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- research-articleJuly 2024
Tropical cyclone trajectory based on satellite remote sensing prediction and time attention mechanism ConvLSTM model
AbstractThe accurate and timely prediction of tropical cyclones is of paramount importance in mitigating the impact of these catastrophic meteorological events. Presently, methods for predicting tropical cyclones based on satellite remote sensing images ...
- research-articleMay 2024
A Knowledge-Injected Curriculum Pretraining Framework for Question Answering
WWW '24: Proceedings of the ACM on Web Conference 2024May 2024, Pages 1986–1997https://doi.org/10.1145/3589334.3645406Knowledge-based question answering (KBQA) is a key task in natural language processing research, and also an approach to access the web data and knowledge, which requires exploiting knowledge graphs (KGs) for reasoning. In the literature, one promising ...
- research-articleMarch 2024JUST ACCEPTED
L-FNNG: Accelerating Large-Scale KNN Graph Construction on CPU-FPGA Heterogeneous Platform
- Chaoqiang Liu,
- Xiaofei Liao,
- Long Zheng,
- Yu Huang,
- Haifeng Liu,
- Yi Zhang,
- Haiheng He,
- Haoyan Huang,
- Jingyi Zhou,
- Hai Jin
ACM Transactions on Reconfigurable Technology and Systems (TRETS), Just Accepted https://doi.org/10.1145/3652609Due to the high complexity of constructing exact k-nearest neighbor graphs, approximate construction has become a popular research topic. The NN-Descent algorithm is one of the representative in-memory algorithms. To effectively handle large datasets, ...
- research-articleJanuary 2024
Minimal Context-Switching Data Race Detection with Dataflow Tracking
Journal of Computer Science and Technology (JCST), Volume 39, Issue 1Feb 2024, Pages 211–226https://doi.org/10.1007/s11390-023-1569-7AbstractData race is one of the most important concurrent anomalies in multi-threaded programs. Emerging constraint- based techniques are leveraged into race detection, which is able to find all the races that can be found by any other sound race ...
- research-articleJuly 2024
Knowledge Graph Question-Answering Based on Link Reasoning for Electrical Equipment
PEAI '24: Proceedings of the 2024 International Conference on Power Electronics and Artificial IntelligenceJanuary 2024, Pages 594–600https://doi.org/10.1145/3674225.3674332The construction of an intelligent question-answering system based on a knowledge graph of electrical equipment can facilitate the complex retrieval, querying, and answering of questions related to electrical equipment knowledge. However, existing ...
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- research-articleSeptember 2023
Toward Optimal Repair and Load Balance in Locally Repairable Codes
ICPP '23: Proceedings of the 52nd International Conference on Parallel ProcessingAugust 2023, Pages 725–735https://doi.org/10.1145/3605573.3605635Erasure coding is increasingly deployed in modern clustered storage systems to provide low-cost reliable storage. In particular, Locally Repairable Codes (LRCs) are a popular family of repair-efficient erasure codes that receive wide deployment in ...
- research-articleAugust 2023
Learning Balanced Tree Indexes for Large-Scale Vector Retrieval
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 1353–1362https://doi.org/10.1145/3580305.3599406Vector retrieval focuses on finding the k-nearest neighbors from a bunch of data points, and is widely used in a diverse set of areas such as information retrieval and recommender system. The current state-of-the-art methods represented by HNSW usually ...
- research-articleAugust 2023
Guiding Mathematical Reasoning via Mastering Commonsense Formula Knowledge
KDD '23: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data MiningAugust 2023, Pages 1477–1488https://doi.org/10.1145/3580305.3599375Math formulas (e.g., "distance = speed X time'') serve as one of the fundamental commonsense knowledge in human cognition, where humans naturally acquire and manipulate them in logical thinking for mathematical reasoning problems. However, existing ...
- research-articleJune 2023
Accelerating Personalized Recommendation with Cross-level Near-Memory Processing
- Haifeng Liu,
- Long Zheng,
- Yu Huang,
- Chaoqiang Liu,
- Xiangyu Ye,
- Jingrui Yuan,
- Xiaofei Liao,
- Hai Jin,
- Jingling Xue
ISCA '23: Proceedings of the 50th Annual International Symposium on Computer ArchitectureJune 2023, Article No.: 66, Pages 1–13https://doi.org/10.1145/3579371.3589101The memory-intensive embedding layers of the personalized recommendation systems are the performance bottleneck as they demand large memory bandwidth and exhibit irregular and sparse memory access patterns. Recent studies propose near memory ...
- research-articleFebruary 2023
FNNG: A High-Performance FPGA-based Accelerator for K-Nearest Neighbor Graph Construction
FPGA '23: Proceedings of the 2023 ACM/SIGDA International Symposium on Field Programmable Gate ArraysFebruary 2023, Pages 67–77https://doi.org/10.1145/3543622.3573189The k-nearest neighbor graph has emerged as the key data structure for many critical applications. However, it can be notoriously challenging to construct k-nearest neighbor graphs over large graph datasets, especially with a high-dimensional vector ...
- research-articleNovember 2022
ReaDy: A ReRAM-Based Processing-in-Memory Accelerator for Dynamic Graph Convolutional Networks
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCADICS), Volume 41, Issue 11Nov. 2022, Pages 3567–3578https://doi.org/10.1109/TCAD.2022.3199152Dynamic graph convolutional networks (DGCNs) have emerged as an effective approach to analyzing graph data that is constantly changing. The typical DGCNs incorporate not only graph convolutional networks (GCNs) to extract the structural information but ...
- research-articleNovember 2022
A Flexible Yet Efficient DNN Pruning Approach for Crossbar-Based Processing-in-Memory Architectures
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCADICS), Volume 41, Issue 11Nov. 2022, Pages 3745–3756https://doi.org/10.1109/TCAD.2022.3197510Pruning deep neural networks (DNNs) can reduce the model size and thus save hardware resources of a resistive-random-access-memory (ReRAM)-based DNN accelerator. For the tightly coupled crossbar structure, existing ReRAM-based pruning techniques prune the ...
- ArticleOctober 2022
Convolutional Embedding Makes Hierarchical Vision Transformer Stronger
AbstractVision Transformers (ViTs) have recently dominated a range of computer vision tasks, yet it suffers from low training data efficiency and inferior local semantic representation capability without appropriate inductive bias. Convolutional neural ...
- ArticleOctober 2022
Lidar Point Cloud Guided Monocular 3D Object Detection
AbstractMonocular 3D object detection is a challenging task in the self-driving and computer vision community. As a common practice, most previous works use manually annotated 3D box labels, where the annotating process is expensive. In this paper, we ...
- ArticleOctober 2022
DID-M3D: Decoupling Instance Depth for Monocular 3D Object Detection
AbstractMonocular 3D detection has drawn much attention from the community due to its low cost and setup simplicity. It takes an RGB image as input and predicts 3D boxes in the 3D space. The most challenging sub-task lies in the instance depth estimation. ...
- research-articleOctober 2022
Domain Reconstruction and Resampling for Robust Salient Object Detection
MM '22: Proceedings of the 30th ACM International Conference on MultimediaOctober 2022, Pages 5417–5426https://doi.org/10.1145/3503161.3547927Salient Object Detection (SOD) aims at detecting the salient objects covering the whole natural scene. However, one of the main problems in SOD is data bias. Natural scenes vary greatly, while each image in the SOD dataset contains a specific scene. It ...
- research-articleOctober 2022
Mitigating sensitive data exposure with adversarial learning for fairness recommendation systems
Neural Computing and Applications (NCAA), Volume 34, Issue 20Oct 2022, Pages 18097–18111https://doi.org/10.1007/s00521-022-07373-4AbstractFairness is an important research problem for recommendation systems, and unfair recommendation methods can lead to discrimination against users. Gender is a kind of sensitive feature, exposure sensitive feature can lead to unfair treatment of ...
- ArticleSeptember 2022
MGEDR: A Molecular Graph Encoder for Drug Recommendation
Natural Language Processing and Chinese ComputingSep 2022, Pages 98–109https://doi.org/10.1007/978-3-031-17189-5_8AbstractRecently, drug recommendation tasks have been widely accepted in intelligent healthcare. Most of the existing methods utilize patients’ electronic health records (EHRs) to achieve medical prediction. However, existing algorithms neglect the ...
- research-articleAugust 2022
Design of Surface Robot System
2022 IEEE International Conference on Mechatronics and Automation (ICMA)Aug 2022, Pages 116–121https://doi.org/10.1109/ICMA54519.2022.9856388At the present time, the level of aquatic pollution is rising rapidly. aquatic cleaning robots on the market are operated largely by individuals. Therefore, based on the ROS pattern, a combination robot was designed and its prototype model machine was ...
- research-articleAugust 2022
Self-supervised learning for fair recommender systems
- Haifeng Liu,
- Hongfei Lin,
- Wenqi Fan,
- Yuqi Ren,
- Bo Xu,
- Xiaokun Zhang,
- Dongzhen Wen,
- Nan Zhao,
- Yuan Lin,
- Liang Yang
Applied Soft Computing (APSC), Volume 125, Issue CAug 2022https://doi.org/10.1016/j.asoc.2022.109126AbstractData-driven recommender algorithms are widely used in many systems, such as e-commerce recommender systems and movie recommendation systems. However, these systems could be affected by data bias, which leads to unfair recommendations ...
Highlights- We develop a self-supervised learning framework named GRFRec for fair recommender system.