b'Yida Wang'

research

∙ 03/08/2023

RAF: Holistic Compilation for Deep Learning Model Training

As deep learning is pervasive in modern applications, many deep learning...

0 Cody Hao Yu, et al. ∙

research

∙ 02/16/2023

Decoupled Model Schedule for Deep Learning Training

Recent years have seen an increase in the development of large deep lear...

0 Hongzheng Chen, et al. ∙

research

∙ 01/31/2023

Lidar Upsampling with Sliced Wasserstein Distance

Lidar became an important component of the perception systems in autonom...

0 Artem Savkin, et al. ∙

research

∙ 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...

0 Yaoyao Ding, et al. ∙

research

∙ 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...

0 Yida Wang, et al. ∙

research

∙ 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...

0 Zhen Zhang, et al. ∙

research

∙ 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...

0 Chenglong Wang, et al. ∙

research

∙ 03/30/2022

Learning Local Displacements for Point Cloud Completion

We propose a novel approach aimed at object and semantic scene completio...

0 Yida Wang, et al. ∙

research

∙ 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...

22 Evin Pınar Örnek, et al. ∙

research

∙ 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...

0 Hao Zhou, et al. ∙

research

∙ 06/06/2021

Semantic-Enhanced Explainable Finetuning for Open-Domain Dialogues

In this paper, we propose to combine pretrained language models with the...

0 Yinhe Zheng, et al. ∙

research

∙ 05/30/2021

Diversifying Dialog Generation via Adaptive Label Smoothing

Neural dialogue generation models trained with the one-hot target distri...

0 Yida Wang, et al. ∙

research

∙ 05/03/2021

Bring Your Own Codegen to Deep Learning Compiler

Deep neural networks (DNNs) have been ubiquitously applied in many appli...

25 Zhi Chen, et al. ∙

research

∙ 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...

0 Yida Wang, et al. ∙

research

∙ 01/21/2021

UNIT: Unifying Tensorized Instruction Compilation

Because of the increasing demand for computation in DNN, researchers dev...

3 Jian Weng, et al. ∙

research

∙ 11/20/2020

HAWQV3: Dyadic Neural Network Quantization

Quantization is one of the key techniques used to make Neural Networks (...

7 Zhewei Yao, et al. ∙

research

∙ 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...

0 Yuwei Hu, et al. ∙

research

∙ 08/17/2020

SoftPoolNet: Shape Descriptor for Point Cloud Completion and Classification

Point clouds are often the default choice for many applications as they ...

24 Yida Wang, et al. ∙

research

∙ 08/10/2020

A Large-Scale Chinese Short-Text Conversation Dataset

The advancements of neural dialogue generation models show promising res...

0 Yida Wang, et al. ∙

research

∙ 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...

0 Yanyan Li, et al. ∙

research

∙ 06/22/2020

Covert Communications with Constrained Age of Information

In this letter, we consider the requirement of information freshness in ...

0 Yida Wang, et al. ∙

research

∙ 06/18/2020

Efficient Execution of Quantized Deep Learning Models: A Compiler Approach

A growing number of applications implement predictive functions using de...

0 Animesh Jain, et al. ∙

research

∙ 06/17/2020

Is Network the Bottleneck of Distributed Training?

Recently there has been a surge of research on improving the communicati...

0 Zhen Zhang, et al. ∙

research

∙ 06/11/2020

Ansor : Generating High-Performance Tensor Programs for Deep Learning

High-performance tensor programs are crucial to guarantee efficient exec...

10 Lianmin Zheng, et al. ∙

research

∙ 06/04/2020

Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference

Modern deep neural networks increasingly make use of features such as dy...

0 Haichen Shen, et al. ∙

research

∙ 02/27/2020

Optimizing Memory-Access Patterns for Deep Learning Accelerators

Deep learning (DL) workloads are moving towards accelerators for faster ...

0 Hongbin Zheng, et al. ∙

research

∙ 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 ...

0 Yida Wang, et al. ∙

research

∙ 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...

0 Leyuan Wang, et al. ∙

research

∙ 10/25/2018

Adversarial Semantic Scene Completion from a Single Depth Image

We propose a method to reconstruct, complete and semantically label a 3D...

14 Yida Wang, et al. ∙

research

∙ 09/07/2018

Optimizing CNN Model Inference on CPUs

The popularity of Convolutional Neural Network (CNN) models and the ubiq...

0 Yizhi Liu, et al. ∙

research

∙ 07/16/2018

Scheduling Computation Graphs of Deep Learning Models on Manycore CPUs

For a deep learning model, efficient execution of its computation graph ...

0 Linpeng Tang, et al. ∙

research

∙ 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...

0 Yida Wang, et al. ∙

research

∙ 08/16/2016

Enabling Factor Analysis on Thousand-Subject Neuroimaging Datasets

The scale of functional magnetic resonance image data is rapidly increas...

0 Michael J. Anderson, et al. ∙

Yida Wang

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