Olaf Behrendt

I'm a Munich based mathematician.

My work interest is in quantitative modelling of natural and social phenomena, from topics in finance to information retrieval and artificial neural networks.

I respond to .

Featured Explorations

What is a Web Search Engine?
Here I do a little experiment showing that all investigated alternative search engines are infact search proxies and fully dependent on MS Bing search results. Moreover Qwant and Brave Search mislead users by stating that they alledgely operate their own index and technology -- which is in contrast to empirical data.
SIR model
There has been a lot interest on simulation the devolpment of infectious deseases since the COVID-19 pandemic of 2019/20. Many different models and approaches exist to computationally simulate the spread of infectious deseases.
Evaluation Similarity Search
Using published results for the performance of state-of-the-art AI document-vector embeddings and semantic hashing I evaluated a canonical document-vector retrieval system boosted by approximate nearest neighbour search.
Cosine Similarity and Intrinsic Dimension
The cosine measure is the prevailing similarity function for the document vector model of IR. We discuss a its connection to the intrinsic dimension.
Hierarchical Clustering in IR
Hierarchical agglomerative clustering (HAC) is a family of different algorithms to perform grouping of data. HAC starts by merging the two data points with smallest distance into a new cluster and finishes with one big cluster describing the data.
Visualizing k-means++
Initialization of k-means can have a big impact on the performance of the k-means clustering algorithm. Straight forward random initialization can lead to many more iterations compared to a better initialization using kmeans++.
GMDB Binomial Tree Pricing
Here I show how to price a simple GMDB (unit linked insurance product) using installment options and calculate the premium using a binominal tree approach. The analysis shows that non-rational policy holder behaviour leads to strong mispricing.