eide.ai

Date	Title	Description
Feb 25, 2025	Presentation: Guest lecture machine learning course University of Tromsø	Had the pleasure of talking to phd and master students from University of Trømsø about schibsted how we train language models.
Feb 6, 2025	Presentation: The DeepSeek hype	A non-technical presentation on the DeepSeek hype, llms and reinforcement learning.
Jan 6, 2025	Paper: BoRA	New published paper: Bayesian Hierarchical Low-Rank Adaption for Multi-task Large Language Models on the NLDL 2025 conference (paper link).

Schibsted Text Tasks

Recently, big leaps in large language models (LLMs) have shaken up fields like media and journalism. But even with all this progress, there’s still a bit of a gap when it…

Opinion: Bet on the open and global language models

Sven Thaulow (CTO Schibsted) and me have an opinion piece in the norwegian paper digi.no on open sourced LLM, and the discussion on building from scratch vs using global…

Benchmarking different Norwegian T5 models for a fine-tuning summarization task

There are many different text models to choose from when you want to perform some downstream task, but which should you choose for your fine-tuning task? Although there are…

Dynamic Slate Recommendation with Gated Recurrent Units and Thompson Sampling

Authors: Simen Eide, David S. Leslie, Arnoldo Frigessi Publication: Data Mining and Knowledge Discovery Preprint: 5 May 2021 Publication: 19 July 2022

Bayesian Neural Nets and how to effectively train them with Stochastic Gradient Markov Chain Monte Carlo

An intuitive review of training bayesian neural nets with markov chain methods

Running Google Colab with VS code

Running VScode and the python extension is great for development. I get clean python files and can run my code interactively. It is the same setup we have at work and I then…

Installing Pytorch on a raspberry pi 4

I found these wheel builds from Thomas Viehmann that worked very well on a rpi4 64 bit running python 3.7. They are pytorch 1.6.0 and avoids the original hacks. Only issue…

PILCO and Deep PILCO

Papers: - Deisenroth, M. P., & Rasmussen, C. E. (2011). PILCO: A model-based and data-efficient approach to policy search. Proceedings of the 28th International Conference…

Takeaways Recsys 2018

For the first time Ive actually made a summary of all the papers and presentations I found noteworthy at a conference (allright, there were more, but this is a start). Below…

BPMF presentation

Slides from my presentation on “Bayesian Probabilistic Matrix Factorization using Markov Chain Monte Carlo” by Salakhutdinov and Mnih. Paper link.

KDD workshop Deep learning Day: Five lessons from building a deep neural network recommender for marketplaces

Ning Zhou, Audun Øygard and I got a paper in the KDD workshop Deep Learning Day. We provide some practitioner’s findings on applying deep learning recommendations in…

Deep Recommenders, Car Pricing, Self driving rc-car and other projects in 2017

I am not a fan of new years resolutions. If I had been, one of my new years resolutions would be to be better at writing down what I am doing all the time. However, I held…

Deep NLP-based Recommenders at Finn.no

During a hackathon at FINN.no, we figured we wanted to learn more about deep NLP-models. FINN.no has a large database with ads of people trying to sell stuff (around 1…

Jupyter lab - First impression

Every three months or so I get really annoyed about Jupyter Notebook being so limited, and I usually spend half a day browsing alternatives like Spyder, PyCharm and Rodeo.…

Collaborative Filtering Recommendations in Spreadsheets

Most people have a love-hate relationship to spreadsheets. The spreadsheet format is simple and intuitive, and doing calculations becomes really easy. However, they quickly…

Presentation from Oslo Data Science Meetup

In February I talked about the recommendation models we have at FINN.no, and how we work to develop and test new models. It was exciting to be talking to so many people…