Beyond Human-Level Accuracy: Computational Challenges in Deep Learning

3 September 2019

Papers citing "Beyond Human-Level Accuracy: Computational Challenges in Deep Learning"

9 / 9 papers shown

Title
Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws Nikhil Sardana Jacob P. Portes Sasha Doubov Jonathan Frankle LRM 251 73 0 31 Dec 2023
Hera: A Heterogeneity-Aware Multi-Tenant Inference Server for Personalized Recommendations Yujeong Choi John Kim Minsoo Rhu 21 1 0 23 Feb 2023
Cross-Subject Deep Transfer Models for Evoked Potentials in Brain-Computer Interface Chad A. Mello Troy Weingart Ethan M. Rudd 14 0 0 29 Jan 2023
Navigating causal deep learning Jeroen Berrevoets Krzysztof Kacprzyk Zhaozhi Qian M. Schaar CML 41 2 0 01 Dec 2022
Requirements Engineering for Machine Learning: A Review and Reflection Zhong Pei Lin Liu Chen Wang Jianmin Wang VLM 45 22 0 03 Oct 2022
Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback Yuntao Bai Andy Jones Kamal Ndousse Amanda Askell Anna Chen ... Jack Clark Sam McCandlish C. Olah Benjamin Mann Jared Kaplan 98 2,352 0 12 Apr 2022
Is the Number of Trainable Parameters All That Actually Matters? A. Chatelain Amine Djeghri Daniel Hesslow Julien Launay Iacopo Poli 56 7 0 24 Sep 2021
Understanding Capacity-Driven Scale-Out Neural Recommendation Inference Michael Lui Yavuz Yetim Özgür Özkan Zhuoran Zhao Shin-Yeh Tsai Carole-Jean Wu Mark Hempstead GNN BDL LRM 22 51 0 04 Nov 2020
Effective Approaches to Attention-based Neural Machine Translation Thang Luong Hieu H. Pham Christopher D. Manning 220 7,930 0 17 Aug 2015