research
∙
06/11/2023
Kepler: Robust Learning for Faster Parametric Query Optimization
Most existing parametric query optimization (PQO) techniques rely on tra...
share
research
∙
12/07/2021
A Transferable Approach for Partitioning Machine Learning Models on Multi-Chip-Modules
Multi-Chip-Modules (MCMs) reduce the design and fabrication cost of mach...
research
∙
06/04/2021
RL-DARTS: Differentiable Architecture Search for Reinforcement Learning
We introduce RL-DARTS, one of the first applications of Differentiable A...
research
∙
02/09/2021
Reverb: A Framework For Experience Replay
A central component of training in Reinforcement Learning (RL) is Experi...
research
∙
01/13/2021
MLGO: a Machine Learning Guided Compiler Optimizations Framework
Leveraging machine-learning (ML) techniques for compiler optimizations h...
research
∙
07/04/2018
Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion
Integrating model-free and model-based approaches in reinforcement learn...
research
∙
05/04/2018
Dynamic Control Flow in Large-Scale Machine Learning
Many recent machine learning models rely on fine-grained dynamic control...
research
∙
03/16/2018
Tensor2Tensor for Neural Machine Translation
Tensor2Tensor is a library for deep learning models that is well-suited ...
research
∙
11/28/2017
TensorFlow Distributions
The TensorFlow Distributions library implements a vision of probability ...
research
∙
01/13/2017
Deep Probabilistic Programming
We propose Edward, a Turing-complete probabilistic programming language....
research
∙
03/14/2016
