DENT - A Tool for Tagging Stack Overflow Posts With Deep Learning Energy Patterns
Energy efficiency has become an important consideration in deep learning. However, it remains a largely under-emphasized aspect during the development. Despite the development of deep learning energy patterns, their adoption remains a challenge due to the lack of awareness. To address this gap, we present DENT (Deep Learning Energy Pattern Tagger), a Chrome extension used to add “energy pattern tags” to the deep learning related questions from Stack Overflow. The idea of DENT is to hint to the developers about the possible energy-saving opportunities associated with the Stack Overflow post through energy pattern labels. We hope this will increase awareness about energy patterns in deep learning and improve their adoption. A preliminary evaluation of DENT achieved an average precision of 0.74, recall of 0.66, and an F1-score of 0.65 with an accuracy of 66%. The demonstration of the tool is available at https://youtu.be/S0Wf_w0xajw and the related artifacts are available at https://rishalab.github.io/DENT/
Wed 6 DecDisplayed time zone: Pacific Time (US & Canada) change
14:00 - 15:30 | Machine Learning IIIDemonstrations / Industry Papers / Research Papers at Golden Gate C2 Chair(s): Rangeet Pan IBM Research | ||
14:00 15mTalk | Benchmarking Robustness of AI-enabled Multi-sensor Fusion Systems: Challenges and Opportunities Research Papers Xinyu Gao , Zhijie Wang University of Alberta, Yang Feng Nanjing University, Lei Ma The University of Tokyo / University of Alberta, Zhenyu Chen Nanjing University, Baowen Xu Nanjing University Media Attached | ||
14:15 7mTalk | A Language Model of Java Methods with Train/Test Deduplication Demonstrations Chia-Yi Su University of Notre Dame, Aakash Bansal University of Notre Dame, Vijayanta Jain University of Maine, Sepideh Ghanavati University of Maine , Collin McMillan University of Notre Dame Media Attached | ||
14:23 7mTalk | DENT - A Tool for Tagging Stack Overflow Posts With Deep Learning Energy Patterns Demonstrations Shriram Shanbhag Indian Institute of Technology Tirupati, Sridhar Chimalakonda Indian Institute of Technology Tirupati, Vibhu Saujanya Sharma Accenture Labs, India, Vikrant Kaulgud Accenture Labs, India Media Attached | ||
14:30 15mTalk | Automated Testing and Improvement of Named Entity Recognition Systems Research Papers BoXi Yu The Chinese University of Hong Kong, Shenzhen, Yiyan Hu The Chinese University of Hong Kong, Shenzhen, Qiuyang Mang The Chinese University of Hong Kong, Shenzhen, Wenhan Hu The Chinese University of Hong Kong, Shenzhen, Pinjia He The Chinese University of Hong Kong, Shenzhen Pre-print Media Attached | ||
14:45 15mTalk | KDDT: Knowledge Distillation-Empowered Digital Twin for Anomaly Detection Industry Papers Xu Qinghua Simula Research Laboratory; University of Oslo, Shaukat Ali Simula Research Laboratory and Oslo Metropolitan University, Tao Yue Beihang University, Zaimovic Nedim Alstom Rail, Inderjeet Singh Alstom DOI Media Attached | ||
15:00 15mTalk | Deep Learning Based Feature Envy Detection Boosted by Real-World Examples Research Papers Bo Liu Beijing Institute of Technology, Hui Liu Beijing Institute of Technology, Guangjie Li National Innovation Institute of Defense Technology, Nan Niu University of Cincinnati, Zimao Xu Beijing Institute of Technology, Yifan Wang Huawei Cloud, Yunni Xia Chongqing University, Yuxia Zhang Beijing Institute of Technology, Yanjie Jiang Peking University DOI Pre-print Media Attached | ||
15:15 15mTalk | [Remote] The EarlyBIRD Catches the Bug: On Exploiting Early Layers of Encoder Models for More Efficient Code Classification Research Papers Anastasiia Grishina Simula Research Laboratory, Max Hort Simula Research Laboratory, Leon Moonen Simula Research Laboratory and BI Norwegian Business School Pre-print Media Attached |