Summary of Application-driven Innovation in Machine Learning, by David Rolnick et al.
Application-Driven Innovation in Machine Learningby David Rolnick, Alan Aspuru-Guzik, Sara Beery, Bistra Dilkina, Priya L.…
Application-Driven Innovation in Machine Learningby David Rolnick, Alan Aspuru-Guzik, Sara Beery, Bistra Dilkina, Priya L.…
ELLEN: Extremely Lightly Supervised Learning For Efficient Named Entity Recognitionby Haris Riaz, Razvan-Gabriel Dumitru, Mihai…
Generalization Error Analysis for Sparse Mixture-of-Experts: A Preliminary Studyby Jinze Zhao, Peihao Wang, Zhangyang WangFirst…
Transcribing Bengali Text with Regional Dialects to IPA using District Guided Tokensby S M Jishanul…
On permutation-invariant neural networksby Masanari Kimura, Ryotaro Shimizu, Yuki Hirakawa, Ryosuke Goto, Yuki SaitoFirst submitted…
Incorporating Exponential Smoothing into MLP: A Simple but Effective Sequence Modelby Jiqun Chu, Zuoquan LinFirst…
Robust and Scalable Model Editing for Large Language Modelsby Yingfa Chen, Zhengyan Zhang, Xu Han,…
Order of Compression: A Systematic and Optimal Sequence to Combinationally Compress CNNby Yingtao Shen, Minqing…
Imitating Cost-Constrained Behaviors in Reinforcement Learningby Qian Shao, Pradeep Varakantham, Shih-Fen ChengFirst submitted to arxiv…
A Unified Kernel for Neural Network Learningby Shao-Qun Zhang, Zong-Yi Chen, Yong-Ming Tian, Xun LuFirst…