16 citations · 18 across the 3 of their papers we have counts for
3 papers
cs.LG2026
End-to-End Compression for Tabular Foundation Models
Guri Zabërgja, Rafiq Kamel, Arlind Kadra +2
The long-standing dominance of gradient-boosted decision trees for tabular data has recently been challenged by in-context learning tabular foundation models. In-context learning m…
cs.LG2024★ 2 cited
Tabular Data: Is Deep Learning all you need?
Guri Zabërgja, Arlind Kadra, Christian M. M. Frey +1
Tabular data represent one of the most prevalent data formats in applied machine learning, largely because they accommodate a broad spectrum of real-world problems. Existing litera…
cs.LG2022★ 16 cited
NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy
Yash Mehta, Colin White, Arber Zela +6
The release of tabular benchmarks, such as NAS-Bench-101 and NAS-Bench-201, has significantly lowered the computational overhead for conducting scientific research in neural archit…