Summary of Towards Meta-pruning Via Optimal Transport, by Alexander Theus et al.
Towards Meta-Pruning via Optimal Transportby Alexander Theus, Olin Geimer, Friedrich Wicke, Thomas Hofmann, Sotiris Anagnostidis,…
Towards Meta-Pruning via Optimal Transportby Alexander Theus, Olin Geimer, Friedrich Wicke, Thomas Hofmann, Sotiris Anagnostidis,…
The Relevance Feature and Vector Machine for health applicationsby Albert Belenguer-Llorens, Carlos Sevilla-Salcedo, Emilio Parrado-Hernández,…
Learning Attributed Graphlets: Predictive Graph Mining by Graphlets with Trainable Attributeby Tajima Shinji, Ren Sugihara,…
A Survey on Transformer Compressionby Yehui Tang, Yunhe Wang, Jianyuan Guo, Zhijun Tu, Kai Han,…
Vanishing Feature: Diagnosing Model Merging and Beyondby Xingyu Qu, Samuel HorvathFirst submitted to arxiv on:…
Succinct Interaction-Aware Explanationsby Sascha Xu, Joscha Cüppers, Jilles VreekenFirst submitted to arxiv on: 8 Feb…
Exploring Learning Complexity for Efficient Downstream Dataset Pruningby Wenyu Jiang, Zhenlong Liu, Zejian Xie, Songxin…
Everybody Prune Now: Structured Pruning of LLMs with only Forward Passesby Lucio Dery, Steven Kolawole,…
Compressing Deep Reinforcement Learning Networks with a Dynamic Structured Pruning Method for Autonomous Drivingby Wensheng…
Less is KEN: a Universal and Simple Non-Parametric Pruning Algorithm for Large Language Modelsby Michele…