Search Results for author: Yuge Zhang

Found 10 papers, 4 papers with code

Benchmarking Data Science Agents

1 code implementation27 Feb 2024 Yuge Zhang, Qiyang Jiang, Xingyu Han, Nan Chen, Yuqing Yang, Kan Ren

In this paper, we introduce DSEval -- a novel evaluation paradigm, as well as a series of innovative benchmarks tailored for assessing the performance of these agents throughout the entire data science lifecycle.

Benchmarking Code Generation +1

MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks

1 code implementation28 Apr 2023 Lei Zhang, Yuge Zhang, Kan Ren, Dongsheng Li, Yuqing Yang

In contrast, though human engineers have the incredible ability to understand tasks and reason about solutions, their experience and knowledge are often sparse and difficult to utilize by quantitative approaches.

AutoML Code Generation

Privacy-preserving Online AutoML for Domain-Specific Face Detection

no code implementations CVPR 2022 Chenqian Yan, Yuge Zhang, Quanlu Zhang, Yaming Yang, Xinyang Jiang, Yuqing Yang, Baoyuan Wang

Thanks to HyperFD, each local task (client) is able to effectively leverage the learning "experience" of previous tasks without uploading raw images to the platform; meanwhile, the meta-feature extractor is continuously learned to better trade off the bias and variance.

AutoML Face Detection +1

AARL: Automated Auxiliary Loss for Reinforcement Learning

no code implementations29 Sep 2021 Tairan He, Yuge Zhang, Kan Ren, Che Wang, Weinan Zhang, Dongsheng Li, Yuqing Yang

A good state representation is crucial to reinforcement learning (RL) while an ideal representation is hard to learn only with signals from the RL objective.

reinforcement-learning Reinforcement Learning (RL)

Full-Cycle Energy Consumption Benchmark for Low-Carbon Computer Vision

no code implementations30 Aug 2021 Bo Li, Xinyang Jiang, Donglin Bai, Yuge Zhang, Ningxin Zheng, Xuanyi Dong, Lu Liu, Yuqing Yang, Dongsheng Li

The energy consumption of deep learning models is increasing at a breathtaking rate, which raises concerns due to potential negative effects on carbon neutrality in the context of global warming and climate change.

Model Compression

How Does Supernet Help in Neural Architecture Search?

no code implementations16 Oct 2020 Yuge Zhang, Quanlu Zhang, Yaming Yang

Weight sharing, as an approach to speed up architecture performance estimation has received wide attention.

Neural Architecture Search

Deeper Insights into Weight Sharing in Neural Architecture Search

1 code implementation6 Jan 2020 Yuge Zhang, Zejun Lin, Junyang Jiang, Quanlu Zhang, Yujing Wang, Hui Xue, Chen Zhang, Yaming Yang

With the success of deep neural networks, Neural Architecture Search (NAS) as a way of automatic model design has attracted wide attention.

Neural Architecture Search

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