6 citations · 10 across the 10 of their papers we have counts for
4 papers · 1 filter
Feedback-driven object detection and iterative model improvement
Sönke Tenckhoff, Mario Koddenbrock, Erik Rodner
Automated object detection has become increasingly valuable across diverse applications, yet efficient, high-quality annotation remains a persistent challenge. In this paper, we pr…
PMLBmini: A Tabular Classification Benchmark Suite for Data-Scarce Applications
Ricardo Knauer, Marvin Grimm, Erik Rodner
In practice, we are often faced with small-sized tabular data. However, current tabular benchmarks are not geared towards data-scarce applications, making it very difficult to deri…
"Oh LLM, I'm Asking Thee, Please Give Me a Decision Tree": Zero-Shot Decision Tree Induction and Embedding with Large Language Models
Ricardo Knauer, Mario Koddenbrock, Raphael Wallsberger +5
Large language models (LLMs) provide powerful means to leverage prior knowledge for predictive modeling when data is limited. In this work, we demonstrate how LLMs can use their co…
Squeezing Lemons with Hammers: An Evaluation of AutoML and Tabular Deep Learning for Data-Scarce Classification Applications
Ricardo Knauer, Erik Rodner
Many industry verticals are confronted with small-sized tabular data. In this low-data regime, it is currently unclear whether the best performance can be expected from simple base…