Aaron Molt retweeted
We were in contention for Best Paper!
In his second talk in the same (!) session, @AaronMolt presents our novel metric for comparing 2-wise samples: #pickme - this work is based on his Bachelor's thesis.
By the way, Aaron will be looking for a PhD position in 2026, so talk to him! #SPLC25
Aaron Molt retweeted
In his second talk in the same (!) session, @AaronMolt presents our novel metric for comparing 2-wise samples: #pickme - this work is based on his Bachelor's thesis.
By the way, Aaron will be looking for a PhD position in 2026, so talk to him! #SPLC25
Our work "Pick Me: Judging Sample Quality with Binary Decision Diagrams" has been accepted into @splcconf'25 🎉.
This work is based on the Bachelor's Thesis of my amazing student @AaronMolt (who will be looking for a PhD position soon 😉).
Details and preprint below ⬇️ #SPLC25
Aaron Molt retweeted
First talk of @AaronMolt at #SPLC25!
Aaron is presenting our work towards enabling efficient deterministic BDD compilation - this time around through eliminating atomic sets during preprocessing.
Aaand the extended version got accepted into #SPLC25 🎉
Title "Improving Deterministic BDD Compilation with Counting-Free Computation of Atomic Sets"
Joint work with @AaronMolt who will also present it at the conference.
Abstract ⤵️
Aaron Molt retweeted
Aaand the extended version got accepted into #SPLC25 🎉
Title "Improving Deterministic BDD Compilation with Counting-Free Computation of Atomic Sets"
Joint work with @AaronMolt who will also present it at the conference.
Abstract ⤵️
It has been more than 20 years since @sergio_segura2 proposed to exploit atomic sets for preprocessing feature models. Over the holidays, we came up with
"A Fast Counting-Free Algorithm for Computing Atomic Sets in Feature Models"
Paper: arxiv.org/abs/2501.12490
w/ @Aargon06
Aaron Molt retweeted
Our work "Pick Me: Judging Sample Quality with Binary Decision Diagrams" has been accepted into @splcconf'25 🎉.
This work is based on the Bachelor's Thesis of my amazing student @AaronMolt (who will be looking for a PhD position soon 😉).
Details and preprint below ⬇️ #SPLC25
Aaron Molt retweeted
It has been more than 20 years since @sergio_segura2 proposed to exploit atomic sets for preprocessing feature models. Over the holidays, we came up with
"A Fast Counting-Free Algorithm for Computing Atomic Sets in Feature Models"
Paper: arxiv.org/abs/2501.12490
w/ @Aargon06