Publications

Francesco Tonolini, Nikolaos Aletras, Yunlong Jiao, Gabriella Kazai (2023). Robust Weak Supervision with Variational Auto-Encoders. In ICML.

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Yue Feng, Yunlong Jiao, Animesh Prasad, Nikolaos Aletras, Emine Yilmaz, Gabriella Kazai (2023). Schema-Guided User Satisfaction Modeling for Task-Oriented Dialogues. In ACL.

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Zhengxiang Shi, Francesco Tonolini, Nikolaos Aletras, Emine Yilmaz, Gabriella Kazai, Yunlong Jiao (2023). Rethinking Semi-supervised Learning with Language Models. In Findings of ACL.

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Fangyu Liu, Yunlong Jiao, Jordan Massiah, Emine Yilmaz, Serhii Havrylov (2022). Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations. In ICLR.

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Arushi Goel, Yunlong Jiao, Jordan Massiah (2022). PARS: Pseudo-Label Aware Robust Sample Selection for Learning with Noisy Labels. arXiv.

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Giorgio Giannone, Serhii Havrylov, Jordan Massiah, Emine Yilmaz, Yunlong Jiao (2021). Just Mix Once: Mixing Samples with Implicit Group Distribution. In NeurIPS Workshop on Distribution Shifts.

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Adam Gabrys, Yunlong Jiao, Viacheslav Klimkov, Daniel Korzekwa, Roberto Barra-Chicote (2021). Improving the expressiveness of neural vocoding with non-affine Normalizing Flows. In Interspeech.

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Yunlong Jiao, Adam Gabrys, Georgi Tinchev, Bartosz Putrycz, Daniel Korzekwa, Viacheslav Klimkov (2021). Universal Neural Vocoding with Parallel WaveNet. In ICASSP.

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Fabian Heinemann, Stefan Kobel, Sven Dahlmanns, Jean-Philippe Vert, Yunlong Jiao (2019). Failure State Prediction for Automated Analyzers for Analyzing a Biological Sample. US Patent App..

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Yunlong Jiao, Jean-Philippe Vert (2018). The Weighted Kendall and High-order Kernels for Permutations. In ICML.

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Yunlong Jiao, Jean-Philippe Vert (2018). The Kendall and Mallows Kernels for Permutations. IEEE TPAMI.

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Yunlong Jiao, Jean-Philippe Vert (2017). Network-based Wavelet Smoothing for Analysis of Genomic Data.

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Yunlong Jiao, Marta R Hidalgo, Cankut Cubuk, Alicia Amadoz, Jose Carbonell-Caballero, Jean-Philippe Vert, Joaquin Dopazo (2017). Signaling Pathway Activities Improve Prognosis for Breast Cancer. bioRxiv.

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Elsa Bernard, Yunlong Jiao, Erwan Scornet, Veronique Stoven, Thomas Walter, Jean-Philippe Vert (2017). Kernel Multitask Regression for Toxicogenetics. Molecular Informatics.

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Yunlong Jiao (2017). Rank-based Molecular Prognosis and Network-guided Biomarker Discovery for Breast Cancer. PhD Thesis.

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Yunlong Jiao, Anna Korba, Eric Sibony (2016). Controlling the distance to a Kemeny consensus without computing it. In ICML.

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Federica Eduati, Lara M Mangravite, Tao Wang, Hao Tang, J Christopher Bare, Ruili Huang, Thea Norman, Mike Kellen, Michael P Menden, Jichen Yang, Xiaowei Zhan, Rui Zhong, Guanghua Xiao, Menghang Xia, Nour Abdo, Oksana Kosyk, The NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration (2015). Prediction of human population responses to toxic compounds by a collaborative competition. Nature Biotechnology.

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Yunlong Jiao, Jean-Philippe Vert (2015). The Kendall and Mallows Kernels for Permutations. In ICML.

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