no code implementations • 19 Mar 2024 • Yongtao Wu, Fanghui Liu, Carl-Johann Simon-Gabriel, Grigorios G Chrysos, Volkan Cevher
Recent developments in neural architecture search (NAS) emphasize the significance of considering robust architectures against malicious data.
no code implementations • 30 May 2023 • Zhenyu Zhu, Fanghui Liu, Grigorios G Chrysos, Francesco Locatello, Volkan Cevher
This paper focuses on over-parameterized deep neural networks (DNNs) with ReLU activation functions and proves that when the data distribution is well-separated, DNNs can achieve Bayes-optimal test error for classification while obtaining (nearly) zero-training error under the lazy training regime.
no code implementations • CVPR 2023 • Grigorios G Chrysos, Bohan Wang, Jiankang Deng, Volkan Cevher
We introduce a class of PNs, which are able to reach the performance of ResNet across a range of six benchmarks.
no code implementations • 16 Sep 2022 • Yongtao Wu, Zhenyu Zhu, Fanghui Liu, Grigorios G Chrysos, Volkan Cevher
Neural tangent kernel (NTK) is a powerful tool to analyze training dynamics of neural networks and their generalization bounds.
no code implementations • 15 Sep 2022 • Zhenyu Zhu, Fanghui Liu, Grigorios G Chrysos, Volkan Cevher
In particular, when initialized with LeCun initialization, depth helps robustness with the lazy training regime.
no code implementations • 15 Sep 2022 • Zhenyu Zhu, Fanghui Liu, Grigorios G Chrysos, Volkan Cevher
To this end, we derive the lower (and upper) bounds of the minimum eigenvalue of the Neural Tangent Kernel (NTK) under the (in)finite-width regime using a certain search space including mixed activation functions, fully connected, and residual neural networks.
1 code implementation • 15 Sep 2022 • Elias Abad Rocamora, Mehmet Fatih Sahin, Fanghui Liu, Grigorios G Chrysos, Volkan Cevher
Polynomial Networks (PNs) have demonstrated promising performance on face and image recognition recently.
no code implementations • 14 Jun 2022 • Yongtao Wu, Grigorios G Chrysos, Volkan Cevher
Our models can encourage the systematic design of other efficient architectures on the complex field.
no code implementations • ICLR 2022 • Zhenyu Zhu, Fabian Latorre, Grigorios G Chrysos, Volkan Cevher
While the class of Polynomial Nets demonstrates comparable performance to neural networks (NN), it currently has neither theoretical generalization characterization nor robustness guarantees.
no code implementations • CVPR 2022 • Markos Georgopoulos, James Oldfield, Grigorios G Chrysos, Yannis Panagakis
The results highlight the ability of our approach to condition image generation on attributes like gender, pose and hair style on faces, as well as a variety of features on different object classes.
2 code implementations • 16 Apr 2021 • Grigorios G Chrysos, Markos Georgopoulos, Jiankang Deng, Jean Kossaifi, Yannis Panagakis, Anima Anandkumar
The efficacy of the proposed models is evaluated on standard image and audio classification benchmarks.
Ranked #2 on Audio Classification on Speech Commands
1 code implementation • 11 Apr 2021 • Grigorios G Chrysos, Markos Georgopoulos, Yannis Panagakis
We exhibit how CoPE can be trivially augmented to accept an arbitrary number of input variables.