NLP People

JUNE 5, 2018

DeepL DeepL is a Cologne-based startup that utilises deep neural networks to build state-of-the-art machine translation service. The company utilises algorithms for targeted data collection and semantic analysis to extract fine-grained information from various types of customer feedback and market opinions.

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Bugra Akyildiz

JULY 16, 2023

Natural language processing (NLP) or computational linguistics is one of the most important technologies of the information age. Through lectures, assignments and a final project, students will learn the necessary skills to design, implement, and understand their own neural network models, using the Pytorch framework.

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Applied Data Science

DECEMBER 23, 2022

Dall-e , and pre-2022 tools in general, attributed their success either to the use of the Transformer or Generative Adversarial Networks. The former is a powerful architecture for artificial neural networks that was originally introduced for language tasks (you’ve probably heard of GPT-3 ?) Who should I follow?

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John Snow Labs

DECEMBER 26, 2023

Sentiment Analysis Using Simplified Long Short-term Memory Recurrent Neural Networks. The 49th Annual Meeting of the Association for Computational Linguistics (ACL 2011). abs/2005.03993 Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts.

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Defined.ai blog

AUGUST 3, 2023

Machine translation is a subfield of computational linguistics that uses software to translate text or speech from one language to another. The latest and most advanced is NMT , which utilizes artificial neural networks to predict the likelihood of a sequence of words appearing in a text, typically in the form of sentences.

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The Stanford AI Lab Blog

OCTOBER 13, 2021

In Proceedings of the IEEE International Conference on Computer Vision, pp. Distributionally robust neural networks for group shifts: On the importance of regularization for worst-case generalization. In Association for Computational Linguistics (ACL), pp. Selective classification for deep neural networks.

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Sebastian Ruder

FEBRUARY 23, 2023

Computation Function We consider a neural network $f_theta$ as a composition of functions $f_{theta_1} odot f_{theta_2} odot ldots odot f_{theta_l}$, each with their own set of parameters $theta_i$. d) Hypernetwork: A small separate neural network generates modular parameters conditioned on metadata.

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Sebastian Ruder

AUGUST 18, 2019

This goes back to layer-wise training of early deep neural networks ( Hinton et al., Instead, we train layers individually to give them time to adapt to the new task and data. 2006 ; Bengio et al., Recent approaches ( Felbo et al., 2017 ; Howard and Ruder, 2018 ; Chronopoulou et al.,

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Explosion

MAY 8, 2016

We’ve since released spaCy v2.0 , which comes with new convolutional neural network models for German and other languages. In the same way that a physicist might assume a frictionless surface or a spherical cow , sometimes it’s useful for computational linguists to assume projective trees and context-free grammars.

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Heartbeat

FEBRUARY 8, 2023

Natural Language Processing (NLP) plays a crucial role in advancing research in various fields, such as computational linguistics, computer science, and artificial intelligence. C++’s main advantage is its speed, which allows it to do complex computations more quickly, which is vital for AI development.

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Marek Rei

NOVEMBER 4, 2024

Linguistic Parameters of Spontaneous Speech for Identifying Mild Cognitive Impairment and Alzheimer Disease Veronika Vincze, Martina Katalin Szabó, Ildikó Hoffmann, László Tóth, Magdolna Pákáski, János Kálmán, Gábor Gosztolya. Computational Linguistics 2022. University of Szeged.

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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. Skillful Twelve Hour Precipitation Forecasts using Large Context Neural Networks, 1–34. link] ↩︎ Hendricks, L. Schneider, R.,

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Sebastian Ruder

JUNE 6, 2022

The initiative focuses on making Computational Linguistics (CL) research accessible in 60 languages and across all modalities, including text/speech/sign language translation, closed captioning, and dubbing. Another useful aspect of the initiative is the curation of the most common CL terms and their translation into 60 languages.

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The MLOps Blog

JANUARY 25, 2023

Sentiment analysis, commonly referred to as opinion mining/sentiment classification, is the technique of identifying and extracting subjective information from source materials using computational linguistics , text analysis , and natural language processing.

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Explosion

DECEMBER 17, 2013

It would be relatively easy to provide a beam-search version of spaCy…But, I think the gap in accuracy will continue to close, especially given advances in neural network learning. It is much faster than the Redshift parser (my research system), but less accurate. Syntactic Processing Using the Generalized Perceptron and Beam Search.

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Mlearning.ai

FEBRUARY 6, 2023

Classifiers based on neural networks are known to be poorly calibrated outside of their training data [3]. 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics. [7] 57th Annual Meeting of the Association for Computational Linguistics [9] C. Weigreffe, Y.

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NLP People

JULY 24, 2019

The 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019) is starting this week in Florence, Italy. Neural Networks are the workhorse of Deep Learning (cf. Neural Network Methods in Natural Language Processing. Sequence to sequence learning with neural networks.

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ODSC - Open Data Science

MARCH 6, 2024

Artificial Intelligence has made significant strides since its inception, evolving from simple algorithms to highly advanced Neural Networks capable of performing sophisticated tasks such as generating completely new content, including images, audio, and video.

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Probably Approximately a Scientific Blog

OCTOBER 30, 2017

Association for Computational Linguistics (ACL)" ) or considering all the word sequences that start with these initials, and deciding on the correct one using rules or a machine-learning based solution. Today, similarly to other NLP tasks, parsers are mostly based on neural networks. Given enough context (e.g.

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