Chaoyang He
11 papers · 2020–2024 · 6 venues · across top CS/AI venues
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Artificial Intelligence
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Machine Learning
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Application Areas
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Core AI
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Learning Paradigms · Artificial Intelligence
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Deep Learning
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Architectures
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Optimization & Theory · Machine Learning
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Optimization & Theory · Deep Learning
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Natural Language Processing
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Keywords
federated learning
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non-iid data
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model compression
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edge computing
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sequence tagging
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hyperparameter optimization
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text classification
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class-incremental learning
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multi-task learning
(1)
neural architecture search
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question answering
(1)
data-free learning
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efficient inference
(1)
query efficiency
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model serving
(1)
neural network optimization
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gradient descent
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resource allocation
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distributed training
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knowledge distillation
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Papers
ScaleLLM: A Resource-Frugal LLM Serving Framework by Optimizing End-to-End Efficiency
EMNLP 2024
TensorOpera Router: A Multi-Model Router for Efficient LLM Inference
EMNLP 2024
A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks
NeurIPS 2023
FairFed: Enabling Group Fairness in Federated Learning
AAAI 2023
FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks
NAACL 2022
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings
NeurIPS 2022
SpreadGNN: Decentralized Multi-Task Federated Learning for Graph Neural Networks on Molecular Data
AAAI 2022
MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge
NeurIPS 2021
PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models
ICML 2021
Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge
NeurIPS 2020
MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation
CVPR 2020