The Stanford AI Lab Blog

OCTOBER 13, 2021

Acknowledgements Thanks to the SAIL blog editors, Pang Wei Koh, and Shiori Sagawa for their helpful feedback on this blog post. This post is based off our ICLR 2021 paper : Selective Classification Can Magnify Disparities Across Groups. arXiv preprint arXiv:2102.10395, 2021. ↩

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Sebastian Ruder

JANUARY 24, 2022

2021) 2021 saw many exciting advances in machine learning (ML) and natural language processing (NLP).   2021 saw the continuation of the development of ever larger pre-trained models. 2021 saw the development of alternative model architectures that are viable alternatives to the transformer. style loss.

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The Stanford AI Lab Blog

DECEMBER 17, 2021

Our state-of-the-art (k)-medoids algorithm from NeurIPS, BanditPAM, is now publicly available! In our NeurIPS paper, BanditPAM, we sped up the best known algorithm from (O(n^2)) to (O(ntext{log}n)). In our NeurIPS paper, BanditPAM, we reduced the complexity of the best known (k)-medoids algorithm from (O(n^2)) to (O(ntext{log}n)).

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AssemblyAI

MARCH 21, 2023

We can get a first glimpse of this impressive growth if we look at the accepted research publications from the last 3 years for both ICLR and NeurIPS, the two major annual conferences which focus on cutting edge AI research. We find that the term Graph Neural Network consistently ranked in the top 3 keywords year over year.

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AWS Machine Learning Blog

DECEMBER 20, 2023

His PhD is from Duke University and he has published papers in NeurIPS, Cell, and Neuron. In 2021, he presented a paper on adversarial neural networks at the ICLR conference. He is an active researcher in machine learning and statistical inference, and has published many papers in NeurIPS, ICML, ICLR, JMLR, ACL, and EMNLP conferences.

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Flipboard

JULY 10, 2023

Figure 4: Architecture of fully connected autoencoders (source: Amor, “Comprehensive introduction to Autoencoders,” ML Cheat Sheet , 2021 ). Figure 8: Architecture of variational autoencoder (source: Yadav, “Variational Autoencoders,” Data-Science-Blog , 2022 ). ✓ Access on mobile, laptop, desktop, etc.

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The Stanford AI Lab Blog

MARCH 28, 2022

In our recent NeurIPS 2021 paper , we illustrate the challenges in treating interactive coding assignment grading as game playing and introduce the Play to Grade Challenge. This blog post is based on the following paper: “Play to Grade: Testing Coding Games as Classifying Markov Decision Process.”

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AWS Machine Learning Blog

NOVEMBER 14, 2023

Inference example with and without fine-tuning The following table contains the results of the Mistral 7B model fine-tuned with SEC filing documents of Amazon from 2021–2022. He is an active researcher in machine learning and statistical inference, and has published many papers in NeurIPS, ICML, ICLR, JMLR, ACL, and EMNLP conferences.

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Bugra Akyildiz

DECEMBER 3, 2022

Even though there are some limitations that are outlined in the blog post, the bot is really good and has a large breadth of topics that it can hold intelligible conversations. For models and datasets , checkout out HuggingFace (HF) page: [link].

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Sebastian Ruder

JANUARY 19, 2021

They have also facilitated competitions and benchmarks that evaluate models primarily based on their efficiency such as the SustaiNLP workshop at EMNLP 2020, the Efficient QA competition at NeurIPS 2020, and HULK ( Zhou et al., Consequently, the best systems in the NeurIPS 2020 EfficientQA competition ( Min et al.,

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AWS Machine Learning Blog

SEPTEMBER 6, 2023

He is an active researcher in machine learning and statistical inference, and has published many papers in NeurIPS, ICML, ICLR, JMLR, ACL, and EMNLP conferences. Ashish Khetan is a Senior Applied Scientist with Amazon SageMaker JumpStart and helps develop machine learning algorithms.

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AWS Machine Learning Blog

OCTOBER 30, 2023

In 2021, he presented a paper on adversarial neural networks at the ICLR conference. He is an active researcher in machine learning and statistical inference, and has published many papers in NeurIPS, ICML, ICLR, JMLR, ACL, and EMNLP conferences. He is interested in the confluence of machine learning with cloud computing.

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