Search Results for author: Kai Xiao

Found 8 papers, 3 papers with code

Quantifying and Defending against Privacy Threats on Federated Knowledge Graph Embedding

no code implementations6 Apr 2023 Yuke Hu, Wei Liang, Ruofan Wu, Kai Xiao, Weiqiang Wang, Xiaochen Li, Jinfei Liu, Zhan Qin

Knowledge Graph Embedding (KGE) is a fundamental technique that extracts expressive representation from knowledge graph (KG) to facilitate diverse downstream tasks.

Knowledge Graph Embedding

On Distinctive Properties of Universal Perturbations

no code implementations31 Dec 2021 Sung Min Park, Kuo-An Wei, Kai Xiao, Jerry Li, Aleksander Madry

We identify properties of universal adversarial perturbations (UAPs) that distinguish them from standard adversarial perturbations.

SHORING: Design Provable Conditional High-Order Interaction Network via Symbolic Testing

no code implementations3 Jul 2021 Hui Li, Xing Fu, Ruofan Wu, Jinyu Xu, Kai Xiao, xiaofu Chang, Weiqiang Wang, Shuai Chen, Leilei Shi, Tao Xiong, Yuan Qi

Deep learning provides a promising way to extract effective representations from raw data in an end-to-end fashion and has proven its effectiveness in various domains such as computer vision, natural language processing, etc.

Management Product Recommendation +1

3DB: A Framework for Debugging Computer Vision Models

1 code implementation7 Jun 2021 Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry

We introduce 3DB: an extendable, unified framework for testing and debugging vision models using photorealistic simulation.


no code implementations ICLR 2020 Krishnamurthy (Dj) Dvijotham, Jamie Hayes, Borja Balle, Zico Kolter, Chongli Qin, Andras Gyorgy, Kai Xiao, Sven Gowal, Pushmeet Kohli

Formal verification techniques that compute provable guarantees on properties of machine learning models, like robustness to norm-bounded adversarial perturbations, have yielded impressive results.

Audio Classification BIG-bench Machine Learning +1

Deep Learning Analysis of Defect and Phase Evolution During Electron Beam Induced Transformations in WS2

no code implementations14 Mar 2018 Artem Maksov, Ondrej Dyck, Kai Wang, Kai Xiao, David B. Geohegan, Bobby G. Sumpter, Rama K. Vasudevan, Stephen Jesse, Sergei V. Kalinin, Maxim Ziatdinov

Understanding elementary mechanisms behind solid-state phase transformations and reactions is the key to optimizing desired functional properties of many technologically relevant materials.

Materials Science

Evaluating Robustness of Neural Networks with Mixed Integer Programming

6 code implementations ICLR 2019 Vincent Tjeng, Kai Xiao, Russ Tedrake

The computational speedup allows us to verify properties on convolutional networks with an order of magnitude more ReLUs than networks previously verified by any complete verifier.

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