Xiaohan Chen

发表

More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity

Zhangyang Wang, Mykola Pechenizkiy, D. Mocanu, 2022, 2207.03620.

D EEP E NSEMBLING WITH N O O VERHEAD FOR EITHER T RAINING OR T ESTING : T HE A LL -R OUND B LESSINGS OF D YNAMIC S PARSITY

Zhangyang Wang, Mykola Pechenizkiy, D. Mocanu, 2022 .

More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity

Xuxi Chen, Zhangyang Wang, Mykola Pechenizkiy, 2022, ICLR.

P EEK - A -B OO : W HAT (M ORE ) IS D ISGUISED IN A R ANDOMLY W EIGHTED N EURAL N ETWORK , AND H OW TO F IND I T E FFICIENTLY

Zhangyang Wang, Jason Zhang, Xiaohan Chen, 2022 .

T HE U NREASONABLE E FFECTIVENESS OF R ANDOM P RUNING : R ETURN OF THE M OST N AIVE B ASELINE FOR S PARSE T RAINING

Li Shen, Zhangyang Wang, Mykola Pechenizkiy, 2022 .

Hyperparameter Tuning is All You Need for LISTA pdf

Wotao Yin, Zhangyang Wang, Jialin Liu, 2021, NeurIPS.

Sparse Training via Boosting Pruning Plasticity with Neuroregeneration

Zhangyang Wang, Mykola Pechenizkiy, D. Mocanu, 2021, NeurIPS.

The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training

Zhangyang Wang, Mykola Pechenizkiy, D. Mocanu, 2022, ICLR.

Deep Ensembling with No Overhead for either Training or Testing: The All-Round Blessings of Dynamic Sparsity

Zhangyang Wang, Mykola Pechenizkiy, D. Mocanu, 2021, ICLR.

Sanity Checks for Lottery Tickets: Does Your Winning Ticket Really Win the Jackpot? pdf

Zhangyang Wang, Sijia Liu, Xiaolong Ma, 2021, NeurIPS.

Randomized Channel Shuffling: Minimal-Overhead Backdoor Attack Detection without Clean Datasets

Zhangyang Wang, Tianlong Chen, Xiaohan Chen, 2022, NeurIPS.

FreeTickets: Accurate, Robust and Efficient Deep Ensemble by Training with Dynamic Sparsity pdf

Mykola Pechenizkiy, Zhangyang Wang, Decebal Constantin Mocanu, 2021, ArXiv.

Learning A Minimax Optimizer: A Pilot Study

Wotao Yin, Zhangyang Wang, Jiayi Shen, 2021, ICLR.

Towards Constituting Mathematical Structures for Learning to Optimize

W. Yin, Zhangyang Wang, Jialin Liu, 2023, ICML.

Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently

Zhangyang Wang, Jason Zhang, Xiaohan Chen, 2022, ICLR.

Chasing Better Deep Image Priors between Over-and Under-parameterization

Qiming Wu, Xiaohan Chen, Yifan Jiang, 2023 .

Many-Task Federated Learning: A New Problem Setting and A Simple Baseline

R. Kompella, Myungjin Lee, Xiaohan Chen, 2023, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).