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ORCIDIEEE Transactions on Emerging Topics in Computing, Volume 12
Volume 12, Number 1, January - March 2024
- Alberto Bosio
, Ronald F. DeMara, Deliang Fan, Nima TaheriNejad:
Guest Editorial IEEE Transactions on Emerging Topics in Special Section on Emerging In-Memory Computing Architectures and Applications. 4-6 - Ben Perach, Ronny Ronen, Benny Kimelfeld, Shahar Kvatinsky:
Understanding Bulk-Bitwise Processing In-Memory Through Database Analytics. 7-22 - Yandong Luo, Johan Vanderhaegen, Oleg Rybakov, Martin Kraemer, Niel Warren, Shimeng Yu:
A FeFET-Based ADC Offset Robust Compute-In-Memory Architecture for Streaming Keyword Spotting (KWS). 23-34 - Marco Paul E. Apolinario, Adarsh Kumar Kosta, Utkarsh Saxena, Kaushik Roy:
Hardware/Software Co-Design With ADC-Less In-Memory Computing Hardware for Spiking Neural Networks. 35-47 - Khakim Akhunov, Kasim Sinan Yildirim:
CRAM-Based Acceleration for Intermittent Computing of Parallelizable Tasks. 48-59 - Purab Ranjan Sutradhar, Sathwika Bavikadi, Sai Manoj Pudukotai Dinakarrao, Mark A. Indovina, Amlan Ganguly:
3DL-PIM: A Look-Up Table Oriented Programmable Processing in Memory Architecture Based on the 3-D Stacked Memory for Data-Intensive Applications. 60-72 - Shaahin Angizi, Mehrdad Morsali, Sepehr Tabrizchi, Arman Roohi:
A Near-Sensor Processing Accelerator for Approximate Local Binary Pattern Networks. 73-83 - Yiming Chen, Mingyen Lee, Guohao Dai, Mufeng Zhou, Nagadastagiri Challapalle, Tianyi Wang, Yao Yu, Yongpan Liu, Yu Wang, Huazhong Yang, Vijaykrishnan Narayanan, Xueqing Li:
GRAPHIC: Gather and Process Harmoniously in the Cache With High Parallelism and Flexibility. 84-96 - Jia-Le Cui, Yanan Guo, Juntong Chen, Bo Liu, Hao Cai:
Sparsity-Oriented MRAM-Centric Computing for Efficient Neural Network Inference. 97-108 - Ziyu Wang, Fan-Hsuan Meng, Yongmo Park, Jason K. Eshraghian, Wei D. Lu:
Side-Channel Attack Analysis on In-Memory Computing Architectures. 109-121 - Alessandro D'Amelio, Jianyi Lin, Jean-Yves Ramel, Raffaella Lanzarotti:
Guest Editorial Emerging Trends and Advances in Graph-Based Methods and Applications. 122-125 - Meixia He, Jianrui Chen, Maoguo Gong, Zhongshi Shao:
HDGCN: Dual-Channel Graph Convolutional Network With Higher-Order Information for Robust Feature Learning. 126-138 - Xiaolin Li, Qikui Xu, Zhenyu Xu, Hongyan Zhang, Li Xu:
Graph Reconfigurable Pooling for Graph Representation Learning. 139-149 - Yong-Min Shin, Cong Tran, Won-Yong Shin, Xin Cao:
Edgeless-GNN: Unsupervised Representation Learning for Edgeless Nodes. 150-162 - Bo-Wei Zhao, Lei Wang, Peng-Wei Hu, Leon Wong, Xiao-Rui Su, Bao-Quan Wang, Zhu-Hong You, Lun Hu:
Fusing Higher and Lower-Order Biological Information for Drug Repositioning via Graph Representation Learning. 163-176 - Davide Bacciu, Federico Errica, Alessio Gravina, Lorenzo Madeddu, Marco Podda, Giovanni Stilo:
Deep Graph Networks for Drug Repurposing With Multi-Protein Targets. 177-189 - Binon Teji, Swarup Roy, Devendra Singh Dhami, Dinabandhu Bhandari, Pietro Hiram Guzzi:
Graph Embedding Techniques for Predicting Missing Links in Biological Networks: An Empirical Evaluation. 190-201 - Benjamin Filtjens, Bart Vanrumste, Peter Slaets:
Skeleton-Based Action Segmentation With Multi-Stage Spatial-Temporal Graph Convolutional Neural Networks. 202-212 - Federico Becattini, Federico Maria Teotini, Alberto Del Bimbo:
Transformer-Based Graph Neural Networks for Outfit Generation. 213-223 - Alejandro Álvarez-Ayllón, Manuel Palomo-Duarte, Juan Manuel Dodero:
PresQ: Discovery of Multidimensional Equally-Distributed Dependencies via Quasi-Cliques on Hypergraphs. 224-239 - Feng Xia, Xin Chen, Shuo Yu, Mingliang Hou, Mujie Liu, Linlin You:
Coupled Attention Networks for Multivariate Time Series Anomaly Detection. 240-253 - Dongbo Zhou, Hongwei Yu, Jie Yu, Shuai Zhao, Wenhui Xu, Qianqian Li, Fengyin Cai:
MFDS-STGCN: Predicting the Behaviors of College Students With Fine-Grained Spatial-Temporal Activities Data. 254-265 - Jinguang Han, Patrick Schaumont, Willy Susilo:
Guest Editorial IEEE Transactions on Emerging Topics in Computing Special Section on Advances in Emerging Privacy-Preserving Computing. 266-268 - Aditya Pribadi Kalapaaking, Ibrahim Khalil, Xun Yi:
Blockchain-Based Federated Learning With SMPC Model Verification Against Poisoning Attack for Healthcare Systems. 269-280 - Yaoqi Yang, Bangning Zhang, Daoxing Guo, Renhui Xu, Chunhua Su, Weizheng Wang:
Age of Information Optimization for Privacy-Preserving Mobile Crowdsensing. 281-292 - Amir Fathalizadeh, Vahideh Moghtadaiee, Mina Alishahi:
Indoor Geo-Indistinguishability: Adopting Differential Privacy for Indoor Location Data Protection. 293-306 - Fangwei Wang, Meiyun Xie, Zhiyuan Tan, Qingru Li, Changguang Wang:
Preserving Differential Privacy in Deep Learning Based on Feature Relevance Region Segmentation. 307-315 - Yue Zhang, Youwen Zhu, Yuqian Zhou, Jiabin Yuan:
Frequency Estimation Mechanisms Under ϵδ-Utility-Optimized Local Differential Privacy. 316-327 - Kyung Hyun Han, Wai-Kong Lee, Angshuman Karmakar, Jose Maria Bermudo Mera, Seong Oun Hwang:
cuFE: High Performance Privacy Preserving Support Vector Machine With Inner-Product Functional Encryption. 328-343 - Supriya Adhikary, Angshuman Karmakar:
A Fast RLWE-Based IPFE Library and its Application to Privacy-Preserving Biometric Authentication. 344-356 - Irina Arévalo, Jose L. Salmeron:
A Chaotic Maps-Based Privacy-Preserving Distributed Deep Learning for Incomplete and Non-IID Datasets. 357-367 - Abdul Majeed, Safiullah Khan, Seong Oun Hwang:
Towards Optimization of Privacy-Utility Trade-Off Using Similarity and Diversity Based Clustering. 368-385 - Mathias Brossard, Guilhem Bryant, Basma El Gaabouri, Xinxin Fan, Alexandre Ferreira, Edmund Grimley-Evans, Christopher Haster, Evan Johnson, Derek Miller, Fan Mo, Dominic P. Mulligan, Nick Spinale, Eric Van Hensbergen, Hugo J. M. Vincent, Shale Xiong:
Private Delegated Computations Using Strong Isolation. 386-398
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