papers

Publications (11)

cs.LG2018

Mesh-TensorFlow: Deep Learning for Supercomputers

Noam Shazeer, Youlong Cheng, Niki Parmar +9

Batch-splitting (data-parallelism) is the dominant distributed Deep Neural Network (DNN) training strategy, due to its universal applicability and its amenability to Single-Program…

cs.HC2021

Toward Annotator Group Bias in Crowdsourcing

Haochen Liu, Joseph Thekinen, Sinem Mollaoglu +5

Crowdsourcing has emerged as a popular approach for collecting annotated data to train supervised machine learning models. However, annotator bias can lead to defective annotations…

cs.CV2019

GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism

Yanping Huang, Youlong Cheng, Ankur Bapna +8

Scaling up deep neural network capacity has been known as an effective approach to improving model quality for several different machine learning tasks. In many cases, increasing m…

cs.LG2019

Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

Jonathan Shen, Patrick Nguyen, Yonghui Wu +88

Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models. Lingvo models a…

cs.CL2024

GPT-4o System Card

OpenAI, :, Aaron Hurst +416

GPT-4o is an autoregressive omni model that accepts as input any combination of text, audio, image, and video, and generates any combination of text, audio, and image outputs. It's…

cs.LG2022

CowClip: Reducing CTR Prediction Model Training Time from 12 hours to 10 minutes on 1 GPU

Zangwei Zheng, Pengtai Xu, Xuan Zou +12

The click-through rate (CTR) prediction task is to predict whether a user will click on the recommended item. As mind-boggling amounts of data are produced online daily, accelerati…

cs.IR2022

Monolith: Real Time Recommendation System With Collisionless Embedding Table

Zhuoran Liu, Leqi Zou, Xuan Zou +8

Building a scalable and real-time recommendation system is vital for many businesses driven by time-sensitive customer feedback, such as short-videos ranking or online ads. Despite…

eess.IV2019

High Resolution Medical Image Analysis with Spatial Partitioning

Le Hou, Youlong Cheng, Noam Shazeer +6

Medical images such as 3D computerized tomography (CT) scans and pathology images, have hundreds of millions or billions of voxels/pixels. It is infeasible to train CNN models dire…

cs.LG2018

Image Classification at Supercomputer Scale

Chris Ying, Sameer Kumar, Dehao Chen +2

Deep learning is extremely computationally intensive, and hardware vendors have responded by building faster accelerators in large clusters. Training deep learning models at petaFL…

cs.LG2020

Talking-Heads Attention

Noam Shazeer, Zhenzhong Lan, Youlong Cheng +2

We introduce "talking-heads attention" - a variation on multi-head attention which includes linearprojections across the attention-heads dimension, immediately before and after the…

cs.LG2021

Enhanced Exploration in Neural Feature Selection for Deep Click-Through Rate Prediction Models via Ensemble of Gating Layers

Lin Guan, Xia Xiao, Ming Chen +1

Feature selection has been an essential step in developing industry-scale deep Click-Through Rate (CTR) prediction systems. The goal of neural feature selection (NFS) is to choose…