Andrew Tulloch
Publications by Year
Research Areas
Stochastic Gradient Optimization Techniques, Advanced Neural Network Applications, Topic Modeling, Parallel Computing and Optimization Techniques, Sparse and Compressive Sensing Techniques
Most-Cited Works
- → Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour(2017)2,612 cited
- → Machine Learning at Facebook: Understanding Inference at the Edge(2019)443 cited
- → Software-hardware co-design for fast and scalable training of deep learning recommendation models(2022)122 cited
- → GPT-4o System Card(2024)100 cited
- → Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications(2018)82 cited
- → High performance ultra-low-precision convolutions on mobile devices(2017)19 cited
- High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models.(2021)
- → Mixed-Precision Embedding Using a Cache(2020)15 cited
- → On Periodic Functions as Regularizers for Quantization of Neural Networks(2018)14 cited
- → Accurate Low-Rank Approximations Via a Few Iterations of Alternating Least Squares(2017)14 cited