
Automated BackendAware PostTraining Quantization
Quantization is a key technique to reduce the resource requirement and i...
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RAILS: A Robust Adversarial Immuneinspired Learning System
Adversarial attacks against deep neural networks are continuously evolvi...
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Cortex: A Compiler for Recursive Deep Learning Models
Optimizing deep learning models is generally performed in two steps: (i)...
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Dynamic Tensor Rematerialization
Checkpointing enables training deep learning models under restricted mem...
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Relay: A HighLevel Compiler for Deep Learning
Frameworks for writing, compiling, and optimizing deep learning (DL) mod...
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Relay: A HighLevel IR for Deep Learning
Frameworks for writing, compiling, and optimizing deep learning (DL) mod...
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ADARES: Adaptive Resource Management for Virtual Machines
Virtual execution environments allow for consolidation of multiple appli...
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Automating Generation of Low Precision Deep Learning Operators
State of the art deep learning models have made steady progress in the f...
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Relay: A New IR for Machine Learning Frameworks
Machine learning powers diverse services in industry including search, t...
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VTA: An Open HardwareSoftware Stack for Deep Learning
Hardware acceleration is an enabler for ubiquitous and efficient deep le...
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Learning to Optimize Tensor Programs
We introduce a learningbased framework to optimize tensor programs for ...
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TVM: An Automated EndtoEnd Optimizing Compiler for Deep Learning
There is an increasing need to bring machine learning to a wide diversit...
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TVM: EndtoEnd Optimization Stack for Deep Learning
Scalable frameworks, such as TensorFlow, MXNet, Caffe, and PyTorch drive...
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MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems
MXNet is a multilanguage machine learning (ML) library to ease the deve...
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Net2Net: Accelerating Learning via Knowledge Transfer
We introduce techniques for rapidly transferring the information stored ...
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A Complete Recipe for Stochastic Gradient MCMC
Many recent Markov chain Monte Carlo (MCMC) samplers leverage continuous...
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Empirical Evaluation of Rectified Activations in Convolutional Network
In this paper we investigate the performance of different types of recti...
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A Parallel and Efficient Algorithm for Learning to Match
Many tasks in data mining and related fields can be formalized as matchi...
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Stochastic Gradient Hamiltonian Monte Carlo
Hamiltonian Monte Carlo (HMC) sampling methods provide a mechanism for d...
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FeatureBased Matrix Factorization
Recommender system has been more and more popular and widely used in man...
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Tianqi Chen
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