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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Henwood, S., Torcato Mordido, G. F., Savaria, Y., Anbil Parthipan, S. C., & Leduc-Primeau, F. (2024, October). Sharpness-Aware Minimization Scaled by Outlier Normalization for Robust DNNs on In-Memory Computing Accelerators [Paper]. 58th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA. External link
Chitsaz, K., Fournier, Q., Torcato Mordido, G. F., & Anbil Parthipan, S. C. (2024, November). Exploring Quantization for Efficient Pre-Training of Transformer Language Models [Paper]. Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), Miami, FL, USA. External link
Zayed, A., Torcato Mordido, G. F., Shabanian, S., Baldini, I., & Chandar, S. (2024, February). Fairness-Aware Structured Pruning in Transformers [Paper]. 38th AAAI Conference on Artificial Intelligence (AAAI 2024). Published in Proceedings of the AAAI Conference on Artificial Intelligence, 38(20). External link
Kern, J., Henwood, S., Torcato Mordido, G. F., Dupraz, E., Aissa-El-Bey, A., Savaria, Y., & Leduc-Primeau, F. (2024). Fast and Accurate Output Error Estimation for Memristor-Based Deep Neural Networks. IEEE Transactions on Signal Processing, 72, 1205-1218. External link
Torcato Mordido, G. F., Malviya, P., Baratin, A., & Anbil Parthipan, S. C. (2024, July). Lookbehind-SAM: k Steps Back, 1 Step Forward [Paper]. 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria. External link
Zayed, A., Torcato Mordido, G. F., Baldini, I., & Anbil Parthipan, S. C. (2024, August). Why Don't Prompt-Based Fairness Metrics Correlate? [Paper]. 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), Bangkok, Thailand. External link
Zayed, A., Parthasarathi, P., Torcato Mordido, G. F., Palangi, H., Shabanian, S., & Anbil Parthipan, S. C. (2023, February). Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness [Paper]. 37th AAAI Conference on Artificial Intelligence (AAAI 2023) and 35th Conference on Innovative Applications of Artificial Intelligence (IAAI 2023) and 13th Symposium on Educational Advances in Artificial Intelligence (EAAI 2023), Washington, DC, USA. External link
Kern, J., Henwood, S., Torcato Mordido, G. F., Dupraz, E., Aissa-El-Bey, A., Savaria, Y., & Leduc-Primeau, F. (2022, June). MemSE: Fast MSE Prediction for Noisy Memristor-Based DNN Accelerators [Paper]. IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS) - Intelligent Technology in the Post-Pandemic Era, Incheon, South Korea. External link
Zhang, Y., Savaria, Y., Zhao, S., Torcato Mordido, G. F., Sawan, M., & Leduc-Primeau, F. (2022, July). Tiny CNN for Seizure Prediction in Wearable Biomedical Devices [Paper]. 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2022), Glasgow, United Kingdom. External link
