Jannis Kurtz
jannisku.bsky.social
Jannis Kurtz
@jannisku.bsky.social
assistant professor at University of Amsterdam | research in integer (robust) optimization and machine learning | scientific views are my own, all others I read somewhere
definitely interesting. My point was that scaling and constraint violation tolerance can only lead to polynomial complexity for NP-hard problems if this changes the overall problem you are solving or it kind of restricts the set of problem instances to a poly solvable subclass of the problem.
November 7, 2025 at 4:41 PM
There cannot be any algorithmic setup which has polynomial complexity for an NP-hard problem (or do you mean expected runtime complexity?). interesting directions could be to bound the number of B&B nodes for specific problems something in line with this: doi.org/10.1287/ijoc...
Estimating the Size of Branch-and-Bound Trees | INFORMS Journal on Computing
doi.org
November 7, 2025 at 3:15 PM
We show that for integer problems calculating optimal CEs is Sigma_2^p-hard and provide solution algorithms which are able to solve instances in small dimension.
October 16, 2025 at 1:55 PM
Essentially a counterfactual question applied to optimization problems asks: what is the minimal change in the problem parameters which would lead to a different but favored optimal solution?
October 16, 2025 at 1:55 PM
Counterfactual explanations (CE) recently received increasing attention as a tool to provide explanations for the decisions of optimization problems; see e.g. Kurtz et al. (2025).
October 16, 2025 at 1:55 PM
I think no real mathematician should ever be asked to come up with an application for their math. There should be a human right for this
October 15, 2025 at 10:43 AM
Meanwhile on LinkedIn: „Academic operations research is useless since papers don’t study what is useful for Amazon“
October 11, 2025 at 12:21 PM
But to be fair, this type of buzz-word repetition you also find at business schools without LLM use 😆
October 1, 2025 at 4:59 PM
But I mean the leading academics in the field are frequently debating the impact of AI (see e.g. www.youtube.com/watch?v=144u...). We can discuss how realistic or smart some arguments are but at least there is a discussion. Never saw anything coming close to this in OR.
Munk Debate on Artificial Intelligence | Bengio & Tegmark vs. Mitchell & LeCun
YouTube video by Policy-Relevant Science & Technology
www.youtube.com
August 20, 2025 at 6:11 AM
Very true, although at least in AI research people are more aware of societal/political consequences of their works. In OR people had some discussions in the 80s and after the neoliberal agenda took over it feels there is no discussion about the inherent OR ideology anymore..
August 19, 2025 at 8:06 PM