MLab

ACMLab is Stanford's premier machine learning club. Its goal is to teach anyone with basic CS experience machine learning. After an intensive ramp-up workshop in the fall, members work on publishing papers at top ML conferences and workshops. We have published 6 workshop papers so far at top conferences and workshops such as ACL and ICLR. Alumni have gone on to Google AI, Stanford ML Group, Stanford NLP Group, and VMWare.

Fall 2024 Onboarding Project

In the MLab Fall Onboarding Project, you will sharpen your deep learning skills by engaging with a high-impact real-world problem. In doing so, you will learn about infrastructure, data processing, implementation, model evaluation, and other critical tools of a machine learning practitioner. By the end of the project, you will have gained valuable skills and expertise in the field of machine learning.

This year’s Fall Project is on bird classification.

Fall 2024 Schedule

This year, we'll be meeting weekly on Wednesday from 7:30-9:00pm PT.

Recent Projects

SemEVAL

We submitted to the Workshop on Semantic Evaluation's Task 1 (lexical complexity modelling) and Task 8 (automatically extracting measurements from scientific text). Our teams performed competitively on both tasks, including second place in one of the Task 8 subcategories. Our task description papers will appear at SemEval at ACL 2021.

Google BIG-Bench

Members proposed 4 tasks to be used in Google's BIG-Bench challenge. The purpose of this challenge was to create a collaborative benchmark for enourmous language models like GPT-3. MLab submitted tasks about temporal sequences, logic puzzles, sarcasm, and IPA translation.

VQA

We are currently preparing a submission on the ChartQA workshop at CVPR 2021, aiming to automatically parse structured information from diverse chart-based visual representations.

Recent Publications