Search Results for author: Chenyang Ma

Found 8 papers, 2 papers with code

See, Imagine, Plan: Discovering and Hallucinating Tasks from a Single Image

no code implementations18 Mar 2024 Chenyang Ma, Kai Lu, Ta-Ying Cheng, Niki Trigoni, Andrew Markham

Humans can not only recognize and understand the world in its current state but also envision future scenarios that extend beyond immediate perception.

Hallucination Motion Planning

Pre-Training LiDAR-Based 3D Object Detectors Through Colorization

1 code implementation23 Oct 2023 Tai-Yu Pan, Chenyang Ma, Tianle Chen, Cheng Perng Phoo, Katie Z Luo, Yurong You, Mark Campbell, Kilian Q. Weinberger, Bharath Hariharan, Wei-Lun Chao

Accurate 3D object detection and understanding for self-driving cars heavily relies on LiDAR point clouds, necessitating large amounts of labeled data to train.

3D Object Detection Colorization +4

Secure Vertical Federated Learning Under Unreliable Connectivity

no code implementations26 May 2023 Xinchi Qiu, Heng Pan, Wanru Zhao, Yan Gao, Pedro P. B. Gusmao, William F. Shen, Chenyang Ma, Nicholas D. Lane

Most work in privacy-preserving federated learning (FL) has focused on horizontally partitioned datasets where clients hold the same features and train complete client-level models independently.

Privacy Preserving Vertical Federated Learning

Efficient Vertical Federated Learning with Secure Aggregation

no code implementations18 May 2023 Xinchi Qiu, Heng Pan, Wanru Zhao, Chenyang Ma, Pedro Porto Buarque de Gusmão, Nicholas D. Lane

The majority of work in privacy-preserving federated learning (FL) has been focusing on horizontally partitioned datasets where clients share the same sets of features and can train complete models independently.

Fraud Detection Privacy Preserving +1

Gradient-less Federated Gradient Boosting Trees with Learnable Learning Rates

1 code implementation15 Apr 2023 Chenyang Ma, Xinchi Qiu, Daniel J. Beutel, Nicholas D. Lane

The privacy-sensitive nature of decentralized datasets and the robustness of eXtreme Gradient Boosting (XGBoost) on tabular data raise the needs to train XGBoost in the context of federated learning (FL).

Federated Learning

Touch and Go: Learning from Human-Collected Vision and Touch

no code implementations22 Nov 2022 Fengyu Yang, Chenyang Ma, Jiacheng Zhang, Jing Zhu, Wenzhen Yuan, Andrew Owens

The ability to associate touch with sight is essential for tasks that require physically interacting with objects in the world.

Image Stylization

Sparse and Complete Latent Organization for Geospatial Semantic Segmentation

no code implementations CVPR 2022 Fengyu Yang, Chenyang Ma

In particular, to enhance the sparsity of the latent space, we design a prototypical contrastive learning to have prototypes of the same category clustering together and prototypes of different categories to be far away from each other.

Contrastive Learning Semantic Segmentation

The Optimization of the Constant Flow Parallel Micropump Using RBF Neural Network

no code implementations17 Sep 2021 Chenyang Ma, Boyuan Xu, Hesheng Liu

The objective of this work is to optimize the performance of a constant flow parallel mechanical displacement micropump, which has parallel pump chambers and incorporates passive check valves.

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