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In task-oriented communications, most existing work designed the physical-layer communication modules and learning based codecs with distinct objectives: learning is targeted at accurate execution of specific tasks, while communication aims at optimizing conventional communication metrics, such as throughput maximization, delay minimization, or bit error rate minimization.
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D. Tse and P. Viswanath, Fundamentals of wireless communication . Cambridge univ. press, 2005
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Y. Ma, H. Derksen, W. Hong, and J. Wright, “Segmentation of multivariate mixed data via lossy data coding and compression,” IEEE Trans. Pattern Anal. Mach. Intell. , vol. 29, no. 9, pp. 1546–1562, 2007
2007
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A. Krizhevsky, G. Hinton et al. , “Learning multiple layers of features from tiny images,” 2009. [Online]. Available: http://www.cs.utoronto.ca/~kriz/learning-features-2009-TR.pdf
2009
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Q. Shi, M. Razaviyayn, Z.-Q. Luo, and C. He, “An iteratively weighted MMSE approach to distributed sum-utility maximization for a MIMO interfering broadcast channel,” IEEE Trans. Signal Process. , vol. 59, no. 9, pp. 4331–4340, 2011
2011
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2012
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H. Su, S. Maji, E. Kalogerakis, and E. Learned-Miller, “Multi-view convolutional neural networks for 3D shape recognition,” in Proc. IEEE Int. Conf. Comput. Vis. , 2015, pp. 945–953
2015
Earlier work this paper cites.
K. Simonyan and A. Zisserman, “Very deep convolutional networks for large-scale image recognition,” in Proc. Int. Conf. Learn. Repr. , 2015, pp. 1–14
2015
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K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. , 2016, pp. 770–778
2016
Earlier work this paper cites.
C. Rubino, M. Crocco, and A. Del Bue, “3D object localisation from multi-view image detections,” IEEE Trans. Pattern Anal. Mach. Intell. , vol. 40, no. 6, pp. 1281–1294, 2018
2018
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Y. Zhou and L. Shao, “Viewpoint-aware attentive multi-view inference for vehicle re-identification,” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. , 2018, pp. 6489–6498
2018
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K. Shen and W. Yu, “Fractional programming for communication systems-part I: Power control and beamforming,” IEEE Trans. Signal Process. , vol. 66, no. 10, pp. 2616–2630, 2018
2018
Cited alongside, same era.
K. B. Letaief, W. Chen, Y. Shi, J. Zhang, and Y.-J. A. Zhang, “The roadmap to 6G: AI empowered wireless networks,” IEEE Commun. Mag. , vol. 57, no. 8, pp. 84–90, 2019
2019
Cited alongside, same era.
E. Bourtsoulatze, D. Burth Kurka, and D. Gündüz, “Deep joint source-channel coding for wireless image transmission,” IEEE Trans. Cogn. Commun. Netw. , vol. 5, no. 3, pp. 567–579, 2019
2019
Cited alongside, same era.
W. Saad, M. Bennis, and M. Chen, “A vision of 6G wireless systems: Applications, trends, technologies, and open research problems,” IEEE Netw. , vol. 34, no. 3, pp. 134–142, 2020
2020
Cited alongside, same era.
I. E. Aguerri and A. Zaidi, “Distributed variational representation learning,” IEEE Trans. Pattern Anal. Mach. Intell. , vol. 43, no. 1, pp. 120–138, 2021
2021
Later among the works it cites.
K. B. Letaief, Y. Shi, J. Lu, and J. Lu, “Edge artificial intelligence for 6G: Vision, enabling technologies, and applications,” IEEE J. Sel. Areas Commun. , vol. 40, no. 1, pp. 5–36, 2022
2022
Later among the works it cites.
J. Shao, Y. Mao, and J. Zhang, “Learning task-oriented communication for edge inference: An information bottleneck approach,” IEEE J. Sel. Areas Commun. , vol. 40, no. 1, pp. 197–211, 2022
2022
Later among the works it cites.
H. Xie, Z. Qin, X. Tao, and K. B. Letaief, “Task-oriented multi-user semantic communications,” IEEE J. Sel. Areas Commun. , vol. 40, no. 9, pp. 2584–2597, 2022
2022
Later among the works it cites.
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J. Shao and J. Zhang, “Bottlenet++: An end-to-end approach for feature compression in device-edge co-inference systems,” in Proc. IEEE Int. Conf. Commun. Workshops , 2020, pp. 1–6
2020
Cited alongside, same era.
Y. Yu, K. H. R. Chan, C. You, C. Song, and Y. Ma, “Learning diverse and discriminative representations via the principle of maximal coding rate reduction,” in Proc. Adv. Neural Inf. Process. Syst. , vol. 33, 2020, pp. 9422–9434
2020
Cited alongside, same era.
Q. Lan, D. Wen, Z. Zhang, Q. Zeng, X. Chen, P. Popovski, and K. Huang, “What is semantic communication? A view on conveying meaning in the era of machine intelligence,” J. Commun. Inf. Netw. , vol. 6, no. 4, pp. 336–371, 2021
2021
Cited alongside, same era.
M. Jankowski, D. Gündüz, and K. Mikolajczyk, “Wireless image retrieval at the edge,” IEEE J. Sel. Areas Commun. , vol. 39, no. 1, pp. 89–100, 2021
2021
Cited alongside, same era.
Z. Weng and Z. Qin, “Semantic communication systems for speech transmission,” IEEE J. Sel. Areas Commun. , vol. 39, no. 8, pp. 2434–2444, 2021
2021
Cited alongside, same era.
H. Xie, Z. Qin, G. Y. Li, and B.-H. Juang, “Deep learning enabled semantic communication systems,” IEEE Trans. Signal Process. , vol. 69, pp. 2663–2675, 2021
2021
Cited alongside, same era.
Y. Zheng, R. Shao, Y. Zhang, T. Yu, Z. Zheng, Q. Dai, and Y. Liu, “Deepmulticap: Performance capture of multiple characters using sparse multiview cameras,” in Proc. IEEE Int. Conf. Comput. Vis. , 2021, pp. 6219–6229
2021
Cited alongside, same era.
N. Shlezinger, E. Farhan, H. Morgenstern, and Y. C. Eldar, “Collaborative inference via ensembles on the edge,” in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process. , 2021, pp. 8478–8482
2021
Cited alongside, same era.
2022
Later among the works it cites.
X. Luo, R. Gao, H.-H. Chen, S. Chen, Q. Guo, and P. N. Suganthan, “Multi-modal and multi-user semantic communications for channel-level information fusion,” IEEE Wireless Commun. , pp. 1–18, 2022
2022
Later among the works it cites.
K. H. R. Chan, Y. Yu, C. You, H. Qi, J. Wright, and Y. Ma, “Redunet: A white-box deep network from the principle of maximizing rate reduction,” J. Mach. Learn. Res. , vol. 23, no. 1, pp. 4907–5009, 2022
2022
Later among the works it cites.
D. Gündüz, Z. Qin, I. E. Aguerri, H. S. Dhillon, Z. Yang, A. Yener, K. K. Wong, and C.-B. Chae, “Beyond transmitting bits: Context, semantics, and task-oriented communications,” IEEE J. Sel. Areas Commun. , vol. 41, no. 1, pp. 5–41, 2023
2023
Closest in time.
W. Yang, H. Du, Z. Q. Liew, W. Y. B. Lim, Z. Xiong, D. Niyato, X. Chi, X. Shen, and C. Miao, “Semantic communications for future internet: Fundamentals, applications, and challenges,” IEEE Commun. Surveys Tuts. , vol. 25, no. 1, pp. 213–250, 2023
2023
Closest in time.
——, “Task-oriented communication for multidevice cooperative edge inference,” IEEE Trans. Wireless Commun. , vol. 22, no. 1, pp. 73–87, 2023
2023
Closest in time.
H. Du, J. Wang, D. Niyato, J. Kang, Z. Xiong, J. Zhang, and X. Shen, “Semantic communications for wireless sensing: RIS-aided encoding and self-supervised decoding,” IEEE J. Sel. Areas Commun. , vol. 41, no. 8, pp. 2547–2562, 2023
2023
Closest in time.
P. Jiang, C.-K. Wen, S. Jin, and G. Y. Li, “Wireless semantic transmission via revising modules in conventional communications,” IEEE Wireless Commun. , vol. 30, no. 3, pp. 28–34, 2023
2023
Closest in time.
W. F. Lo, N. Mital, H. Wu, and D. Gündüz, “Collaborative semantic communication for edge inference,” IEEE Wireless Commun. Lett. , vol. 12, no. 7, pp. 1125–1129, 2023
2023
Closest in time.