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- research-articleAugust 2024
Nebula: An Edge-Cloud Collaborative Learning Framework for Dynamic Edge Environments
ICPP '24: Proceedings of the 53rd International Conference on Parallel ProcessingAugust 2024, Pages 782–791https://doi.org/10.1145/3673038.3673120To bring the great power of modern DNNs into mobile computing and distributed systems, current practices primarily employ one of the two learning paradigms: cloud-based learning or on-device learning. Despite their distinct advantages, neither of these ...
- research-articleJuly 2024JUST ACCEPTED
MedNER: Enhanced Named Entity Recognition in Medical Corpus via Optimized Balanced and Deep Active Learning
ACM Transactions on Intelligent Systems and Technology (TIST), Just Accepted https://doi.org/10.1145/3678178Ever-growing electronic medical corpora provide unprecedented opportunities for researchers to analyze patient conditions and drug effects. Meanwhile, severe challenges emerged in the large-scale electronic medical records process phase. Primarily, ...
- research-articleJuly 2024
Multi-agent cooperative strategy with explicit teammate modeling and targeted informative communication
AbstractThe mainstream Multi-Agent Reinforcement Learning (MARL) methods introduce the teammate modeling or the communication mechanism into Centralized Training Decentralized Execution (CTDE) paradigm, which can improve coordination performance. However,...
- research-articleMay 2024
FairLISA: fair user modeling with limited sensitive attributes information
NIPS '23: Proceedings of the 37th International Conference on Neural Information Processing SystemsDecember 2023, Article No.: 1796, Pages 41432–41450User modeling techniques profile users' latent characteristics (e.g., preference) from their observed behaviors, and play a crucial role in decision-making. Unfortunately, traditional user models may unconsciously capture biases related to sensitive ...
- research-articleMay 2024
A bounded ability estimation for computerized adaptive testing
- Yan Zhuang,
- Qi Liu,
- GuanHao Zhao,
- Zhenya Huang,
- Weizhe Huang,
- Zachary A. Pardos,
- Enhong Chen,
- Jinze Wu,
- Xin Li
NIPS '23: Proceedings of the 37th International Conference on Neural Information Processing SystemsDecember 2023, Article No.: 111, Pages 2381–2402Computerized adaptive testing (CAT), as a tool that can efficiently measure student's ability, has been widely used in various standardized tests (e.g., GMAT and GRE). The adaptivity of CAT refers to the selection of the most informative questions for ...
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- demonstrationOctober 2023
BranchClash: A Fully On-Chain Tower Defense Blockchain Game with New Collaboration Mechanism
MM '23: Proceedings of the 31st ACM International Conference on MultimediaOctober 2023, Pages 9385–9387https://doi.org/10.1145/3581783.3612671Mainstream blockchain games have drawn criticism for prioritizing economic systems over gameplay experience. Influenced by these economically-centered games, existing research on blockchain games predominantly focuses on the financial sector. We have ...
- research-articleOctober 2023
Simulating Student Interactions with Two-stage Imitation Learning for Intelligent Educational Systems
CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge ManagementOctober 2023, Pages 3423–3432https://doi.org/10.1145/3583780.3615060The fundamental task of intelligent educational systems is to offer adaptive learning services to students, such as exercise recommendations and computerized adaptive testing. However, optimizing required models in these systems would always encounter ...
- research-articleOctober 2023
Search-Efficient Computerized Adaptive Testing
CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge ManagementOctober 2023, Pages 773–782https://doi.org/10.1145/3583780.3615049Computerized Adaptive Testing (CAT) arises as a promising personalized test mode in online education, targeting at revealing students' latent knowledge state by selecting test items adaptively. The item selection strategy is the core component of CAT, ...
- ArticleFebruary 2024
Semantic Image Synthesis for Abdominal CT
AbstractAs a new emerging and promising type of generative models, diffusion models have proven to outperform Generative Adversarial Networks (GANs) in multiple tasks, including image synthesis. In this work, we explore semantic image synthesis for ...
- ArticleOctober 2023
From Sparse to Precise: A Practical Editing Approach for Intracardiac Echocardiography Segmentation
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023Oct 2023, Pages 766–775https://doi.org/10.1007/978-3-031-43901-8_73AbstractAccurate and safe catheter ablation procedures for atrial fibrillation require precise segmentation of cardiac structures in Intracardiac Echocardiography (ICE) imaging. Prior studies have suggested methods that employ 3D geometry information from ...
- research-articleAugust 2023
Automated Model-Based Assurance Case Management Using Constrained Natural Language
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCADICS), Volume 43, Issue 1Jan. 2024, Pages 291–304https://doi.org/10.1109/TCAD.2023.3303220Assurance cases are used to communicate and assess confidence in critical system properties, e.g., safety and security. Historically, assurance cases have been manually created documents, validated by engineers through lengthy and error-prone processes. ...
- research-articleMay 2023
Invariance encoding in sliced-Wasserstein space for image classification with limited training data
- Mohammad Shifat-E-Rabbi,
- Yan Zhuang,
- Shiying Li,
- Abu Hasnat Mohammad Rubaiyat,
- Xuwang Yin,
- Gustavo K. Rohde
Highlights- We present a mathematical framework to learn invariance to certain image transformations.
Deep convolutional neural networks (CNNs) are broadly considered to be state-of-the-art generic end-to-end image classification systems. However, they are known to underperform when training data are limited and thus require data ...
- research-articleMay 2023
Self-sovereign identity empowered non-fungible patient tokenization for health information exchange using blockchain technology
Computers in Biology and Medicine (CBIM), Volume 157, Issue CMay 2023https://doi.org/10.1016/j.compbiomed.2023.106778AbstractBackground: Patient tokenization is a novel approach that allows anonymous patient-level linkage across healthcare facilities, minimizing the risk of breaching protected health information in health information exchange (HIE). Most patient ...
Highlights- Non-fungible tokens (NFT) anonymously bridge patients' records from disparate sources.
- Self-sovereign identity (SSI) allows patients to completely control their identities.
- SSI-empowered NFT facilitates patient-centric health ...
- research-articleFebruary 2023
A robust RGB‐D visual odometry with moving object detection in dynamic indoor scenes
IET Cyber-Systems and Robotics (CSY2), Volume 5, Issue 1March 2023https://doi.org/10.1049/csy2.12079AbstractSimultaneous localisation and mapping (SLAM) are the basis for many robotic applications. As the front end of SLAM, visual odometry is mainly used to estimate camera pose. In dynamic scenes, classical methods are deteriorated by dynamic objects ...
- research-articleApril 2023
PT-Fuzz: A Transformer Based Fuzzing Data Generation Method
ICNCC '22: Proceedings of the 2022 11th International Conference on Networks, Communication and ComputingDecember 2022, Pages 277–283https://doi.org/10.1145/3579895.3579937American Fuzzy Lop (AFL) is one of the most widely used overlay-oriented fuzzers in the field of fuzz processing. In the process of analyzing AFL, we found that the number of tests per code block in the AFL testing process is very unevenly distributed. ...
- research-articleDecember 2022
Towards High-Quality CGRA Mapping with Graph Neural Networks and Reinforcement Learning
ICCAD '22: Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided DesignOctober 2022, Article No.: 61, Pages 1–9https://doi.org/10.1145/3508352.3549458Coarse-Grained Reconfigurable Architectures (CGRA) is a promising solution to accelerate domain applications due to its good combination of energy-efficiency and flexibility. Loops, as computation-intensive parts of applications, are often mapped onto ...
- ArticleOctober 2022
Hierarchical Long-Short Transformer for Group Activity Recognition
Pattern Recognition and Computer VisionOct 2022, Pages 233–244https://doi.org/10.1007/978-3-031-18913-5_18AbstractGroup activity recognition is a challenging task in computer vision, which needs to comprehensively model the diverse spatio-temporal relations among individuals and generate group representation. In this paper, we propose a novel group activity ...
- research-articleOctober 2022
Fibonacci numbers, consecutive patterns, and inverse peaks
Advances in Applied Mathematics (AAMA), Volume 141, Issue COct 2022https://doi.org/10.1016/j.aam.2022.102406AbstractWe give multiple proofs of two formulas concerning the enumeration of permutations avoiding a monotone consecutive pattern with a certain value for the inverse peak number or inverse left peak number statistic. The enumeration in both ...
- research-articleSeptember 2022
Hybrid sparse monocular visual odometry with online photometric calibration
International Journal of Robotics Research (RBRS), Volume 41, Issue 11-12Sep 2022, Pages 993–1021https://doi.org/10.1177/02783649221107703Most monocular visual Simultaneous Localization and Mapping (vSLAM) and visual odometry (VO) algorithms focus on either feature-based methods or direct methods. Hybrid (semi-direct) approach is less studied although it is equally important. In this paper,...
- research-articleAugust 2022
From luna to solar: the evolutions of the compute-to-storage networks in Alibaba cloud
- Rui Miao,
- Lingjun Zhu,
- Shu Ma,
- Kun Qian,
- Shujun Zhuang,
- Bo Li,
- Shuguang Cheng,
- Jiaqi Gao,
- Yan Zhuang,
- Pengcheng Zhang,
- Rong Liu,
- Chao Shi,
- Binzhang Fu,
- Jiaji Zhu,
- Jiesheng Wu,
- Dennis Cai,
- Hongqiang Harry Liu
SIGCOMM '22: Proceedings of the ACM SIGCOMM 2022 ConferenceAugust 2022, Pages 753–766https://doi.org/10.1145/3544216.3544238This paper presents the two generations of storage network stacks that reduced the average I/O latency of Alibaba Cloud's EBS service by 72% in the last five years: Luna, a user-space TCP stack that corresponds the latency of network to the speed of SSD; ...