Explosion

DECEMBER 17, 2013

I wrote this blog post in 2013, describing an exciting advance in natural language understanding technology. Today, almost all high-performance parsers are using a variant of the algorithm described below (including spaCy). But the parsing algorithm I’ll be explaining deals with projective trees.

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Bugra Akyildiz

NOVEMBER 17, 2024

Vision Transformers(ViT) ViT is a type of machine learning model that applies the transformer architecture, originally developed for natural language processing, to image recognition tasks. and 8B base and chat models, supporting both English and Chinese languages. 2020) EBM : Explainable Boosting Machine (Nori, et al.

Convolutional Neural Networks 52

Convolutional Neural Networks Metadata Computer Vision Python 52

Topbots

SEPTEMBER 11, 2023

This approach leads them straight into the integration fallacy: even if these experts and engineers produce exceptional models and algorithms, their outputs often get stuck at the level of playgrounds, sandboxes, and demos, and never really become full-fledged parts of a product. 3] Don Norman (2013). 2] Orbit Media (2022).

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Sebastian Ruder

JANUARY 19, 2021

The selection of areas and methods is heavily influenced by my own interests; the selected topics are biased towards representation and transfer learning and towards natural language processing (NLP).  Reinforcement learning algorithms have a multitude of practical implications ( Bellemare et al.,

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Kavita Ganesan

MAY 24, 2022

And they may not fit in within your infrastructure, you may have an old infrastructure that can maybe take in basic computer algorithms, not something sophisticated that needs GPUs, and TPUs. I took one natural language processing class and the professor. So, that’s how I got exposed to this whole field. I liked it.

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Sebastian Ruder

OCTOBER 26, 2019

To ensure that non-English language speakers are not left behind and at the same time to offset the existing imbalance, we need to apply our models to non-English languages. The NLP Resource Hierarchy In current machine learning, the amount of available training data is the main factor that influences an algorithm's performance.

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The Stanford AI Lab Blog

MAY 31, 2022

Language Model Pretraining Language models (LMs), like BERT 1 and the GPT series 2 , achieve remarkable performance on many natural language processing (NLP) tasks. We will now see how LinkBERT performs on several downstream natural language processing tasks. Let’s use LinkBERT!

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Artificial Corner

JUNE 6, 2023

The 1990s also saw the rise of data mining, the process of discovering patterns and knowledge from large amounts of data. Data mining involves using sophisticated algorithms to identify patterns and relationships in data that might not be immediately apparent. MapReduce: simplified data processing on large clusters.

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Data Mining Big Data ETL Machine Learning 52

Probably Approximately a Scientific Blog

AUGUST 30, 2019

Scope The reason that everyone is talking about language models (LMs) lately is not so much that they're all working on text generation, but because pre-trained LMs (like the OpenAI GPT-2 or Google's BERT ) are used to produce text representations across various NLP applications, greatly improving their performances.

NLP 52

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ML Review

JUNE 4, 2018

Recent Intersections Between Computer Vision and Natural Language Processing (Part Two) This is the second instalment of our latest publication series looking at some of the intersections between Computer Vision (CV) and Natural Language Processing (NLP). Image Captioning with Semantic Attention (You et al.,

Neural Network 52

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Probably Approximately a Scientific Blog

JANUARY 3, 2016

We're already after 6 posts on the topic of natural language processing, and I can't believe I haven't discussed this basic topic yet. So today I'm going to discuss words; More accurately - I will discuss how words are represented in natural language processing. CoRR, 2013. EMNLP 2014.

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ML Review

MAY 3, 2018

Recent Intersections Between Computer Vision and Natural Language Processing (Part One) This is the first instalment of our latest publication series looking at some of the intersections between Computer Vision (CV) and Natural Language Processing (NLP). Thus the algorithm is alignment-free.

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NLP People

JULY 24, 2019

As the following chart shows, research activity has been flourishing in the past years: Figure 1: Paper quantity published at the ACL conference by years In the following, we summarize some core trends in terms of data strategies, algorithms, tasks as well as multilingual NLP. They not only need annotated data – they need Big Labeled Data.

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ODSC - Open Data Science

FEBRUARY 29, 2024

The Stanford AI Lab Founded in 1963, the Stanford AI Lab has made significant contributions to various domains, including natural language processing, computer vision, and robotics. Notably, BAIR recently unveiled a pioneering algorithm that revolutionizes the efficiency of deep learning models. But that’s not all.

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Artificial Intelligence Artificial Intelligence AI Research AI Researcher 52

Viso.ai

DECEMBER 21, 2023

From the development of sophisticated object detection algorithms to the rise of convolutional neural networks (CNNs) for image classification to innovations in facial recognition technology, applications of computer vision are transforming entire industries. This significantly enhances the training process for multi-layer neural networks.

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