Xiaoliang Dai | DeepAI

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Featured Co-authors

Masayoshi Tomizuka
149 publications
Matthias Nießner
114 publications
Kurt Keutzer
112 publications
Yiran Chen
100 publications
Joseph E. Gonzalez
99 publications
Hai Li
85 publications
Zsolt Kira
69 publications
Yuandong Tian
69 publications
Prateek Mittal
63 publications
Yingyan Lin
57 publications
Hang Zhang
55 publications

∙ 09/21/2023

Unveiling Optimal SDG Pathways: An Innovative Approach Leveraging Graph Pruning and Intent Graph for Effective Recommendations

The recommendation of appropriate development pathways, also known as ec...

0 Zhihang Yu, et al. ∙

∙ 04/24/2023

Auto-CARD: Efficient and Robust Codec Avatar Driving for Real-time Mobile Telepresence

Real-time and robust photorealistic avatars for telepresence in AR/VR ha...

0 Yonggan Fu, et al. ∙

∙ 03/19/2023

Trainable Projected Gradient Method for Robust Fine-tuning

Recent studies on transfer learning have shown that selectively fine-tun...

0 Junjiao Tian, et al. ∙

∙ 02/28/2023

Mask3D: Pre-training 2D Vision Transformers by Learning Masked 3D Priors

Current popular backbones in computer vision, such as Vision Transformer...

0 Ji Hou, et al. ∙

∙ 11/18/2022

Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention During Vision Transformer Inference

Vision Transformers (ViTs) have shown impressive performance but still r...

0 Haoran You, et al. ∙

∙ 11/12/2022

3D-Aware Encoding for Style-based Neural Radiance Fields

We tackle the task of NeRF inversion for style-based neural radiance fie...

4 Yu-Jhe Li, et al. ∙

∙ 10/17/2022

Token Merging: Your ViT But Faster

We introduce Token Merging (ToMe), a simple method to increase the throu...

0 Daniel Bolya, et al. ∙

∙ 10/09/2022

Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP

Open-vocabulary semantic segmentation aims to segment an image into sema...

36 Feng Liang, et al. ∙

∙ 09/15/2022

Hydra Attention: Efficient Attention with Many Heads

While transformers have begun to dominate many tasks in vision, applying...

0 Daniel Bolya, et al. ∙

∙ 08/29/2022

Open-Set Semi-Supervised Object Detection

Recent developments for Semi-Supervised Object Detection (SSOD) have sho...

15 Yen-Cheng Liu, et al. ∙

∙ 07/14/2022

NASRec: Weight Sharing Neural Architecture Search for Recommender Systems

The rise of deep neural networks provides an important driver in optimiz...

0 Tunhou Zhang, et al. ∙

∙ 11/25/2021

Cross-Domain Object Detection via Adaptive Self-Training

We tackle the problem of domain adaptation in object detection, where th...

4 Yu-Jhe Li, et al. ∙

∙ 11/19/2021

FBNetV5: Neural Architecture Search for Multiple Tasks in One Run

Neural Architecture Search (NAS) has been widely adopted to design accur...

10 Bichen Wu, et al. ∙

∙ 11/22/2020

FP-NAS: Fast Probabilistic Neural Architecture Search

Differential Neural Architecture Search (NAS) requires all layer choices...

4 Zhicheng Yan, et al. ∙

∙ 07/29/2020

Fully Dynamic Inference with Deep Neural Networks

Modern deep neural networks are powerful and widely applicable models th...

0 Wenhan Xia, et al. ∙

∙ 06/05/2020

Visual Transformers: Token-based Image Representation and Processing for Computer Vision

Computer vision has achieved great success using standardized image repr...

23 Bichen Wu, et al. ∙

∙ 06/03/2020

FBNetV3: Joint Architecture-Recipe Search using Neural Acquisition Function

Neural Architecture Search (NAS) yields state-of-the-art neural networks...

11 Xiaoliang Dai, et al. ∙

∙ 04/12/2020

FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions

Differentiable Neural Architecture Search (DNAS) has demonstrated great ...

17 Alvin Wan, et al. ∙

∙ 12/12/2019

STEERAGE: Synthesis of Neural Networks Using Architecture Search and Grow-and-Prune Methods

Neural networks (NNs) have been successfully deployed in many applicatio...

0 Shayan Hassantabar, et al. ∙

∙ 10/11/2019

DiabDeep: Pervasive Diabetes Diagnosis based on Wearable Medical Sensors and Efficient Neural Networks

Diabetes impacts the quality of life of millions of people. However, dia...

13 Hongxu Yin, et al. ∙

∙ 05/27/2019

Incremental Learning Using a Grow-and-Prune Paradigm with Efficient Neural Networks

Deep neural networks (DNNs) have become a widely deployed model for nume...

0 Xiaoliang Dai, et al. ∙

∙ 12/21/2018

ChamNet: Towards Efficient Network Design through Platform-Aware Model Adaptation

This paper proposes an efficient neural network (NN) architecture design...

0 Xiaoliang Dai, et al. ∙

∙ 12/09/2018

FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search

Designing accurate and efficient ConvNets for mobile devices is challeng...

0 Bichen Wu, et al. ∙

∙ 05/30/2018

Grow and Prune Compact, Fast, and Accurate LSTMs

Long short-term memory (LSTM) has been widely used for sequential data m...

0 Xiaoliang Dai, et al. ∙

∙ 05/30/2018

Grow and Prune Compact, Fast, and AccurateLSTMs

Long short-term memory (LSTM) has been widely used for sequential data m...

0 Xiaoliang Dai, et al. ∙

∙ 02/05/2018

PinMe: Tracking a Smartphone User around the World

With the pervasive use of smartphones that sense, collect, and process v...

0 Arsalan Mosenia, et al. ∙

∙ 11/06/2017

NeST: A Neural Network Synthesis Tool Based on a Grow-and-Prune Paradigm

Neural networks (NNs) have begun to have a pervasive impact on various a...

0 Xiaoliang Dai, et al. ∙

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