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Probabilistic Accumulate-then-Transmit in Wireless-Powered Covert Communications
In this paper, we investigate the optimal design of a wireless-powered c...
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UNIT: Unifying Tensorized Instruction Compilation
Because of the increasing demand for computation in DNN, researchers dev...
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HAWQV3: Dyadic Neural Network Quantization
Quantization is one of the key techniques used to make Neural Networks (...
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FeatGraph: A Flexible and Efficient Backend for Graph Neural Network Systems
Graph neural networks (GNNs) are gaining increasing popularity as a prom...
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SoftPoolNet: Shape Descriptor for Point Cloud Completion and Classification
Point clouds are often the default choice for many applications as they ...
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A Large-Scale Chinese Short-Text Conversation Dataset
The advancements of neural dialogue generation models show promising res...
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Structure-SLAM: Low-Drift Monocular SLAM in Indoor Environments
In this paper a low-drift monocular SLAM method is proposed targeting in...
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Covert Communications with Constrained Age of Information
In this letter, we consider the requirement of information freshness in ...
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Efficient Execution of Quantized Deep Learning Models: A Compiler Approach
A growing number of applications implement predictive functions using de...
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Is Network the Bottleneck of Distributed Training?
Recently there has been a surge of research on improving the communicati...
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Ansor : Generating High-Performance Tensor Programs for Deep Learning
High-performance tensor programs are crucial to guarantee efficient exec...
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Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference
Modern deep neural networks increasingly make use of features such as dy...
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Optimizing Memory-Access Patterns for Deep Learning Accelerators
Deep learning (DL) workloads are moving towards accelerators for faster ...
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ForkNet: Multi-branch Volumetric Semantic Completion from a Single Depth Image
We propose a novel model for 3D semantic completion from a single depth ...
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A Unified Optimization Approach for CNN Model Inference on Integrated GPUs
Modern deep learning applications urge to push the model inference takin...
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Adversarial Semantic Scene Completion from a Single Depth Image
We propose a method to reconstruct, complete and semantically label a 3D...
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Optimizing CNN Model Inference on CPUs
The popularity of Convolutional Neural Network (CNN) models and the ubiq...
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Scheduling Computation Graphs of Deep Learning Models on Manycore CPUs
For a deep learning model, efficient execution of its computation graph ...
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Generative Model with Coordinate Metric Learning for Object Recognition Based on 3D Models
Given large amount of real photos for training, Convolutional neural net...
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Enabling Factor Analysis on Thousand-Subject Neuroimaging Datasets
The scale of functional magnetic resonance image data is rapidly increas...
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