HyperPower: Power- and Memory-Constrained Hyper-Parameter Optimization for Neural Networks

6 December 2017

Papers citing "HyperPower: Power- and Memory-Constrained Hyper-Parameter Optimization for Neural Networks"

22 / 22 papers shown

Title
THOR: A Generic Energy Estimation Approach for On-Device Training Jiaru Zhang Zesong Wang Hao Wang Tao Song Huai-an Su ... Yang Hua Xiangwei Zhou Ruhui Ma Miao Pan Haibing Guan 106 0 0 27 Jan 2025
eScope: A Fine-Grained Power Prediction Mechanism for Mobile Applications Dipayan Mukherjee Atul Sandur K. Mechitov Pratik Lahiri Gul Agha 27 0 0 05 Apr 2024
Exploring the Carbon Footprint of Hugging Face's ML Models: A Repository Mining Study Joel Castaño Silverio Martínez-Fernández Xavier Franch Justus Bogner CVBM 98 37 0 18 May 2023
Dynamic GPU Energy Optimization for Machine Learning Training Workloads Farui Wang Weizhe Zhang Shichao Lai Meng Hao Zheng Wang 65 33 0 05 Jan 2022
A survey on multi-objective hyperparameter optimization algorithms for Machine Learning A. Hernández I. Nieuwenhuyse Sebastian Rojas Gonzalez 72 103 0 23 Nov 2021
Towards Green Automated Machine Learning: Status Quo and Future Directions Tanja Tornede Alexander Tornede Jonas Hanselle Marcel Wever F. Mohr Eyke Hüllermeier 124 38 0 10 Nov 2021
Third ArchEdge Workshop: Exploring the Design Space of Efficient Deep Neural Networks Fuxun Yu Dimitrios Stamoulis Di Wang Dimitrios Lymberopoulos Xiang Chen 3DV 51 1 0 22 Nov 2020
Performance Prediction for Convolutional Neural Networks in Edge Devices Halima Bouzidi Hamza Ouarnoughi Smail Niar A. A. E. Cadi 43 7 0 21 Oct 2020
ConfuciuX: Autonomous Hardware Resource Assignment for DNN Accelerators using Reinforcement Learning Sheng-Chun Kao Geonhwa Jeong T. Krishna 111 96 0 04 Sep 2020
Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Models Lasse F. Wolff Anthony Benjamin Kanding Raghavendra Selvan HAI 95 316 0 06 Jul 2020
PreVIous: A Methodology for Prediction of Visual Inference Performance on IoT Devices Delia Velasco-Montero Jorge Fernández-Berni R. Carmona-Galán Á. Rodríguez-Vázquez 39 21 0 13 Dec 2019
On-Device Machine Learning: An Algorithms and Learning Theory Perspective Sauptik Dhar Junyao Guo Jiayi Liu S. Tripathi Unmesh Kurup Mohak Shah 129 144 0 02 Nov 2019
Fast Hardware-Aware Neural Architecture Search Li Zhang Yuqing Yang Yuhang Jiang Wenwu Zhu Yunxin Liu 3DV 68 61 0 25 Oct 2019
Single-Path Mobile AutoML: Efficient ConvNet Design and NAS Hyperparameter Optimization Dimitrios Stamoulis Ruizhou Ding Di Wang Dimitrios Lymberopoulos B. Priyantha Jie Liu Diana Marculescu 59 34 0 01 Jul 2019
SCANN: Synthesis of Compact and Accurate Neural Networks Shayan Hassantabar Zeyu Wang N. Jha 36 38 0 19 Apr 2019
Single-Path NAS: Designing Hardware-Efficient ConvNets in less than 4 Hours Dimitrios Stamoulis Ruizhou Ding Di Wang Dimitrios Lymberopoulos B. Priyantha Jie Liu Diana Marculescu 73 285 0 05 Apr 2019
FLightNNs: Lightweight Quantized Deep Neural Networks for Fast and Accurate Inference Ruizhou Ding Z. Liu Ting-Wu Chin Diana Marculescu R. D. R. D. Blanton MQ 65 26 0 05 Apr 2019
ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation Xiaoliang Dai Peizhao Zhang Bichen Wu Hongxu Yin Fei Sun ... Yiming Wu Yangqing Jia Peter Vajda M. Uyttendaele N. Jha 94 275 0 21 Dec 2018
TEA-DNN: the Quest for Time-Energy-Accuracy Co-optimized Deep Neural Networks Lile Cai Anne-Maelle Barneche Arthur Herbout Chuan-Sheng Foo Jie Lin V. Chandrasekhar M. Sabry 63 16 0 29 Nov 2018
Hardware-Aware Machine Learning: Modeling and Optimization Diana Marculescu Dimitrios Stamoulis E. Cai 67 45 0 14 Sep 2018
Designing Adaptive Neural Networks for Energy-Constrained Image Classification Dimitrios Stamoulis Ting-Wu Chin Anand P. Krishnan Haocheng Fang S. Sajja Mitchell Bognar Diana Marculescu 103 64 0 05 Aug 2018
Not All Ops Are Created Equal! Liangzhen Lai Naveen Suda Vikas Chandra 61 24 0 12 Jan 2018