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Chia-Yu Chen
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2020 – today
- 2024
- [c33]Bonan Zhang, Chia-Yu Chen, Naveen Verma:
Reshape and Adapt for Output Quantization (RAOQ): Quantization-aware Training for In-memory Computing Systems. ICML 2024 - 2023
- [c32]Chi-Che Chang, An-Hung Hsiao, Li-Hsiang Shen, Kai-Ten Feng, Chia-Yu Chen:
Attention-based Learning for Sleep Apnea and Limb Movement Detection using Wi-Fi CSI Signals. VTC2023-Spring 2023: 1-5 - [i7]Chi-Che Chang, An-Hung Hsiao, Li-Hsiang Shen
, Kai-Ten Feng, Chia-Yu Chen:
Attention-based Learning for Sleep Apnea and Limb Movement Detection using Wi-Fi CSI Signals. CoRR abs/2304.06474 (2023) - 2022
- [j6]Sae Kyu Lee
, Ankur Agrawal
, Joel Silberman, Matthew M. Ziegler
, Mingu Kang, Swagath Venkataramani
, Nianzheng Cao
, Bruce M. Fleischer
, Michael Guillorn, Matthew Cohen, Silvia M. Mueller, Jinwook Oh, Martin Lutz, Jinwook Jung
, Siyu Koswatta, Ching Zhou, Vidhi Zalani, Monodeep Kar, James Bonanno
, Robert Casatuta, Chia-Yu Chen
, Jungwook Choi, Howard Haynie, Alyssa Herbert, Radhika Jain
, Kyu-Hyoun Kim
, Yulong Li, Zhibin Ren, Scot Rider, Marcel Schaal, Kerstin Schelm, Michael Scheuermann, Xiao Sun
, Hung Tran, Naigang Wang
, Wei Wang, Xin Zhang
, Vinay Shah, Brian W. Curran, Vijayalakshmi Srinivasan, Pong-Fei Lu, Sunil Shukla, Kailash Gopalakrishnan, Leland Chang:
A 7-nm Four-Core Mixed-Precision AI Chip With 26.2-TFLOPS Hybrid-FP8 Training, 104.9-TOPS INT4 Inference, and Workload-Aware Throttling. IEEE J. Solid State Circuits 57(1): 182-197 (2022) - [c31]Chih-Chi Chung
, Yen-Chun Lin
, Yu-Cheng Wang
, Tze-Yu Chen
, Chia-Yu Chen
, Xinye Jiang
, Fang-Yu Lin
, Yu-Hao Weng
, Yung-Ju Chang
:
CAMPUS: A University Crowdsourcing Platform for Reporting Facility, Status Update, and Problem Area Information. CSCW Companion 2022: 59-62 - [c30]Andrea Fasoli, Chia-Yu Chen, Mauricio J. Serrano, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Kailash Gopalakrishnan:
Accelerating Inference and Language Model Fusion of Recurrent Neural Network Transducers via End-to-End 4-bit Quantization. INTERSPEECH 2022: 2038-2042 - [c29]Naigang Wang, Chi-Chun (Charlie) Liu, Swagath Venkataramani, Sanchari Sen, Chia-Yu Chen, Kaoutar El Maghraoui, Vijayalakshmi Srinivasan, Leland Chang:
Deep Compression of Pre-trained Transformer Models. NeurIPS 2022 - [c28]Chia-Yu Chen, An-Hung Hsiao, Chun-Jie Chiu, Kai-Ten Feng:
Contactless Transfer Learning Based Apnea Detection System for Wi-Fi CSI Networks. PIMRC 2022: 788-793 - [i6]Andrea Fasoli, Chia-Yu Chen, Mauricio J. Serrano, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Kailash Gopalakrishnan:
Accelerating Inference and Language Model Fusion of Recurrent Neural Network Transducers via End-to-End 4-bit Quantization. CoRR abs/2206.07882 (2022) - 2021
- [c27]Andrea Fasoli, Chia-Yu Chen, Mauricio J. Serrano, Xiao Sun
, Naigang Wang, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Wei Zhang, Zoltán Tüske, Kailash Gopalakrishnan:
4-Bit Quantization of LSTM-Based Speech Recognition Models. Interspeech 2021: 2586-2590 - [c26]Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Wang, Sanchari Sen, Jintao Zhang, Ankur Agrawal, Monodeep Kar, Shubham Jain, Alberto Mannari, Hoang Tran, Yulong Li, Eri Ogawa, Kazuaki Ishizaki, Hiroshi Inoue, Marcel Schaal, Mauricio J. Serrano, Jungwook Choi, Xiao Sun
, Naigang Wang, Chia-Yu Chen, Allison Allain, James Bonanno, Nianzheng Cao, Robert Casatuta, Matthew Cohen, Bruce M. Fleischer, Michael Guillorn, Howard Haynie, Jinwook Jung, Mingu Kang, Kyu-Hyoun Kim
, Siyu Koswatta, Sae Kyu Lee, Martin Lutz, Silvia M. Mueller, Jinwook Oh, Ashish Ranjan, Zhibin Ren, Scot Rider, Kerstin Schelm, Michael Scheuermann, Joel Silberman, Jie Yang, Vidhi Zalani, Xin Zhang, Ching Zhou, Matthew M. Ziegler, Vinay Shah, Moriyoshi Ohara, Pong-Fei Lu, Brian W. Curran, Sunil Shukla, Leland Chang, Kailash Gopalakrishnan:
RaPiD: AI Accelerator for Ultra-low Precision Training and Inference. ISCA 2021: 153-166 - [c25]Ankur Agrawal, Sae Kyu Lee, Joel Silberman, Matthew M. Ziegler, Mingu Kang, Swagath Venkataramani, Nianzheng Cao, Bruce M. Fleischer, Michael Guillorn, Matt Cohen, Silvia M. Mueller, Jinwook Oh, Martin Lutz, Jinwook Jung, Siyu Koswatta, Ching Zhou, Vidhi Zalani, James Bonanno, Robert Casatuta, Chia-Yu Chen, Jungwook Choi, Howard Haynie, Alyssa Herbert, Radhika Jain, Monodeep Kar, Kyu-Hyoun Kim
, Yulong Li, Zhibin Ren, Scot Rider, Marcel Schaal, Kerstin Schelm, Michael Scheuermann, Xiao Sun
, Hung Tran, Naigang Wang, Wei Wang, Xin Zhang, Vinay Shah, Brian W. Curran, Vijayalakshmi Srinivasan, Pong-Fei Lu, Sunil Shukla, Leland Chang, Kailash Gopalakrishnan:
A 7nm 4-Core AI Chip with 25.6TFLOPS Hybrid FP8 Training, 102.4TOPS INT4 Inference and Workload-Aware Throttling. ISSCC 2021: 144-146 - [i5]Chia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Zhang, Kailash Gopalakrishnan:
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training. CoRR abs/2104.11125 (2021) - [i4]Andrea Fasoli, Chia-Yu Chen, Mauricio J. Serrano, Xiao Sun, Naigang Wang, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Wei Zhang, Zoltán Tüske, Kailash Gopalakrishnan:
4-bit Quantization of LSTM-based Speech Recognition Models. CoRR abs/2108.12074 (2021) - 2020
- [j5]Meng-Chieh Jeffrey Lee
, Hsiao-Yu Chen, Yi-Ming Fang, Ling-Fang Wang, Chia-Yu Chen:
Learning Performance of Teaching Practice of Friendly Senior Care Space Design. Int. J. Online Pedagog. Course Des. 10(4): 32-44 (2020) - [j4]Swagath Venkataramani
, Xiao Sun
, Naigang Wang
, Chia-Yu Chen
, Jungwook Choi
, Mingu Kang, Ankur Agarwal
, Jinwook Oh, Shubham Jain
, Tina Babinsky, Nianzheng Cao
, Thomas W. Fox
, Bruce M. Fleischer, George Gristede, Michael Guillorn, Howard Haynie, Hiroshi Inoue
, Kazuaki Ishizaki, Michael J. Klaiber, Shih-Hsien Lo, Gary W. Maier, Silvia M. Mueller, Michael Scheuermann, Eri Ogawa, Marcel Schaal, Mauricio J. Serrano, Joel Silberman, Christos Vezyrtzis, Wei Wang, Fanchieh Yee, Jintao Zhang
, Matthew M. Ziegler
, Ching Zhou, Moriyoshi Ohara, Pong-Fei Lu, Brian W. Curran, Sunil Shukla
, Vijayalakshmi Srinivasan, Leland Chang, Kailash Gopalakrishnan:
Efficient AI System Design With Cross-Layer Approximate Computing. Proc. IEEE 108(12): 2232-2250 (2020) - [c24]Chia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Zhang, Kailash Gopalakrishnan:
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training. NeurIPS 2020 - [c23]Xiao Sun, Naigang Wang, Chia-Yu Chen, Jiamin Ni, Ankur Agrawal, Xiaodong Cui, Swagath Venkataramani, Kaoutar El Maghraoui, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan:
Ultra-Low Precision 4-bit Training of Deep Neural Networks. NeurIPS 2020 - [c22]Chih-Kun Ke, Mei-Yu Wu, Chia-Yu Chen:
An Intelligent Approach for Optimizing Energy-Efficient Packets Routing in the Smart Grid Internet of Things. SGIoT 2020: 260-269 - [c21]Jinwook Oh, Sae Kyu Lee, Mingu Kang, Matthew M. Ziegler, Joel Silberman, Ankur Agrawal, Swagath Venkataramani, Bruce M. Fleischer, Michael Guillorn, Jungwook Choi, Wei Wang, Silvia M. Mueller, Shimon Ben-Yehuda, James Bonanno, Nianzheng Cao, Robert Casatuta, Chia-Yu Chen, Matt Cohen, Ophir Erez, Thomas W. Fox, George Gristede, Howard Haynie, Vicktoria Ivanov, Siyu Koswatta, Shih-Hsien Lo, Martin Lutz, Gary W. Maier, Alex Mesh, Yevgeny Nustov, Scot Rider, Marcel Schaal, Michael Scheuermann, Xiao Sun
, Naigang Wang, Fanchieh Yee, Ching Zhou, Vinay Shah, Brian W. Curran, Vijayalakshmi Srinivasan, Pong-Fei Lu, Sunil Shukla, Kailash Gopalakrishnan, Leland Chang:
A 3.0 TFLOPS 0.62V Scalable Processor Core for High Compute Utilization AI Training and Inference. VLSI Circuits 2020: 1-2
2010 – 2019
- 2019
- [j3]Chia-Yu Chen
, Boris Murmann
, Jae-sun Seo
, Hoi-Jun Yoo
:
Custom Sub-Systems and Circuits for Deep Learning: Guest Editorial Overview. IEEE J. Emerg. Sel. Topics Circuits Syst. 9(2): 247-252 (2019) - [c20]Hao-Ping Lee, Kuan-yin Chen, Chih-Heng Lin, Chia-Yu Chen, Yu-Lin Chung, Yung-Ju Chang
, Chien-Ru Sun:
Does Who Matter?: Studying the Impact of Relationship Characteristics on Receptivity to Mobile IM Messages. CHI 2019: 526 - [c19]Charbel Sakr, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Ankur Agrawal, Naresh R. Shanbhag, Kailash Gopalakrishnan:
Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks. ICLR (Poster) 2019 - [c18]Hao-Ping Lee, Tilman Dingler
, Chih-Heng Lin, Kuan-yin Chen, Yu-Lin Chung, Chia-Yu Chen, Yung-Ju Chang:
Predicting Smartphone Users' General Responsiveness to IM Contacts Based on IM Behavior. MobileHCI 2019: 40:1-40:6 - [c17]Ying-Yu Chen, Yuan-Chi Tseng, Chia-Yu Chen, Tina Chien-Wen Yuan:
Bounded & Nuanced: Designing Mobile Technology for Children and Parents. MobileHCI 2019: 76:1-76:5 - [c16]Xiao Sun, Jungwook Choi, Chia-Yu Chen, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Xiaodong Cui, Wei Zhang, Kailash Gopalakrishnan:
Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks. NeurIPS 2019: 4901-4910 - [c15]Chia-Yu Chen, I-Chen Lin:
Rapid 3D building modeling by sketching. SIGGRAPH Posters 2019: 5:1-5:2 - [c14]Chih-Kun Ke, Mei-Yu Wu, Wang-Hsin Hsu, Chia-Yu Chen:
Discover the Optimal IoT Packets Routing Path of Software-Defined Network via Artificial Bee Colony Algorithm. WiCON 2019: 147-162 - [i3]Charbel Sakr, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Ankur Agrawal, Naresh R. Shanbhag, Kailash Gopalakrishnan:
Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks. CoRR abs/1901.06588 (2019) - 2018
- [c13]Chia-Yu Chen, Jungwook Choi, Daniel Brand, Ankur Agrawal, Wei Zhang, Kailash Gopalakrishnan:
AdaComp : Adaptive Residual Gradient Compression for Data-Parallel Distributed Training. AAAI 2018: 2827-2835 - [c12]Chia-Yu Chen, Jungwook Choi, Kailash Gopalakrishnan, Viji Srinivasan, Swagath Venkataramani:
Exploiting approximate computing for deep learning acceleration. DATE 2018: 821-826 - [c11]Vijayalakshmi Srinivasan, Bruce M. Fleischer, Sunil Shukla, Matthew M. Ziegler, Joel Silberman, Jinwook Oh, Jungwook Choi, Silvia M. Mueller, Ankur Agrawal, Tina Babinsky, Nianzheng Cao, Chia-Yu Chen, Pierce Chuang, Thomas W. Fox, George Gristede, Michael Guillorn, Howard Haynie, Michael J. Klaiber, Dongsoo Lee, Shih-Hsien Lo, Gary W. Maier, Michael Scheuermann, Swagath Venkataramani, Christos Vezyrtzis, Naigang Wang, Fanchieh Yee, Ching Zhou, Pong-Fei Lu, Brian W. Curran, Leland Chang, Kailash Gopalakrishnan:
Across the Stack Opportunities for Deep Learning Acceleration. ISLPED 2018: 35:1-35:2 - [c10]Naigang Wang, Jungwook Choi, Daniel Brand, Chia-Yu Chen, Kailash Gopalakrishnan:
Training Deep Neural Networks with 8-bit Floating Point Numbers. NeurIPS 2018: 7686-7695 - [c9]Chia-Yu Chen, Chien-Yi Liu, Hsung-Pin Chang
:
A Prefetching Scheme for Multi-Tiered Storage Systems. SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2018: 1582-1586 - [c8]Bruce M. Fleischer, Sunil Shukla, Matthew M. Ziegler, Joel Silberman, Jinwook Oh, Vijayalakshmi Srinivasan, Jungwook Choi, Silvia M. Mueller, Ankur Agrawal, Tina Babinsky, Nianzheng Cao, Chia-Yu Chen, Pierce Chuang, Thomas W. Fox, George Gristede, Michael Guillorn, Howard Haynie, Michael J. Klaiber, Dongsoo Lee, Shih-Hsien Lo, Gary W. Maier, Michael Scheuermann, Swagath Venkataramani, Christos Vezyrtzis, Naigang Wang, Fanchieh Yee, Ching Zhou, Pong-Fei Lu, Brian W. Curran, Leland Chang, Kailash Gopalakrishnan:
A Scalable Multi- TeraOPS Deep Learning Processor Core for AI Trainina and Inference. VLSI Circuits 2018: 35-36 - [i2]Naigang Wang, Jungwook Choi, Daniel Brand, Chia-Yu Chen, Kailash Gopalakrishnan:
Training Deep Neural Networks with 8-bit Floating Point Numbers. CoRR abs/1812.08011 (2018) - 2017
- [c7]Ankur Agrawal, Chia-Yu Chen, Jungwook Choi, Kailash Gopalakrishnan, Jinwook Oh, Sunil Shukla, Viji Srinivasan, Swagath Venkataramani, Wei Zhang:
Accelerator Design for Deep Learning Training: Extended Abstract: Invited. DAC 2017: 57:1-57:2 - [i1]Chia-Yu Chen, Jungwook Choi, Daniel Brand, Ankur Agrawal, Wei Zhang, Kailash Gopalakrishnan:
AdaComp : Adaptive Residual Gradient Compression for Data-Parallel Distributed Training. CoRR abs/1712.02679 (2017) - 2016
- [c6]I-Fang Wang, Dennis Wang, Chia-Yu Chen, Jyun-Fong Jheng:
PinchFun: A Fine Motor Training Game for Preschool Children with Developmental Delay. CHI Extended Abstracts 2016: 152-155 - [c5]Chia-Yu Chen, Yen-Yu Chen, Yi-Ju Chung, Neng-Hao Yu
:
Motion Guidance Sleeve: Guiding the Forearm Rotation through External Artificial Muscles. CHI 2016: 3272-3276 - 2015
- [c4]Miaomiao Wang, Zuoguang Liu, Tenko Yamashita, James H. Stathis, Chia-Yu Chen:
Separation of interface states and electron trapping for hot carrier degradation in ultra-scaled replacement metal gate n-FinFET. IRPS 2015: 4 - 2014
- [j2]Yufei Wu, Chia-Yu Chen, Jesús A. del Alamo:
Activation energy of drain-current degradation in GaN HEMTs under high-power DC stress. Microelectron. Reliab. 54(12): 2668-2674 (2014) - 2010
- [c3]Shu-Chen Cheng, Wu-Yuin Hwang
, Dun-Wei Wen, Sheng-Yi Wu
, Ching-Hua Hsiehe, Chia-Yu Chen:
A Mobile and Web System with Contextual Familiarity and its Effect on Campus English Learning. DIGITEL 2010: 222-224
2000 – 2009
- 2006
- [j1]Jun-Ming Su, Shian-Shyong Tseng, Chia-Yu Chen, Jui-Feng Weng, Wen-Nung Tsai:
Constructing SCORM compliant course based on High-Level Petri Nets. Comput. Stand. Interfaces 28(3): 336-355 (2006) - 2004
- [c2]Jun-Ming Su, Shian-Shyong Tseng, Chia-Yu Chen, Jui-Feng Weng:
Constructing Scorm Compliant Course Based on High Level Petri Nets. CELDA 2004: 204-216 - [c1]Ying-Wen Bai, Chia-Yu Chen, Yu-Nien Yang:
A two-pass web document allocation method for load balancing in the multiple grouping of a Web cluster system. ICON 2004: 177-181
Coauthor Index
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