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Superposing Many Tickets into One: A Performance Booster for Sparse Neural Network Training



Lu Yin , Vlado Menkovski , Meng Fang , Tianjin Huang , Yulong Pei , Mykola Pechenizkiy , Decebal Constantin Mocanu , Shiwei Liu

* 17 pages, 5 figures, accepted by the 38th Conference on Uncertainty in Artificial Intelligence (UAI) 

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Phrase-level Textual Adversarial Attack with Label Preservation



Yibin Lei , Yu Cao , Dianqi Li , Tianyi Zhou , Meng Fang , Mykola Pechenizkiy

* NAACL-HLT 2022 Findings (Long), 9 pages + 2 pages references + 8 pages appendix 

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Survey on Fair Reinforcement Learning: Theory and Practice



Pratik Gajane , Akrati Saxena , Maryam Tavakol , George Fletcher , Mykola Pechenizkiy


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Does the End Justify the Means? On the Moral Justification of Fairness-Aware Machine Learning



Hilde Weerts , Lambèr Royakkers , Mykola Pechenizkiy


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The Impact of Batch Learning in Stochastic Linear Bandits



Danil Provodin , Pratik Gajane , Mykola Pechenizkiy , Maurits Kaptein

* arXiv admin note: substantial text overlap with arXiv:2111.02071 

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The Unreasonable Effectiveness of Random Pruning: Return of the Most Naive Baseline for Sparse Training



Shiwei Liu , Tianlong Chen , Xiaohan Chen , Li Shen , Decebal Constantin Mocanu , Zhangyang Wang , Mykola Pechenizkiy

* Published as a conference paper at ICLR 2022. Code is available at https://github.com/VITA-Group/Random_Pruning 

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Semantic-Based Few-Shot Learning by Interactive Psychometric Testing



Lu Yin , Vlado Menkovski , Yulong Pei , Mykola Pechenizkiy

* Accepted by AAAI 2022 Workshop on Interactive Machine Learning ([email protected]

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The Impact of Batch Learning in Stochastic Bandits



Danil Provodin , Pratik Gajane , Mykola Pechenizkiy , Maurits Kaptein

* To appear at the workshop on the Ecological Theory of Reinforcement Learning, NeurIPS 2021 

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Calibrated Adversarial Training



Tianjin Huang , Vlado Menkovski , Yulong Pei , Mykola Pechenizkiy

* ACML 2021 accepted,24 pages 

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Addressing the Stability-Plasticity Dilemma via Knowledge-Aware Continual Learning



Ghada Sokar , Decebal Constantin Mocanu , Mykola Pechenizkiy

* Preprint 

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