Mlearning.ai

FEBRUARY 19, 2023

It combines techniques from computational linguistics, probabilistic modeling, deep learning to make computers intelligent enough to grasp the context and the intent of the language. GPT-3 is a successor to the earlier GPT-2 (released in Feb 2019) and GPT-1 (released in June 2018) models .

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NLP People

JANUARY 2, 2019

Hundreds of researchers, students, recruiters, and business professionals came to Brussels this November to learn about recent advances, and share their own findings, in computational linguistics and Natural Language Processing (NLP). 3-Is Automatic Post-Editing (APE) a Thing? 7-Have we Finally Solved Machine Translation?

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The Stanford AI Lab Blog

JANUARY 21, 2022

Deep learning has enabled improvements in the capabilities of robots on a range of problems such as grasping 1 and locomotion 2 in recent years. QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation. Conference on Robot Learning. ↩ Kumar, A., Kalashnikov, D., Quillen, D.,

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Sebastian Ruder

NOVEMBER 14, 2022

This post is partially based on a keynote I gave at the Deep Learning Indaba 2022. These include groups focusing on linguistic regions such as Masakhane for African languages, AmericasNLP for native American languages, IndoNLP for Indonesian languages, GhanaNLP and HausaNLP , among others. Vulić, I., & Søgaard, A.

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The Stanford AI Lab Blog

OCTOBER 13, 2021

Deep learning face attributes in the wild. In Proceedings of the IEEE International Conference on Computer Vision, pp. In Association for Computational Linguistics (ACL), pp. 1112–1122, 2018. ↩ Yonatan Giefman and Ran El-Yaniv. SelectiveNet: A deep neural network with an integrated reject option.

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Sebastian Ruder

JANUARY 24, 2022

Transactions of the Association for Computational Linguistics, 9, 978–994. Transactions of the Association for Computational Linguistics, 9, 570–585. CodeTrans: Towards Cracking the Language of Silicone’s Code Through Self-Supervised Deep Learning and High Performance Computing.

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ML Review

MARCH 5, 2019

vector: Probing sentence embeddings for linguistic properties. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (Vol. TACL, 5, 135–146. Conneau, A., Kruszewski, G., Barrault, L., & Baroni, M. What you can cram into a single $ &!#* 2126–2136). Dumais, S.

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