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04/26/2022
GPUNet: Searching the Deployable Convolution Neural Networks for GPUs
Customizing Convolution Neural Networks (CNN) for production use has bee...
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10/07/2021
Multi-objective Optimization by Learning Space Partitions
In contrast to single-objective optimization (SOO), multi-objective opti...
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06/19/2021
Learning Space Partitions for Path Planning
Path planning, the problem of efficiently discovering high-reward trajec...
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07/01/2020
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search
High dimensional black-box optimization has broad applications but remai...
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06/11/2020
Few-shot Neural Architecture Search
To improve the search efficiency for Neural Architecture Search (NAS), O...
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06/17/2019
Sample-Efficient Neural Architecture Search by Learning Action Space
Neural Architecture Search (NAS) has emerged as a promising technique fo...
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11/21/2018
SuperNeurons: FFT-based Gradient Sparsification in the Distributed Training of Deep Neural Networks
The performance and efficiency of distributed training of Deep Neural Ne...
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05/18/2018
AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search
We present AlphaX, a fully automated agent that designs complex neural a...
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01/13/2018
SuperNeurons: Dynamic GPU Memory Management for Training Deep Neural Networks
Going deeper and wider in neural architectures improves the accuracy, wh...
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12/14/2017
Learning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition
Recurrent Neural Networks (RNNs) are powerful sequence modeling tools. H...
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11/11/2016
Simple and Efficient Parallelization for Probabilistic Temporal Tensor Factorization
Probabilistic Temporal Tensor Factorization (PTTF) is an effective algor...
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11/13/2015