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Seng Pei Liew
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2020 – today
- 2024
- [c8]Ryo Shirai, Ryo Imai, Seng Pei Liew, Daichi Amagata, Tsubasa Takahashi, Takahiro Hara:
Estimating Visited Stores Through Positive-Unlabeled Learning. DASFAA (7) 2024: 377-389 - [i11]Shang Liu, Yang Cao, Takao Murakami, Weiran Liu, Seng Pei Liew, Tsubasa Takahashi, Jinfei Liu, Masatoshi Yoshikawa:
Federated Graph Analytics with Differential Privacy. CoRR abs/2405.20576 (2024) - 2023
- [j2]Ryuichi Ito, Seng Pei Liew, Tsubasa Takahashi, Yuya Sasaki, Makoto Onizuka:
Scaling Private Deep Learning with Low-rank and Sparse Gradients. J. Inf. Process. 31: 748-757 (2023) - 2022
- [j1]Fumiyuki Kato, Tsubasa Takahashi, Shun Takagi, Yang Cao, Seng Pei Liew, Masatoshi Yoshikawa:
HDPView: Differentially Private Materialized View for Exploring High Dimensional Relational Data. Proc. VLDB Endow. 15(9): 1766-1778 (2022) - [c7]Seng Pei Liew, Tsubasa Takahashi, Michihiko Ueno:
PEARL: Data Synthesis via Private Embeddings and Adversarial Reconstruction Learning. ICLR 2022 - [c6]Seng Pei Liew, Tsubasa Takahashi, Shun Takagi, Fumiyuki Kato, Yang Cao
, Masatoshi Yoshikawa:
Network Shuffling: Privacy Amplification via Random Walks. SIGMOD Conference 2022: 773-787 - [i10]Fumiyuki Kato, Tsubasa Takahashi, Shun Takagi, Yang Cao, Seng Pei Liew, Masatoshi Yoshikawa:
HDPView: Differentially Private Materialized View for Exploring High Dimensional Relational Data. CoRR abs/2203.06791 (2022) - [i9]Seng Pei Liew, Tsubasa Takahashi, Shun Takagi, Fumiyuki Kato, Yang Cao, Masatoshi Yoshikawa:
Network Shuffling: Privacy Amplification via Random Walks. CoRR abs/2204.03919 (2022) - [i8]Seng Pei Liew, Satoshi Hasegawa, Tsubasa Takahashi:
Shuffled Check-in: Privacy Amplification towards Practical Distributed Learning. CoRR abs/2206.03151 (2022) - [i7]Marin Matsumoto, Tsubasa Takahashi, Seng Pei Liew, Masato Oguchi:
Measuring Lower Bounds of Local Differential Privacy via Adversary Instantiations in Federated Learning. CoRR abs/2206.09122 (2022) - [i6]Seng Pei Liew, Tsubasa Takahashi:
Shuffle Gaussian Mechanism for Differential Privacy. CoRR abs/2206.09569 (2022) - [i5]Ryuichi Ito, Seng Pei Liew, Tsubasa Takahashi, Yuya Sasaki, Makoto Onizuka
Scaling Private Deep Learning with Low-Rank and Sparse Gradients. CoRR abs/2207.02699 (2022) - 2021
- [c5]Takuma Amada, Kazuya Kakizaki, Seng Pei Liew, Toshinori Araki, Joseph Keshet, Jun Furukawa:
Adversarial Robustness for Face Recognition: How to Introduce Ensemble Diversity among Feature Extractors? SafeAI@AAAI 2021 - [c4]Takuma Amada, Seng Pei Liew, Kazuya Kakizaki
Universal Adversarial Spoofing Attacks against Face Recognition. IJCB 2021: 1-7 - [i4]Anna Stakia, Tommaso Dorigo, Giovanni Banelli, Daniela Bortoletto
Advanced Multi-Variate Analysis Methods for New Physics Searches at the Large Hadron Collider. CoRR abs/2105.07530 (2021) - [i3]Seng Pei Liew, Tsubasa Takahashi, Michihiko Ueno:
PEARL: Data Synthesis via Private Embeddings and Adversarial Reconstruction Learning. CoRR abs/2106.04590 (2021) - [i2]Takuma Amada, Seng Pei Liew, Kazuya Kakizaki, Toshinori Araki:
Universal Adversarial Spoofing Attacks against Face Recognition. CoRR abs/2110.00708 (2021) - 2020
- [c3]Kosuke Akimoto, Seng Pei Liew, Sakiko Mishima, Ryo Mizushima, Kong Aik Lee
POCO: A Voice Spoofing and Liveness Detection Corpus Based on Pop Noise. INTERSPEECH 2020: 1081-1085 - [c2]Takayuki Sasaki, Koki Tomita, Yuto Hayaki, Seng Pei Liew, Norio Yamagaki:
Secure IoT Device Architecture Using TrustZone. SECON Workshops 2020: 1-6 - [i1]Seng Pei Liew, Tsubasa Takahashi:
FaceLeaks: Inference Attacks against Transfer Learning Models via Black-box Queries. CoRR abs/2010.14023 (2020)
2010 – 2019
- 2019
- [c1]Seng Pei Liew, Satoshi Ikeda:
Detecting Adversary using Windows Digital Artifacts. IEEE BigData 2019: 3210-3215
Coauthor Index
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