Architecture Harmonization Between Cloud Radio Access Networks and Fog Networks. - Shao-Chou Hung; Hsiang Hsu; Shao-Yu Lien; Kwang-Cheng Chen (IEEE Access, 2015)

Optimal caching time for epidemic content dissemination in mobile social networks. - Hsiang Hsu; Kwang-Cheng Chen (ICC, 2016)

Collaborative radio access of heterogeneous cloud radio access networks and edge computing networks. - Shao-Yu Lien; Shao-Chou Hung; Hsiang Hsu; Kwang-Cheng Chen (ICC Workshops, 2016)

A Resource Allocation Perspective on Caching to Achieve Low Latency. - Hsiang Hsu; Kwang-Cheng Chen (IEEE Commun. Lett., 2016)

Generalizing Bottleneck Problems. - Hsiang Hsu; Shahab Asoodeh; Salman Salamatian; Flávio P. Calmon (ISIT, 2018)

Energy-Optimal Edge Content Cache and Dissemination: Designs for Practical Network Deployment. - Shao-Yu Lien; Shao-Chou Hung; Hsiang Hsu; Der-Jiunn Deng (IEEE Commun. Mag., 2018)

Deep Orthogonal Representations: Fundamental Properties and Applications. - Hsiang Hsu; Salman Salamatian; Flávio P. Calmon (CoRR, 2018)

Correspondence Analysis of Government Expenditure Patterns. - Hsiang Hsu; Flávio P. Calmon; José Cândido Silveira Santos Filho; Andre P. Calmon; Salman Salamatian (CoRR, 2018)

Latency Control in Edge Information Cache and Dissemination for Unmanned Mobile Machines. - Shao-Yu Lien; Shao-Chou Hung; Hsiang Hsu (IEEE Trans. Ind. Informatics, 2018)

Delay Guaranteed Network Association for Mobile Machines in Heterogeneous Cloud Radio Access Network. - Shao-Chou Hung; Hsiang Hsu; Shin-Ming Cheng; Qimei Cui; Kwang-Cheng Chen (IEEE Trans. Mob. Comput., 2018)

Correspondence Analysis Using Neural Networks. - Hsiang Hsu; Salman Salamatian; Flávio P. Calmon (AISTATS, 2019)

Electromyography (EMG) Signal Contributions in Speed and Slope Estimation Using Robotic Exoskeletons. - Inseung Kang; Pratik Kunapuli; Hsiang Hsu; Aaron J. Young (ICORR, 2019)

Information-Theoretic Privacy Watchdogs. - Hsiang Hsu; Shahab Asoodeh; Flávio P. Calmon (ISIT, 2019)

The Effect of Hip Assistance Levels on Human Energetic Cost Using Robotic Hip Exoskeletons. - Inseung Kang; Hsiang Hsu; Aaron J. Young (IEEE Robotics Autom. Lett., 2019)

Graph-Based Modeling, Scheduling, and Verification for Intersection Management of Intelligent Vehicles. - Yi-Ting Lin; Hsiang Hsu; Shang-Chien Lin; Chung-Wei Lin; Iris Hui-Ru Jiang; Changliu Liu (ACM Trans. Embed. Comput. Syst., 2019)

Obfuscation via Information Density Estimation. - Hsiang Hsu; Shahab Asoodeh; Flávio P. Calmon (AISTATS, 2020)

A Dynamic Programming Approach to Optimal Lane Merging of Connected and Autonomous Vehicles. - Shang-Chien Lin; Hsiang Hsu; Yi-Ting Lin; Chung-Wei Lin; Iris Hui-Ru Jiang; Changliu Liu (IV, 2020)

CPR: Classifier-Projection Regularization for Continual Learning. - Sungmin Cha; Hsiang Hsu; Flávio P. Calmon; Taesup Moon (CoRR, 2020)

CPR: Classifier-Projection Regularization for Continual Learning. - Sungmin Cha; Hsiang Hsu; Taebaek Hwang; Flávio P. Calmon; Taesup Moon (ICLR, 2021)

The Impact of Split Classifiers on Group Fairness. - Hao Wang 063; Hsiang Hsu; Mario Díaz; Flávio P. Calmon (ISIT, 2021)

To Split or not to Split: The Impact of Disparate Treatment in Classification. - Hao Wang 063; Hsiang Hsu; Mario Díaz; Flávio P. Calmon (IEEE Trans. Inf. Theory, 2021)

Beyond Adult and COMPAS: Fair Multi-Class Prediction via Information Projection. - Wael Alghamdi; Hsiang Hsu; Haewon Jeong; Hao Wang 063; Peter Michalák; Shahab Asoodeh; Flávio P. Calmon (NeurIPS, 2022)

Rashomon Capacity: A Metric for Predictive Multiplicity in Classification. - Hsiang Hsu; Flávio P. Calmon (NeurIPS, 2022)

Rashomon Capacity: A Metric for Predictive Multiplicity in Probabilistic Classification. - Hsiang Hsu; Flávio du Pin Calmon (CoRR, 2022)

Beyond Adult and COMPAS: Fairness in Multi-Class Prediction. - Wael Alghamdi; Hsiang Hsu; Haewon Jeong; Hao Wang 063; P. Winston Michalak; Shahab Asoodeh; Flávio P. Calmon (CoRR, 2022)

Automated Segmentation and Recurrence Risk Prediction of Surgically Resected Lung Tumors with Adaptive Convolutional Neural Networks. - Marguerite B. Basta; Sarfaraz Hussein; Hsiang Hsu; Flávio P. Calmon (CoRR, 2022)

Generalizing Correspondence Analysis for Applications in Machine Learning. - Hsiang Hsu; Salman Salamatian; Flávio P. Calmon (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Arbitrary Decisions Are a Hidden Cost of Differentially Private Training. - Bogdan Kulynych; Hsiang Hsu; Carmela Troncoso; Flávio P. Calmon (EWAF, 2023)

Individual Arbitrariness and Group Fairness. - Carol Xuan Long; Hsiang Hsu; Wael Alghamdi; Flávio P. Calmon (NeurIPS, 2023)

Arbitrariness Lies Beyond the Fairness-Accuracy Frontier. - Carol Xuan Long; Hsiang Hsu; Wael Alghamdi; Flávio P. Calmon (CoRR, 2023)

Robust Hybrid Learning With Expert Augmentation. - Antoine Wehenkel; Jens Behrmann; Hsiang Hsu; Guillermo Sapiro; Gilles Louppe; Jörn-Henrik Jacobsen (Trans. Mach. Learn. Res., 2023)

Adaptive 3D UI Placement in Mixed Reality Using Deep Reinforcement Learning. - Feiyu Lu; Mengyu Chen; Hsiang Hsu; Pranav Deshpande; Cheng Yao Wang; Blair MacIntyre (CHI Extended Abstracts, 2024)

Fast-NTK: Parameter-Efficient Unlearning for Large-Scale Models. - Guihong Li; Hsiang Hsu; Chun-Fu Richard Chen; Radu Marculescu (CVPR Workshops, 2024)

Dropout-Based Rashomon Set Exploration for Efficient Predictive Multiplicity Estimation. - Hsiang Hsu; Guihong Li; Shaohan Hu; Chun-Fu Chen 001 (ICLR, 2024)

OVOR: OnePrompt with Virtual Outlier Regularization for Rehearsal-Free Class-Incremental Learning. - Wei-Cheng Huang; Chun-Fu Richard Chen; Hsiang Hsu (ICLR, 2024)

Machine Unlearning for Image-to-Image Generative Models. - Guihong Li; Hsiang Hsu; Chun-Fu Chen 001; Radu Marculescu (ICLR, 2024)

MaSS: Multi-attribute Selective Suppression for Utility-preserving Data Transformation from an Information-theoretic Perspective. - Yizhuo Chen; Chun-Fu Chen 001; Hsiang Hsu; Shaohan Hu; Marco Pistoia; Tarek F. Abdelzaher (ICML, 2024)

Adaptive Content Placement in Mixed Reality Through Empirical User Behavioral Patterns. - Feiyu Lu; Mengyu Chen; Hsiang Hsu; Pranav Deshpande; Cheng Yao Wang; Blair MacIntyre (ISMAR-Adjunct, 2024)

RashomonGB: Analyzing the Rashomon Effect and Mitigating Predictive Multiplicity in Gradient Boosting. - Hsiang Hsu; Ivan Brugere; Shubham Sharma; Freddy Lécué; Richard Chen (NeurIPS, 2024)

LLM Hallucination Reasoning with Zero-shot Knowledge Test. - Seongmin Lee 007; Hsiang Hsu; Chun-Fu Chen 001 (CoRR, 2024)

PaLD: Detection of Text Partially Written by Large Language Models. - Eric Lei; Hsiang Hsu; Chun-Fu Chen 001 (ICLR, 2025)

Optimized Couplings for Watermarking Large Language Models. - Dor Tsur; Carol Xuan Long; Claudio Mayrink Verdun; Hsiang Hsu; Haim H. Permuter; Flávio P. Calmon (CoRR, 2025)

HeavyWater and SimplexWater: Watermarking Low-Entropy Text Distributions. - Dor Tsur; Carol Xuan Long; Claudio Mayrink Verdun; Hsiang Hsu; Chen-Fu Chen; Haim H. Permuter; Sajani Vithana; Flávio P. Calmon (CoRR, 2025)

PASS: Private Attributes Protection with Stochastic Data Substitution. - Yizhuo Chen; Chun-Fu Chen 001; Hsiang Hsu; Shaohan Hu; Tarek F. Abdelzaher (CoRR, 2025)