17 citations · 17 across the 1 of their papers we have counts for
3 papers
Introducing Milabench: Benchmarking Accelerators for AI
Pierre Delaunay, Xavier Bouthillier, Olivier Breuleux +12
AI workloads, particularly those driven by deep learning, are introducing novel usage patterns to high-performance computing (HPC) systems that are not comprehensively captured by…
LMEMs for post-hoc analysis of HPO Benchmarking
Anton Geburek, Neeratyoy Mallik, Danny Stoll +2
The importance of tuning hyperparameters in Machine Learning (ML) and Deep Learning (DL) is established through empirical research and applications, evident from the increase in ne…
Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets
Pascal Vincent, Alexandre de Brébisson, Xavier Bouthillier
An important class of problems involves training deep neural networks with sparse prediction targets of very high dimension D. These occur naturally in e.g. neural language models…