activity
20112026
most citedThe directed landscape

110 citations · 183 across the 16 of their papers we have counts for

collaborators

18 papers

math.OC2026

A scenario-cluster-based and enhanced progressive hedging algorithm for the two-stage stochastic quadratic knapsack problem

Ibrahim Dan Dije, Franklin Djeumou Fomeni, Leandro C. Coelho +1

This paper introduces the two-stage stochastic quadratic knapsack problem (TSSQKP) with uncertainty in profits and weights. To overcome the computational difficulties arising from…

math.PR2025

A Gaussian integral formula for the Hermite polynomials: Combinatorics, Asymptotics and Applications

Mihai Nica, Janosch Ortmann

The Hermite polynomials are ubiquitous but can be difficult to work with due to their unwieldy definition in terms of derivatives. To remedy this, we showcase an underappreciated G…

stat.AP2023★ 1 cited

On the distribution of cosine similarity with application to biology

Ian Smith, Janosch Ortmann, Farnoosh Abbas-Aghababazadeh +2

Cosine similarity is an established similarity metric for computing associations on vectors, and it is commonly used to identify related samples from biological perturbational data…

math.OC2023

Gröbner and Graver bases for calculating Opportunity Cost Matrices

Yuchen Ge, Janosch Ortmann, Walter Rei

Opportunity cost matrices are interesting in the context of scenario reduction. We provide new algorithms, based on ideas from algebraic geometry, to efficiently compute the opport…

math.PR2022★ 1 cited

Coupling derivation of optimal-order central moment bounds in exponential last-passage percolation

Elnur Emrah, Nicos Georgiou, Janosch Ortmann

We introduce new probabilistic arguments to derive optimal-order central moment bounds in planar directed last-passage percolation. Our technique is based on couplings with the inc…

math.OC2021★ 5 cited

Problem-Driven Scenario Clustering in Stochastic Optimization

Julien Keutchayan, Janosch Ortmann, Walter Rei

In stochastic optimisation, the large number of scenarios required to faithfully represent the underlying uncertainty is often a barrier to finding efficient numerical solutions. T…