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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 Hits 1 – 20 of 24 1 Multilingual Neural Machine Translation:Can Linguistic Hierarchies Help? ... Saleh, Fahimeh; Buntine, Wray; Haffari, Gholamreza. - : arXiv, 2021 BASE Show details 2 Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data Selection ... Vu, Thuy-Trang; He, Xuanli; Phung, Dinh. - : arXiv, 2021 BASE Show details 3 Uncertainty-Aware Balancing for Multilingual and Multi-Domain Neural Machine Translation Training ... Wu, Minghao; Li, Yitong; Zhang, Meng. - : arXiv, 2021 BASE Show details 4 Cognition-aware Cognate Detection ... Kanojia, Diptesh; Sharma, Prashant; Ghodekar, Sayali. - : arXiv, 2021 BASE Show details 5 Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource Languages ... Kanojia, Diptesh; Dabre, Raj; Dewangan, Shubham. - : arXiv, 2021 BASE Show details 6 Learning Coupled Policies for Simultaneous Machine Translation using Imitation Learning ... Arthur, Philip; Cohn, Trevor; Haffari, Gholamreza. - : arXiv, 2020 BASE Show details 7 SummPip: Unsupervised Multi-Document Summarization with Sentence Graph Compression ... Zhao, Jinming; Liu, Ming; Gao, Longxiang. - : arXiv, 2020 BASE Show details 8 Leveraging Discourse Rewards for Document-Level Neural Machine Translation ... Unanue, Inigo Jauregi; Esmaili, Nazanin; Haffari, Gholamreza. - : arXiv, 2020 BASE Show details 9 Collective Wisdom: Improving Low-resource Neural Machine Translation using Adaptive Knowledge Distillation ... Saleh, Fahimeh; Buntine, Wray; Haffari, Gholamreza. - : arXiv, 2020 BASE Show details 10 Learning to Multi-Task Learn for Better Neural Machine Translation ... Zaremoodi, Poorya; Haffari, Gholamreza. - : arXiv, 2020 BASE Show details 11 Learning how to active learn by dreaming Liu, Ming; Phung, Dinh; Haffari, Gholamreza. - : Association for Computational Linguistics, 2019 BASE Show details 12 Contextual Neural Model for Translating Bilingual Multi-Speaker Conversations ... Maruf, Sameen; Martins, André F. T.; Haffari, Gholamreza. - : arXiv, 2018 BASE Show details 13 Sequence to Sequence Mixture Model for Diverse Machine Translation ... He, Xuanli; Haffari, Gholamreza; Norouzi, Mohammad. - : arXiv, 2018 BASE Show details 14 Learning how to actively learn: a deep imitation learning approach Buntine, Wray; Haffari, Gholamreza; Liu, Ming. - : Association for Computational Linguistics, 2018 BASE Show details 15 Learning to actively learn neural machine translation Haffari, Gholamreza; Buntine, Wray; Liu, Ming. - : Association for Computational Linguistics, 2018 BASE Show details 16 Neural Machine Translation for Bilingually Scarce Scenarios: A Deep Multi-task Learning Approach ... Zaremoodi, Poorya; Haffari, Gholamreza. - : arXiv, 2018 BASE Show details 17 Phonemic transcription of low-resource tonal languages Adams, Oliver; Cohn, Trevor; Neubig, Graham... In: ISSN: 1834-7037 ; Australasian Language Technology Association Workshop 2017 ; https://halshs.archives-ouvertes.fr/halshs-01656683 ; Australasian Language Technology Association Workshop 2017, Dec 2017, Brisbane, Australia. pp.53-60 (2017) BASE Show details 18 Towards Decoding as Continuous Optimization in Neural Machine Translation ... Hoang, Cong Duy Vu; Haffari, Gholamreza; Cohn, Trevor. - : arXiv, 2017 Abstract: We propose a novel decoding approach for neural machine translation (NMT) based on continuous optimisation. We convert decoding - basically a discrete optimization problem - into a continuous optimization problem. The resulting constrained continuous optimisation problem is then tackled using gradient-based methods. Our powerful decoding framework enables decoding intractable models such as the intersection of left-to-right and right-to-left (bidirectional) as well as source-to-target and target-to-source (bilingual) NMT models. Our empirical results show that our decoding framework is effective, and leads to substantial improvements in translations generated from the intersected models where the typical greedy or beam search is not feasible. We also compare our framework against reranking, and analyse its advantages and disadvantages. ... : EMNLP 2017 Camera Ready Paper ... Keyword: Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/1701.02854 https://dx.doi.org/10.48550/arxiv.1701.02854 BASE Hide details 19 Leveraging linguistic resources for improving neural text classification Liu, Ming; Haffari, Gholamreza; Buntine, Wray. - : Australian Language Technology Association, 2017 BASE Show details 20 Phonemic transcription of low-resource tonal languages Adams, Oliver; Cohn, Trevor; Neubig, Graham... In: ISSN: 1834-7037 ; Australasian Language Technology Association Workshop 2017 ; https://halshs.archives-ouvertes.fr/halshs-01656683 ; Australasian Language Technology Association Workshop 2017, Dec 2017, Brisbane, Australia. pp.53-60 (2017) BASE Show details Page: 1 2

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