Summary of Unlocking the Theory Behind Scaling 1-bit Neural Networks, by Majid Daliri et al.
Unlocking the Theory Behind Scaling 1-Bit Neural Networksby Majid Daliri, Zhao Song, Chiwun YangFirst submitted…
Unlocking the Theory Behind Scaling 1-Bit Neural Networksby Majid Daliri, Zhao Song, Chiwun YangFirst submitted…
Rethinking Weight Decay for Robust Fine-Tuning of Foundation Modelsby Junjiao Tian, Chengyue Huang, Zsolt KiraFirst…
A General Recipe for Contractive Graph Neural Networks – Technical Reportby Maya Bechler-Speicher, Moshe EliasofFirst…
1st-Order Magic: Analysis of Sharpness-Aware Minimizationby Nalin Tiwary, Siddarth AananthFirst submitted to arxiv on: 3…
Online Relational Inference for Evolving Multi-agent Interacting Systemsby Beomseok Kang, Priyabrata Saha, Sudarshan Sharma, Biswadeep…
FEED: Fairness-Enhanced Meta-Learning for Domain Generalizationby Kai Jiang, Chen Zhao, Haoliang Wang, Feng ChenFirst submitted…
HG-Adapter: Improving Pre-Trained Heterogeneous Graph Neural Networks with Dual Adaptersby Yujie Mo, Runpeng Yu, Xiaofeng…
Provable Length Generalization in Sequence Prediction via Spectral Filteringby Annie Marsden, Evan Dogariu, Naman Agarwal,…
BACSA: A Bias-Aware Client Selection Algorithm for Privacy-Preserving Federated Learning in Wireless Healthcare Networksby Sushilkumar…
Fighting Spurious Correlations in Text Classification via a Causal Learning Perspectiveby Yuqing Zhou, Ziwei ZhuFirst…