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08/28/2023
Target-independent XLA optimization using Reinforcement Learning
An important challenge in Machine Learning compilers like XLA is multi-p...
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07/11/2023
SAM^Med: A medical image annotation framework based on large vision model
Recently, large vision model, Segment Anything Model (SAM), has revoluti...
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03/08/2023
RAF: Holistic Compilation for Deep Learning Model Training
As deep learning is pervasive in modern applications, many deep learning...
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02/16/2023
Decoupled Model Schedule for Deep Learning Training
Recent years have seen an increase in the development of large deep lear...
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01/31/2023
Lidar Upsampling with Sliced Wasserstein Distance
Lidar became an important component of the perception systems in autonom...
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10/18/2022
Hidet: Task-Mapping Programming Paradigm for Deep Learning Tensor Programs
As deep learning models nowadays are widely adopted by both cloud servic...
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05/08/2022
SoftPool++: An Encoder-Decoder Network for Point Cloud Completion
We propose a novel convolutional operator for the task of point cloud co...
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04/30/2022
MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud
Existing general purpose frameworks for gigantic model training, i.e., m...
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04/08/2022
Towards Reliable and Explainable AI Model for Solid Pulmonary Nodule Diagnosis
Lung cancer has the highest mortality rate of deadly cancers in the worl...
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03/30/2022
Learning Local Displacements for Point Cloud Completion
We propose a novel approach aimed at object and semantic scene completio...
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03/15/2022
From 2D to 3D: Re-thinking Benchmarking of Monocular Depth Prediction
There have been numerous recently proposed methods for monocular depth p...
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08/03/2021
EVA: An Open-Domain Chinese Dialogue System with Large-Scale Generative Pre-Training
Although pre-trained language models have remarkably enhanced the genera...
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06/06/2021
Semantic-Enhanced Explainable Finetuning for Open-Domain Dialogues
In this paper, we propose to combine pretrained language models with the...
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05/30/2021
Diversifying Dialog Generation via Adaptive Label Smoothing
Neural dialogue generation models trained with the one-hot target distri...
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05/03/2021
Bring Your Own Codegen to Deep Learning Compiler
Deep neural networks (DNNs) have been ubiquitously applied in many appli...
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04/13/2021
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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01/21/2021
UNIT: Unifying Tensorized Instruction Compilation
Because of the increasing demand for computation in DNN, researchers dev...
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11/20/2020
HAWQV3: Dyadic Neural Network Quantization
Quantization is one of the key techniques used to make Neural Networks (...
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08/26/2020
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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08/17/2020
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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08/10/2020
A Large-Scale Chinese Short-Text Conversation Dataset
The advancements of neural dialogue generation models show promising res...
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08/05/2020
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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06/22/2020
Covert Communications with Constrained Age of Information
In this letter, we consider the requirement of information freshness in ...
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06/18/2020
Efficient Execution of Quantized Deep Learning Models: A Compiler Approach
A growing number of applications implement predictive functions using de...
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06/17/2020
Is Network the Bottleneck of Distributed Training?
Recently there has been a surge of research on improving the communicati...
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06/11/2020
Ansor : Generating High-Performance Tensor Programs for Deep Learning
High-performance tensor programs are crucial to guarantee efficient exec...
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06/04/2020
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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02/27/2020
Optimizing Memory-Access Patterns for Deep Learning Accelerators
Deep learning (DL) workloads are moving towards accelerators for faster ...
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09/03/2019
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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07/03/2019
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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10/25/2018
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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09/07/2018
Optimizing CNN Model Inference on CPUs
The popularity of Convolutional Neural Network (CNN) models and the ubiq...
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07/16/2018
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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05/24/2017
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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08/16/2016