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Veritable
Towards human-centered AI.
https://veritable.pw
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Machine Learning
Ceshine Lee
in
Veritable
Apr 17, 2021
[Paper] Adafactor: Adaptive Learning Rates with Sublinear Memory Cost
Essential for fine-tuning T5…
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4
Ceshine Lee
in
Veritable
Dec 8, 2020
[Paper] Are We Really Making Much Progress?
A Worrying Analysis of Recent Neural Recommendation…
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5
Ceshine Lee
in
Veritable
Sep 22, 2020
[Paper] Please Stop Permuting Features
Permutation importance can be very misleading
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8
Ceshine Lee
in
Veritable
Jul 21, 2020
[Tip] TorchScript Supports Half Precision
Speeding up inference for models trained with mixed…
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55
1 response
Ceshine Lee
in
Veritable
Nov 28, 2019
Fine-tuning BERT for Similarity Search
BERT as Sentence Encoder is Surprisingly Sample-Efficient
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193
2 responses
Ceshine Lee
in
Veritable
Sep 25, 2019
Zero Shot Cross-Lingual Transfer with Multilingual BERT
Finetuning BERT for Sentence Embeddings on…
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100
Ceshine Lee
in
Veritable
Sep 1, 2019
More Memory-Efficient Swish Activation Function
And How to Profile PyTorch GPU Memory Usage
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47
Ceshine Lee
in
Veritable
Aug 6, 2019
[Notes] Jigsaw Unintended Bias in Toxicity Classification
Bias Reduction; Summary of Top Solutions
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28
Ceshine Lee
in
Veritable
Jul 20, 2019
[Notes] iMet Collection 2019 — FGVC6 (Part 1)
Overview; Augmentation; Training Models on Kaggle
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15
1 response
Ceshine Lee
in
Veritable
Jun 21, 2019
Mixed Precision Training on Tesla T4 and P100
Training Wide-Resnet with Apex on Google Colab and Kaggle
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