- mlsys
- transformer
- paper-summaries
- MLSys
- LLMs
- PPML
•
•
•
•
•
-
PPML Series #3 - Federated Learning for Mobile Keyboard Prediction
Understanding how your mobile keyboard (Gboard, specifically) performs the next word prediction task and performs model training and updates
-
PPML Series #2 - Federated Optimization Algorithms - FedSGD and FedAvg
A mathematical deep dive on a Federated Optimization algorithm - FedAvg and comparing it with a standard approach - FedSGD.
-
PPML Series #1 - An introduction to Federated Learning
A short general introduction to Federated Learning (FL) for folks interested in privacy-preserving machine learning (PPML).
-
Paper Summary #6 - Language Models are Unsupervised Multitask Learners
The GPT2 model which aimed to perform complex NLP tasks while relying only on a language model trained in a completely unsupervised fashion.
-
Paper Summary #5 - XLNet: Generalized Autoregressive Pretraining for Language Understanding
XLNet tries to overcome the limitations of BERT by having a autoregressive component while also capturing the bidirectional context.
-
Paper Summary #4 - BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
The ground breaking paper that introduced the famous BERT model. This started the inflow of a large number of BERT-based language understanding models.
-
Paper Summary #3 - Improving Language Understanding by Generative Pre-Training
The first paper in the GPT set of models. This is OpenAI's GPT-1.
-
Paper Summary #2 - Deep contextualized word representations (ELMo)
The second post in the paper notes series. This time we take a look at ELMo.
-
Paper Summary #1 - Attention Is All You Need
The first of the paper summary series. This is where I briefly summarise the important papers that I read for my job or just for fun :P
-
Deep Learning in the Browser - Exploring TF.js, WebDNN and ONNX.js
A quick tutorial to set up a small scale deployment for your ML or DL model