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  1. 10 ML & NLP Research Highlights of 2019
  2. 10 ML & NLP Research Highlights of 2019
  3. Unsupervised Cross-lingual Representation Learning
  4. The State of Transfer Learning in NLP
  5. EurNLP
  6. NAACL 2019 Highlights
  7. Neural Transfer Learning for Natural Language Processing (PhD thesis)
  8. AAAI 2019 Highlights: Dialogue, reproducibility, and more
  9. The 4 Biggest Open Problems in NLP
  10. 10 Exciting Ideas of 2018 in NLP
  11. EMNLP 2018 Highlights: Inductive bias, cross-lingual learning, and more
  12. HackerNoon Interview
  13. A Review of the Neural History of Natural Language Processing
  14. ACL 2018 Highlights: Understanding Representations and Evaluation in More Challenging Settings
  15. NLP's ImageNet moment has arrived
  16. Tracking the Progress in Natural Language Processing
  17. Highlights of NAACL-HLT 2018: Generalization, Test-of-time, and Dialogue Systems
  18. An overview of proxy-label approaches for semi-supervised learning
  19. AI helps us sift for SETI signals
  20. Frequently asked questions (FAQ)
  21. Word embeddings in 2017: Trends and future directions
  22. A Review of the Neural History of Natural Language Processing
  23. Multi-Task Learning Objectives for Natural Language Processing
  24. HackerNoon Interview
  25. A Review of the Neural History of Natural Language Processing
  26. ACL 2018 Highlights: Understanding Representations and Evaluation in More Challenging Settings
  27. A Review of the Neural History of Natural Language Processing
  28. A Review of the Recent History of Natural Language Processing
  29. A Review of the Recent History of Natural Language Processing
  30. An overview of proxy-label approaches for semi-supervised learning
  31. ACL 2018 Highlights: Understanding Representations and Evaluation in More Challenging Settings
  32. NLP's ImageNet moment has arrived
  33. NLP's ImageNet moment has arrived
  34. Highlights of EMNLP 2017: Exciting datasets, return of the clusters, and more
  35. NLP's ImageNet moment has arrived
  36. Tracking the Progress in Natural Language Processing
  37. Highlights of NAACL-HLT 2018: Generalization, Test-of-time, and Dialogue Systems
  38. An overview of proxy-label approaches for semi-supervised learning
  39. Text Classification with TensorFlow Estimators
  40. Requests for Research
  41. Optimization for Deep Learning Highlights in 2017
  42. Word embeddings in 2017: Trends and future directions
  43. Multi-Task Learning Objectives for Natural Language Processing
  44. Highlights of EMNLP 2017: Exciting datasets, return of the clusters, and more
  45. Frequently asked questions (FAQ)
  46. Learning to select data for transfer learning
  47. Deep Learning for NLP Best Practices
  48. An Overview of Multi-Task Learning in Deep Neural Networks
  49. Transfer Learning - Machine Learning's Next Frontier
  50. Highlights of NIPS 2016: Adversarial learning, Meta-learning, and more
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