Haichuan Yang
12 papers · 2014–2024 · 6 venues · across top CS/AI venues
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Machine Learning
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Deep Learning
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Optimization & Theory Β· Machine Learning
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Optimization & Theory Β· Deep Learning
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Keywords
model compression
(5)
constrained optimization
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neural network compression
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feature selection
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energy constraint
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compressed sensing
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neural network pruning
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combinatorial optimization
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policy gradient
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energy efficiency
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sparse learning
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secure computation
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machine translation
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network pruning
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group sparsity
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similarity search
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neural network optimization
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neural architecture search
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adversarial robustness
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Papers
Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts
ACL 2024
CoPriv: Network/Protocol Co-Optimization for Communication-Efficient Private Inference
NeurIPS 2023
DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks
ICML 2022
Automatic Neural Network Compression by Sparsity-Quantization Joint Learning: A Constrained Optimization-Based Approach
CVPR 2020
GAN Slimming: All-in-One GAN Compression by A Unified Optimization Framework
ECCV 2020
ECC: Platform-Independent Energy-Constrained Deep Neural Network Compression via a Bilinear Regression Model
CVPR 2019
Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking
ICLR 2019
Marginal Policy Gradients: A Unified Family of Estimators for Bounded Action Spaces with Applications
ICLR 2019
Model Compression with Adversarial Robustness: A Unified Optimization Framework
NeurIPS 2019
On The Projection Operator to A Three-view Cardinality Constrained Set
ICML 2017
On Benefits of Selection Diversity via Bilevel Exclusive Sparsity
CVPR 2016
Adaptive Object Retrieval with Kernel Reconstructive Hashing
CVPR 2014