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Published in Sensors (MDPI), 2013
In this paper, we propose and analyze a retransmission protocol named Cooperative-Hybrid Automatic Repeat reQuest (C-HARQ) for underwater acoustic sensor networks, which exploits both the reliability of cooperative ARQ (CARQ) and the efficiency of incremental redundancy-hybrid ARQ (IR-HARQ) using rate-compatible punctured convolution (RCPC) codes.
Recommended citation: Ghosh, Arindam, Jae-Won Lee, and Ho-Shin Cho. "Throughput and energy efficiency of a cooperative hybrid ARQ protocol for underwater acoustic sensor networks." Sensors 13.11 (2013): 15385-15408.
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Published in International Conference on Signal Processing and Communications (SPCOM), 2014
In this paper, accurate and analytically tractable symbol-error probability (SEP) expressions have been derived for a free-space optics (FSO) communication system that employs M-ary dual-ring star-quadrature amplitude modulation (QAM) and operates over atmospheric turbulent channels.
Recommended citation: Ghosh, Arindam, Gourab Ghatak, and Aniruddha Chandra. "SEP of dual-ring star-QAM over FSO channels with atmospheric turbulence." 2014 International Conference on Signal Processing and Communications (SPCOM). IEEE, 2014.
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Published in IEEE Communications Letters, 2017
In this paper, we present an approach to model the correlated interferences in Poisson Point Process (PPP) network using a correlation framework constructed using mixtures of random variables.
Recommended citation: Ghosh, Arindam. "Mixture-based modeling of spatially correlated interference in a Poisson field of interferers." IEEE Communications Letters 21.11 (2017): 2496-2499
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Published in IEEE Communications Letters, 2018
In this paper, we analytically derive the MRC outage probability for an arbitrary N by employing the mixture-based method of modeling the correlation in the interference powers.
Recommended citation: Ghosh, Arindam, and Harpreet S. Dhillon. "Performance analysis of MRC under spatially correlated interference using mixture-based method." IEEE Communications Letters 22.11 (2018): 2314-2317
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Published in EMNLP, 2021
In this paper, we explore the feasibility of using pretrained transformer models (BART) for summarizing doctor-patient conversations directly from transcripts.
Recommended citation: Zhang, Longxiang, Renato Negrinho, Arindam Ghosh, Vasudevan Jagannathan, Hamid Reza Hassanzadeh, Thomas Schaaf, and Matthew R. Gormley. "Leveraging Pretrained Models for Automatic Summarization of Doctor-Patient Conversations." In Findings of the Association for Computational Linguistics: EMNLP 2021, pp. 3693-3712. 2021.
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Published in Interspeech, 2022
This paper explores two techniques to leverage acoustic modeling data for large-vocabulary speech recognition to improve a purpose-built wake-word detector: transfer learning and knowledge distillation.
Recommended citation: Ghosh, A., Fuhs, M., Bagchi, D., Farahani, B., Woszczyna, M. (2022) Low-resource Low-footprint Wake-word Detection using Knowledge Distillation. Proc. Interspeech 2022, 3739-3743, doi: 10.21437/Interspeech.2022-529.
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Published in Advances in Neural Information Processing Systems 35, 2022
This paper proposes Adafocal training algorithm that produces better calibrated models without any significant loss in accuracy/performance.
Recommended citation: Ghosh, Arindam, Thomas Schaaf, and Matthew Gormley. “Adafocal: Calibration-aware adaptive focal loss.” Advances in Neural Information Processing Systems 35 (2022): 1583-1595.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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