Yingyan Lin
24 papers · 2018–2025 · 7 venues · across top CS/AI venues
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Research topics
Deep Learning
(21)
Machine Learning
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Application Areas
(19)
Optimization & Theory Β· Deep Learning
(12)
Techniques
(11)
Artificial Intelligence
(8)
Architectures
(7)
Core AI Β· Artificial Intelligence
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Optimization & Theory Β· Machine Learning
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Computer Vision
(3)
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Keywords
model compression
(11)
neural architecture search
(5)
convolutional neural network
(5)
efficient computing
(4)
vision transformer
(3)
lottery ticket hypothesis
(3)
early bird ticket
(3)
adversarial robustness
(3)
energy consumption
(2)
knowledge distillation
(2)
graph convolutional network
(2)
computational efficiency
(2)
model training
(2)
efficient training
(2)
weight sharing
(2)
adversarial training
(2)
energy efficiency
(2)
training efficiency
(2)
low-precision training
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image translation
(1)
Papers
Early-Bird Diffusion: Investigating and Leveraging Timestep-Aware Early-Bird Tickets in Diffusion Models for Efficient Training
CVPR 2025
ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer
NeurIPS 2023
DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks
ICML 2022
Early-Bird GCNs: Graph-Network Co-optimization towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Tickets
AAAI 2022
MIA-Former: Efficient and Robust Vision Transformers via Multi-Grained Input-Adaptation
AAAI 2022
Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?
ICLR 2022
PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication
ICLR 2022
ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks
ICML 2022
SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning
ECCV 2022
Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators
ICML 2021
CPT: Efficient Deep Neural Network Training via Cyclic Precision
ICLR 2021
Double-Win Quant: Aggressively Winning Robustness of Quantized Deep Neural Networks via Random Precision Training and Inference
ICML 2021
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks
NeurIPS 2021
HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark
ICLR 2021
Locality Sensitive Teaching
NeurIPS 2021
SACoD: Sensor Algorithm Co-Design Towards Efficient CNN-Powered Intelligent PhlatCam
ICCV 2021
AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks
ICML 2020
Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks
ICLR 2020
Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference
AAAI 2020
FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training
NeurIPS 2020
HALO: Hardware-Aware Learning to Optimize
ECCV 2020
ShiftAddNet: A Hardware-Inspired Deep Network
NeurIPS 2020
E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings
NeurIPS 2019
Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions
ICML 2018