The conventional wisdom of simple models in signal processing and machine learning misses the bigger picture, especially over-parameterized neural networks (NNs), where the number of parameters are much larger than the number of training data. Our goal is to explore the mystery behind over-parameterized NNs from a theoretical side.

In this talk, I will discuss the role of over-parameterization in neural networks, to theoretically understand why they can perform well. First, I will discuss the role of over-parameterization in neural networks, to theoretically understand why they can perform well in terms of benign overfitting and double descent. Furthermore, I will talk about the robustness of neural networks, affected by architecture and initialization in a function space theory view. It aims to answer a fundamental question: over-parameterization in NNs helps or hurts robustness? Besides, from classical statistical learning to sequential decision making, I will talk about the benefits of over-parameterization on how deep reinforcement learning works well for function approximation. Potential future directions on theory of over-parameterization ML will also be discussed.

The Role of Over-Parameterization in Machine Learning – the Good, the Bad, the Ugly

New Faculty Highlights

technical paper

We are pleased to announce the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI-24), which will be held in Vancouver, British Columbia at the Vancouver Convention Centre – West Building from 20-27 February, 2024.

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. AAAI-24 will feature technical paper presentations, special tracks, invited speakers, workshops, tutorials, poster sessions, senior member presentations, competitions, and exhibit programs, and a range of other activities to be announced.

We expect for AAAI-24 to be an in-person conference – one author of all accepted papers will be expected to present work in person unless there are exceptional circumstances that prevent this.<br><br><br><br>

In order to access the AAAI-24 event page you need to register [here](https://aaai.org/aaai-conference/registration/)

AAAI 2024

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. 

Fanghui Liu

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The Role of Over-Parameterization in Machine Learning – the Good, the Bad, the Ugly

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