Yingyan (Celine) Lin
Orcid: 0000-0001-5946-203XAffiliations:
- Georgia Institute of Technology, Atlanta, GA, USA
According to our database1,
Yingyan (Celine) Lin
authored at least 116 papers
between 2012 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
AutoAI2C: An Automated Hardware Generator for DNN Acceleration on Both FPGA and ASIC.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., October, 2024
ACM Trans. Embed. Comput. Syst., May, 2024
Towards Efficient Neuro-Symbolic AI: From Workload Characterization to Hardware Architecture.
CoRR, 2024
CoRR, 2024
EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning and Voting.
CoRR, 2024
ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization.
CoRR, 2024
Omni-Recon: Towards General-Purpose Neural Radiance Fields for Versatile 3D Applications.
CoRR, 2024
CoRR, 2024
Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2024
Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Omni-Recon: Harnessing Image-Based Rendering for General-Purpose Neural Radiance Fields.
Proceedings of the Computer Vision - ECCV 2024, 2024
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024
EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Unified Compression and Adaptive Layer Voting.
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024
Proceedings of the International Conference on 3D Vision, 2024
2023
IEEE Trans. Neural Networks Learn. Syst., October, 2023
NASA+: Neural Architecture Search and Acceleration for Multiplication-Reduced Hybrid Networks.
IEEE Trans. Circuits Syst. I Regul. Pap., 2023
IEEE Micro, 2023
EyeCoD: Eye Tracking System Acceleration via FlatCam-Based Algorithm and Hardware Co-Design.
IEEE Micro, 2023
Master-ASR: Achieving Multilingual Scalability and Low-Resource Adaptation in ASR with Modular Learning.
CoRR, 2023
A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware.
CoRR, 2023
Proceedings of the 31st IFIP/IEEE International Conference on Very Large Scale Integration, 2023
ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Instant-3D: Instant Neural Radiance Field Training Towards On-Device AR/VR 3D Reconstruction.
Proceedings of the 50th Annual International Symposium on Computer Architecture, 2023
Gen-NeRF: Efficient and Generalizable Neural Radiance Fields via Algorithm-Hardware Co-Design.
Proceedings of the 50th Annual International Symposium on Computer Architecture, 2023
Master-ASR: Achieving Multilingual Scalability and Low-Resource Adaptation in ASR with Modular Learning.
Proceedings of the International Conference on Machine Learning, 2023
NeRFool: Uncovering the Vulnerability of Generalizable Neural Radiance Fields against Adversarial Perturbations.
Proceedings of the International Conference on Machine Learning, 2023
GPT4AIGChip: Towards Next-Generation AI Accelerator Design Automation via Large Language Models.
Proceedings of the IEEE/ACM International Conference on Computer Aided Design, 2023
ERSAM: Neural Architecture Search for Energy-Efficient and Real-Time Social Ambiance Measurement.
Proceedings of the IEEE International Conference on Acoustics, 2023
ViTCoD: Vision Transformer Acceleration via Dedicated Algorithm and Accelerator Co-Design.
Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2023
ViTALiTy: Unifying Low-rank and Sparse Approximation for Vision Transformer Acceleration with a Linear Taylor Attention.
Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2023
Instant-NeRF: Instant On-Device Neural Radiance Field Training via Algorithm-Accelerator Co-Designed Near-Memory Processing.
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023
NetBooster: Empowering Tiny Deep Learning By Standing on the Shoulders of Deep Giants.
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023
Robust Tickets Can Transfer Better: Drawing More Transferable Subnetworks in Transfer Learning.
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023
Hint-Aug: Drawing Hints from Foundation Vision Transformers towards Boosted Few-shot Parameter-Efficient Tuning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention at Vision Transformer Inference.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
Auto-CARD: Efficient and Robust Codec Avatar Driving for Real-time Mobile Telepresence.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference.
ACM Trans. Design Autom. Electr. Syst., 2022
RT-RCG: Neural Network and Accelerator Search Towards Effective and Real-time ECG Reconstruction from Intracardiac Electrograms.
ACM J. Emerg. Technol. Comput. Syst., 2022
Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention During Vision Transformer Inference.
CoRR, 2022
LDP: Learnable Dynamic Precision for Efficient Deep Neural Network Training and Inference.
CoRR, 2022
e-G2C: A 0.14-to-8.31 µJ/Inference NN-based Processor with Continuous On-chip Adaptation for Anomaly Detection and ECG Conversion from EGM.
Proceedings of the IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits 2022), 2022
i-FlatCam: A 253 FPS, 91.49 µJ/Frame Ultra-Compact Intelligent Lensless Camera for Real-Time and Efficient Eye Tracking in VR/AR.
Proceedings of the IEEE Symposium on VLSI Technology and Circuits (VLSI Technology and Circuits 2022), 2022
Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling.
Proceedings of the Fifth Conference on Machine Learning and Systems, 2022
EyeCoD: eye tracking system acceleration via flatcam-based algorithm & accelerator co-design.
Proceedings of the ISCA '22: The 49th Annual International Symposium on Computer Architecture, New York, New York, USA, June 18, 2022
ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks.
Proceedings of the International Conference on Machine Learning, 2022
DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks.
Proceedings of the International Conference on Machine Learning, 2022
PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
NASA: Neural Architecture Search and Acceleration for Hardware Inspired Hybrid Networks.
Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design, 2022
RT-NeRF: Real-Time On-Device Neural Radiance Fields Towards Immersive AR/VR Rendering.
Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design, 2022
GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design.
Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2022
Proceedings of the 32nd International Conference on Field-Programmable Logic and Applications, 2022
Proceedings of the 30th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2022
SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning.
Proceedings of the Computer Vision - ECCV 2022, 2022
Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022
Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022
MIA-Former: Efficient and Robust Vision Transformers via Multi-Grained Input-Adaptation.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
Early-Bird GCNs: Graph-Network Co-optimization towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Tickets.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles.
IEEE Trans. Mob. Comput., 2021
ACM Trans. Internet Things, 2021
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2021
Introduction to the Special Issue on Hardware and Algorithms for Efficient Machine Learning - Part 2.
ACM J. Emerg. Technol. Comput. Syst., 2021
Introduction of Special Issue on Hardware and Algorithms for Efficient Machine Learning-Part 1.
ACM J. Emerg. Technol. Comput. Syst., 2021
CoRR, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
I-GCN: A Graph Convolutional Network Accelerator with Runtime Locality Enhancement through Islandization.
Proceedings of the MICRO '21: 54th Annual IEEE/ACM International Symposium on Microarchitecture, 2021
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency.
Proceedings of the MICRO '21: 54th Annual IEEE/ACM International Symposium on Microarchitecture, 2021
Proceedings of the IEEE/ACM International Symposium on Low Power Electronics and Design, 2021
Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators.
Proceedings of the 38th International Conference on Machine Learning, 2021
Double-Win Quant: Aggressively Winning Robustness of Quantized Deep Neural Networks via Random Precision Training and Inference.
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
Proceedings of the 9th International Conference on Learning Representations, 2021
SACoD: Sensor Algorithm Co-Design Towards Efficient CNN-powered Intelligent PhlatCam.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2021
O-HAS: Optical Hardware Accelerator Search for Boosting Both Acceleration Performance and Development Speed.
Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2021
Proceedings of the HotOS '21: Workshop on Hot Topics in Operating Systems, 2021
A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning.
Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021
InstantNet: Automated Generation and Deployment of Instantaneously Switchable-Precision Networks.
Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021
2020
Dual Dynamic Inference: Enabling More Efficient, Adaptive, and Controllable Deep Inference.
IEEE J. Sel. Top. Signal Process., 2020
Auto-Agent-Distiller: Towards Efficient Deep Reinforcement Learning Agents via Neural Architecture Search.
CoRR, 2020
AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles.
CoRR, 2020
Bringing Powerful Machine-Learning Systems to Daily-Life Devices via Algorithm-Hardware Co-Design.
Proceedings of the 2020 International Symposium on VLSI Design, Automation and Test, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
A New MRAM-Based Process In-Memory Accelerator for Efficient Neural Network Training with Floating Point Precision.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2020
Proceedings of the 47th ACM/IEEE Annual International Symposium on Computer Architecture, 2020
Timely: Pushing Data Movements And Interfaces In Pim Accelerators Towards Local And In Time Domain.
Proceedings of the 47th ACM/IEEE Annual International Symposium on Computer Architecture, 2020
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 8th International Conference on Learning Representations, 2020
DNN-Chip Predictor: An Analytical Performance Predictor for DNN Accelerators with Various Dataflows and Hardware Architectures.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
Proceedings of the FPGA '20: The 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2020
Proceedings of the Computer Vision - ECCV 2020, 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
E2-Train: Energy-Efficient Deep Network Training with Data-, Model-, and Algorithm-Level Saving.
CoRR, 2019
CoRR, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Live Demonstration: Bringing Powerful Deep Learning into Daily-Life Devices (Mobiles and FPGAs) Via Deep k-Means.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2019
2018
A Rank Decomposed Statistical Error Compensation Technique for Robust Convolutional Neural Networks in the Near Threshold Voltage Regime.
J. Signal Process. Syst., 2018
Proceedings of the 4th ACM Workshop on Micro Aerial Vehicle Networks, 2018
On-Demand Deep Model Compression for Mobile Devices: A Usage-Driven Model Selection Framework.
Proceedings of the 16th Annual International Conference on Mobile Systems, 2018
Energy-efficient Convolutional Neural Networks via Statistical Error Compensated Near Threshold Computing.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2018
Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions.
Proceedings of the 35th International Conference on Machine Learning, 2018
2017
Proceedings of the IEEE International Symposium on Circuits and Systems, 2017
2016
IEEE Trans. Circuits Syst. I Regul. Pap., 2016
Variation-Tolerant Architectures for Convolutional Neural Networks in the Near Threshold Voltage Regime.
Proceedings of the 2016 IEEE International Workshop on Signal Processing Systems, 2016
2012
A fully automated technique for constructing FSM abstractions of non-ideal latches in communication systems.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012