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Melissa Ailem
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2020 – today
- 2024
- [c12]Charlotte Siska, Katerina Marazopoulou, Melissa Ailem, James Bono:
Examining the robustness of LLM evaluation to the distributional assumptions of benchmarks. ACL (1) 2024: 10406-10421 - [i5]Melissa Ailem, Katerina Marazopoulou, Charlotte Siska, James Bono:
Examining the robustness of LLM evaluation to the distributional assumptions of benchmarks. CoRR abs/2404.16966 (2024) - 2022
- [j5]Mickael Febrissy, Aghiles Salah, Melissa Ailem, Mohamed Nadif:
Improving NMF clustering by leveraging contextual relationships among words. Neurocomputing 495: 105-117 (2022) - [c11]Melissa Ailem, Jingshu Liu, Raheel Qader:
Encouraging Neural Machine Translation to Satisfy Terminology Constraints. TALN-RECITAL 2022: 446 - [c10]Melissa Ailem, Jingshu Liu, Jean-Gabriel Barthelemy, Raheel Qader:
Lingua Custodia's Participation at the WMT 2022 Word-Level Auto-completion Shared Task. WMT 2022: 1170-1175 - 2021
- [c9]Melissa Ailem, Jingshu Liu, Raheel Qader:
Encouraging Neural Machine Translation to Satisfy Terminology Constraints. ACL/IJCNLP (Findings) 2021: 1450-1455 - [c8]Melissa Ailem, Jingshu Liu, Raheel Qader:
Lingua Custodia's Participation at the WMT 2021 Machine Translation Using Terminologies Shared Task. WMT@EMNLP 2021: 799-803 - [i4]Melissa Ailem, Jingshu Liu, Raheel Qader:
Encouraging Neural Machine Translation to Satisfy Terminology Constraints. CoRR abs/2106.03730 (2021) - [i3]Melissa Ailem, Jingshu Liu, Raheel Qader:
Lingua Custodia's participation at the WMT 2021 Machine Translation using Terminologies shared task. CoRR abs/2111.02120 (2021) - 2020
- [c7]Yiming Yan, Melissa Ailem, Fei Sha:
Amortized Inference of Variational Bounds for Learning Noisy-OR. AISTATS 2020: 3632-3641
2010 – 2019
- 2019
- [i2]Yiming Yan, Melissa Ailem, Fei Sha:
Amortized Inference of Variational Bounds for Learning Noisy-OR. CoRR abs/1906.02428 (2019) - [i1]Melissa Ailem, Bowen Zhang, Fei Sha:
Topic Augmented Generator for Abstractive Summarization. CoRR abs/1908.07026 (2019) - 2018
- [c6]Aghiles Salah, Melissa Ailem, Mohamed Nadif:
Word Co-Occurrence Regularized Non-Negative Matrix Tri-Factorization for Text Data Co-Clustering. AAAI 2018: 3992-3999 - [c5]Melissa Ailem, Bowen Zhang, Aurélien Bellet, Pascal Denis, Fei Sha:
A Probabilistic Model for Joint Learning of Word Embeddings from Texts and Images. EMNLP 2018: 1478-1487 - [c4]Melissa Ailem, François Role, Mohamed Nadif
:
Sparse Poisson Latent Block Model for Document Clustering (Extended Abstract). ICDE 2018: 1743-1744 - 2017
- [j4]Melissa Ailem, François Role, Mohamed Nadif
Model-based co-clustering for the effective handling of sparse data. Pattern Recognit. 72: 108-122 (2017) - [j3]Melissa Ailem, François Role, Mohamed Nadif:
Sparse Poisson Latent Block Model for Document Clustering. IEEE Trans. Knowl. Data Eng. 29(7): 1563-1576 (2017) - [c3]Aghiles Salah, Melissa Ailem, Mohamed Nadif:
A Way to Boost Semi-NMF for Document Clustering. CIKM 2017: 2275-2278 - [c2]Melissa Ailem, Aghiles Salah, Mohamed Nadif:
Non-negative Matrix Factorization Meets Word Embedding. SIGIR 2017: 1081-1084 - 2016
- [j2]Melissa Ailem, François Role, Mohamed Nadif, Florence Demenais
Unsupervised text mining for assessing and augmenting GWAS results. J. Biomed. Informatics 60: 252-259 (2016) - [j1]Melissa Ailem, François Role, Mohamed Nadif:
Graph modularity maximization as an effective method for co-clustering text data. Knowl. Based Syst. 109: 160-173 (2016) - 2015
- [c1]Melissa Ailem, François Role, Mohamed Nadif:
Co-clustering Document-term Matrices by Direct Maximization of Graph Modularity. CIKM 2015: 1807-1810
Coauthor Index
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