Linking pages
- Challenges in Few-shot learning; 2019 predictions; JAX; Explainable models; MT reading list; Foundations of ML; AI Index 2018; Karen Sparck Jones; Analysis methods survey; ICLR 2019 rejects | Revue http://newsletter.ruder.io/issues/challenges-in-few-shot-learning-2019-predictions-jax-explainable-models-mt-reading-list-foundations-of-ml-ai-index-2018-karen-sparck-jones-analysis-methods-survey-iclr-2019-rejects-151442 0 comments
- GitHub - ujjwalkarn/Machine-Learning-Tutorials: machine learning and deep learning tutorials, articles and other resources https://github.com/ujjwalkarn/Machine-Learning-Tutorials 0 comments
Linked pages
- [1609.08144] Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation http://arxiv.org/abs/1609.08144 97 comments
- Attention is All you Need https://papers.nips.cc/paper/7181-attention-is-all-you-need 30 comments
- [1810.04805] BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding https://arxiv.org/abs/1810.04805 25 comments
- [1906.06718] Neural Decipherment via Minimum-Cost Flow: from Ugaritic to Linear B https://arxiv.org/abs/1906.06718 22 comments
- [1906.08237] XLNet: Generalized Autoregressive Pretraining for Language Understanding https://arxiv.org/abs/1906.08237 15 comments
- [1703.01619] Neural Machine Translation and Sequence-to-sequence Models: A Tutorial https://arxiv.org/abs/1703.01619 6 comments
- [1611.04558] Google's Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation https://arxiv.org/abs/1611.04558 2 comments
- https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf 1 comment
- https://www.microsoft.com/en-us/research/uploads/prod/2018/03/final-achieving-human.pdf 1 comment
- [1309.4168] Exploiting Similarities among Languages for Machine Translation http://arxiv.org/abs/1309.4168 1 comment
- [1908.05672] Towards Making the Most of BERT in Neural Machine Translation https://arxiv.org/abs/1908.05672 0 comments
- [1908.05731] Simple and Effective Noisy Channel Modeling for Neural Machine Translation https://arxiv.org/abs/1908.05731 0 comments
- [1904.09324] Mask-Predict: Parallel Decoding of Conditional Masked Language Models https://arxiv.org/abs/1904.09324 0 comments
- [1909.00040] Handling Syntactic Divergence in Low-resource Machine Translation https://arxiv.org/abs/1909.00040 0 comments
- [1908.11782] Latent Part-of-Speech Sequences for Neural Machine Translation https://arxiv.org/abs/1908.11782 0 comments
- [1711.02281] Non-Autoregressive Neural Machine Translation https://arxiv.org/abs/1711.02281 0 comments
- [1908.11020] Regularized Context Gates on Transformer for Machine Translation https://arxiv.org/abs/1908.11020 0 comments
- [1909.02074] Jointly Learning to Align and Translate with Transformer Models https://arxiv.org/abs/1909.02074 0 comments
- [1909.02197] Investigating Multilingual NMT Representations at Scale https://arxiv.org/abs/1909.02197 0 comments
- [1412.6980] Adam: A Method for Stochastic Optimization http://arxiv.org/abs/1412.6980 0 comments