I am a research fellow at Victoria University of Wellington (VUW), working on meta-learning in deep neural networks. My current application areas are in topics related to optimization-based few-shot learning, with a specific focus on meta-learned loss functions and optimizers. For students with prior publication experience in meta-learning or related areas, I am open to co-supervision of masters and PhD projects through VUW with Dr Qi Chen, and Prof Bing Xue. If you are interested please do not hesitate to contact me.
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PhD candidate in AI/ML interested in meta-learning, hyper-parameter optimization, and few-shot learning.
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Victoria University of Wellington
- Wellington, New Zealand
- in/christianfraymond
- https://orcid.org/0000-0002-0963-9367
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Evolved-Model-Agnostic-Loss
Evolved-Model-Agnostic-Loss PublicPyTorch code for the EvoMAL algorithm presented in "Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning" (TPAMI-2023). Paper Link: https://arxiv.org/abs/2209.08907
Python 12
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Genetic-Programming-with-Rademacher-Complexity
Genetic-Programming-with-Rademacher-Complexity PublicCode for the GP-RC algorithm presented in "Genetic Programming with Rademacher Complexity for Symbolic Regression" (CEC-2019). Paper Link: https://ieeexplore.ieee.org/document/8790341
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