing customer base on our pricing service Wheelhouse. Backed by our own inventory - currently in 12 US markets - we also have the ability to test different strategies and learn to improve our recommendation engine over time.

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Sep
11
12:00 PM12:00

WEDNESDAY lunch: Rebecca Wiborg Seyfarth

The lunch starts at 12:00, and the talk will start around 12:20.

NB: Wednesday BigInsight Lunches are open to staff and students from any of the BigInsight partners, including UiO, but not to others.

Speaker: Rebecca Wiborg Seyfarth, Data Scientist at Cognite AS

Location: 8. floor Niels Henrik Abel’s building.

Title: Open set classification

Abstract:

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Aug
28
12:00 PM12:00

WEDNESDAY lunch: Azzeddine Bakdi

The lunch starts at 12:00, and the talk will start around 12:20.

NB: Wednesday BigInsight Lunches are open to staff and students from any of the BigInsight partners, including UiO, but not to others.

Speaker: Azzeddine Bakdi, Postdoc, Statistics and Data Science, UiO

Location: Spiseriet at Norsk Regnesentral.

Title: Multiple vessel collision and grounding risk identification through historical AIS data and adaptive safety domains.

Abstract: The growth in maritime traffic and recent technological development of autonomous navigation systems have induced an increasing attention to navigational safety in which new tools are required to automatically identify risky and complex navigation situations to avoid disastrous consequences and promote safety. Smart technology for autonomous navigation however needs to be evaluated and very extensively tested against realistic situations before autonomous vessels might be certified for sailing. In this work, real historical big maritime data sources (AIS, vessel registry, weather, maps, sea levels/ states, etc.) are investigated to identify likely situations of high risk and complexity to design a complete set of test bed scenarios for autonomous vessel evaluation. Collision, grounding, and combined risks are automatically identified from data through the design of maneuverability-dependent adaptive ship-safety-domains with spatial risk functions. The high efficiency ensures real implementation for multiple vessel risk identification over a large scale in space and time, with a promising performance that allows for risk prediction and complexity analysis against multi-criteria conflicting and uncertain navigation rules.

 

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Jun
5
12:00 PM12:00

WEDNESDAY lunch: Michael Kampffmeyer

The lunch starts at 12:00, and the talk will start around 12:20.

NB: Wednesday BigInsight Lunches are open to staff and students from any of the BigInsight partners, including UiO, but not to others.

Speaker: Michael Kampffmeyer, Postdoc, Machine learning group, University of Tromsø

Location: Spiseriet at Norsk Regnesentral.

Title: Rethinking Knowledge Graph Propagation for Zero-Shot Learning

Abstract: Graph convolutional neural networks have recently shown great potential for the task of zero-shot learning. These models are highly sample efficient as related concepts in the graph structure share statistical strength allowing generalization to new classes when faced with a lack of data. However, multi-layer architectures, which are required to propagate knowledge to distant nodes in the graph, dilute the knowledge by performing extensive Laplacian smoothing at each layer and thereby consequently decrease performance. In order to still enjoy the benefit brought by the graph structure while preventing dilution of knowledge from distant nodes, we propose a Dense Graph Propagation (DGP) module with carefully designed direct links among distant nodes. DGP allows us to exploit the hierarchical graph structure of the knowledge graph through additional connections. These connections are added based on a node's relationship to its ancestors and descendants. A weighting scheme is further used to weigh their contribution depending on the distance to the node to improve information propagation in the graph. Combined with finetuning of the representations in a two-stage training approach our method outperforms state-of-the-art zero-shot learning approaches.

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