Search Results for author: Yu Hu

Found 36 papers, 10 papers with code

PA&DA: Jointly Sampling PAth and DAta for Consistent NAS

1 code implementation CVPR 2023 Shun Lu, Yu Hu, Longxing Yang, Zihao Sun, Jilin Mei, Jianchao Tan, Chengru Song

Our method only requires negligible computation cost for optimizing the sampling distributions of path and data, but achieves lower gradient variance during supernet training and better generalization performance for the supernet, resulting in a more consistent NAS.

Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback

no code implementations24 Feb 2023 Baolin Peng, Michel Galley, Pengcheng He, Hao Cheng, Yujia Xie, Yu Hu, Qiuyuan Huang, Lars Liden, Zhou Yu, Weizhu Chen, Jianfeng Gao

Large language models (LLMs), such as ChatGPT, are able to generate human-like, fluent responses for many downstream tasks, e. g., task-oriented dialog and question answering.

Informativeness Open-Domain Question Answering

Few-shot 3D LiDAR Semantic Segmentation for Autonomous Driving

no code implementations17 Feb 2023 Jilin Mei, Junbao Zhou, Yu Hu

Thus, we propose a few-shot 3D LiDAR semantic segmentation method that predicts both novel classes and base classes simultaneously.

Autonomous Driving Generalized Few-Shot Semantic Segmentation +4

Uniform tensor clustering by jointly exploring sample affinities of various orders

no code implementations3 Feb 2023 Hongmin Cai, Fei Qi, Junyu Li, Yu Hu, Yue Zhang, Yiu-ming Cheung, Bin Hu

Conventional clustering methods based on pairwise affinity usually suffer from the concentration effect while processing huge dimensional features yet low sample sizes data, resulting in inaccuracy to encode the sample proximity and suboptimal performance in clustering.


CloudBrain-ReconAI: An Online Platform for MRI Reconstruction and Image Quality Evaluation

no code implementations4 Dec 2022 Yirong Zhou, Chen Qian, Jiayu Li, Zi Wang, Yu Hu, Biao Qu, Liuhong Zhu, Jianjun Zhou, Taishan Kang, Jianzhong Lin, Qing Hong, Jiyang Dong, Di Guo, Xiaobo Qu

Efficient collaboration between engineers and radiologists is important for image reconstruction algorithm development and image quality evaluation in magnetic resonance imaging (MRI).

Cloud Computing MRI Reconstruction

A General Model-Based Extended State Observer with Built-In Zero Dynamics

no code implementations25 Aug 2022 Jinfeng Chen, Zhiqiang Gao, Yu Hu, Sally Shao

A general model-based extended state observer (GMB-ESO) is proposed for single-input single-output linear time-invariant systems with a given state space model, where the total disturbance, a lump sum of model uncertainties and external disturbances, is defined as an extended state in the same manner as in the original formulation of ESO.

AGNAS: Attention-Guided Micro- and Macro-Architecture Search

1 code implementation International Conference on Machine Learning 2022 Zihao Sun, Yu Hu, Shun Lu, Longxing Yang, Jilin Mei, Yinhe Han, Xiaowei Li

We utilize the attention weights to represent the importance of the relevant operations for the micro search or the importance of the relevant blocks for the macro search.

Neural Architecture Search

Potential utilization of Battery Energy Storage Systems (BESS) in the major European electricity markets

no code implementations18 Dec 2021 Yu Hu, Miguel Armada, Maria Jesus Sanchez

The result shows that under the current empirical estimation of the battery cost and lifetime, BESS is not feasible for energy arbitrage in most of the European electricity markets.

Learning Linear Polytree Structural Equation Models

1 code implementation22 Jul 2021 Xingmei Lou, Yu Hu, XiaoDong Li

Under the Gaussian polytree models, we study sufficient conditions on the sample sizes for the well-known Chow-Liu algorithm to exactly recover both the skeleton and the equivalence class of the polytree, which is uniquely represented by a CPDAG.

Deep learning based low-dose synchrotron radiation CT reconstruction

no code implementations9 Jun 2021 Ling Li, Yu Hu

Synchrotron radiation sources are widely used in various fields, among which computed tomography (CT) is one of the most important.

Computed Tomography (CT)

Quantization of Deep Neural Networks for Accurate Edge Computing

no code implementations25 Apr 2021 Wentao Chen, Hailong Qiu, Jian Zhuang, Chutong Zhang, Yu Hu, Qing Lu, Tianchen Wang, Yiyu Shi, Meiping Huang, Xiaowe Xu

Deep neural networks (DNNs) have demonstrated their great potential in recent years, exceeding the per-formance of human experts in a wide range of applications.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +5

DPointNet: A Density-Oriented PointNet for 3D Object Detection in Point Clouds

no code implementations7 Feb 2021 Jie Li, Yu Hu

In this paper, we put forward a novel density-oriented PointNet (DPointNet) for 3D object detection in point clouds, in which the density of points increases layer by layer.

3D Object Detection Object +1

Model-based cellular kinetic analysis of SARS-CoV-2 infection: different immune response modes and treatment strategies

no code implementations12 Jan 2021 Zhengqing Zhou, Zhiheng Zhao, Shuyu Shi, Jianghua Wu, Dianjie Li, Jianwei Li, Jingpeng Zhang, Ke Gui, Yu Zhang, Heng Mei, Yu Hu, Qi Ouyang, Fangting Li

Integrating theoretical results with clinical COVID-19 patients' data, we classified the COVID-19 development processes into three typical modes of immune responses, correlated with the clinical classification of mild & moderate, severe and critical patients.

ALFA: Adversarial Feature Augmentation for Enhanced Image Recognition

no code implementations1 Jan 2021 Tianlong Chen, Yu Cheng, Zhe Gan, Yu Hu, Zhangyang Wang, Jingjing Liu

Adversarial training is an effective method to combat adversarial attacks in order to create robust neural networks.

Lip-reading with Hierarchical Pyramidal Convolution and Self-Attention

no code implementations28 Dec 2020 Hang Chen, Jun Du, Yu Hu, Li-Rong Dai, Chin-Hui Lee, Bao-Cai Yin

In this paper, we propose a novel deep learning architecture to improving word-level lip-reading.

Lip Reading

Tracking Interaction States for Multi-Turn Text-to-SQL Semantic Parsing

1 code implementation9 Dec 2020 Run-Ze Wang, Zhen-Hua Ling, Jing-Bo Zhou, Yu Hu

The dynamic schema-state and SQL-state representations are then utilized to decode the SQL query corresponding to current utterance.

Semantic Parsing Text-To-SQL

Correlating Subword Articulation with Lip Shapes for Embedding Aware Audio-Visual Speech Enhancement

no code implementations21 Sep 2020 Hang Chen, Jun Du, Yu Hu, Li-Rong Dai, Bao-Cai Yin, Chin-Hui Lee

We first extract visual embedding from lip frames using a pre-trained phone or articulation place recognizer for visual-only EASE (VEASE).

Speech Enhancement

A Density-Aware PointRCNN for 3D Object Detection in Point Clouds

no code implementations11 Sep 2020 Jie Li, Yu Hu

We present an improved version of PointRCNN for 3D object detection, in which a multi-branch backbone network is adopted to handle the non-uniform density of point clouds.

3D Object Detection object-detection

Barriers to grid-connected battery systems: Evidence from the Spanish electricity market

no code implementations28 Jun 2020 Yu Hu, David Soler Soneira, María Jesús Sánchez

The concept of "potentially profitable utilization time" is proposed and introduced to identify and evaluate future potential grid applications for battery systems.

Exploring Spatial-Temporal Multi-Frequency Analysis for High-Fidelity and Temporal-Consistency Video Prediction

1 code implementation CVPR 2020 Beibei Jin, Yu Hu, Qiankun Tang, Jingyu Niu, Zhiping Shi, Yinhe Han, Xiaowei Li

Inspired by the frequency band decomposition characteristic of Human Vision System (HVS), we propose a video prediction network based on multi-level wavelet analysis to deal with spatial and temporal information in a unified manner.

 Ranked #1 on Video Prediction on KTH (PSNR metric)

Video Generation Video Prediction

PosNeg-Balanced Anchors with Aligned Features for Single-Shot Object Detection

no code implementations9 Aug 2019 Qiankun Tang, Shice Liu, Jie Li, Yu Hu

We introduce a novel single-shot object detector to ease the imbalance of foreground-background class by suppressing the easy negatives while increasing the positives.

object-detection Object Detection +1

Integrating Tensor Similarity to Enhance Clustering Performance

no code implementations10 May 2019 Hong Peng, Yu Hu, Jiazhou Chen, Hai-Yan Wang, Yang Li, Hongmin Cai

The performance of most the clustering methods hinges on the used pairwise affinity, which is usually denoted by a similarity matrix.


See and Think: Disentangling Semantic Scene Completion

1 code implementation NeurIPS 2018 Shice Liu, Yu Hu, Yiming Zeng, Qiankun Tang, Beibei Jin, Yinhe Han, Xiaowei Li

Semantic scene completion predicts volumetric occupancy and object category of a 3D scene, which helps intelligent agents to understand and interact with the surroundings.

2D Semantic Segmentation 3D Semantic Scene Completion +2

Quantization of Fully Convolutional Networks for Accurate Biomedical Image Segmentation

no code implementations CVPR 2018 Xiaowei Xu, Qing Lu, Yu Hu, Lin Yang, Sharon Hu, Danny Chen, Yiyu Shi

Unlike existing litera- ture on quantization which primarily targets memory and computation complexity reduction, we apply quan- tization as a method to reduce over tting in FCNs for better accuracy.

Image Segmentation Quantization +2

Commonsense Knowledge Enhanced Embeddings for Solving Pronoun Disambiguation Problems in Winograd Schema Challenge

no code implementations13 Nov 2016 Quan Liu, Hui Jiang, Zhen-Hua Ling, Xiaodan Zhu, Si Wei, Yu Hu

The PDP task we investigate in this paper is a complex coreference resolution task which requires the utilization of commonsense knowledge.

coreference-resolution Test

Part-of-Speech Relevance Weights for Learning Word Embeddings

no code implementations24 Mar 2016 Quan Liu, Zhen-Hua Ling, Hui Jiang, Yu Hu

The model proposed in this paper paper jointly optimizes word vectors and the POS relevance matrices.

Learning Word Embeddings POS +2

Feedforward Sequential Memory Networks: A New Structure to Learn Long-term Dependency

no code implementations28 Dec 2015 Shiliang Zhang, Cong Liu, Hui Jiang, Si Wei, Li-Rong Dai, Yu Hu

In this paper, we propose a novel neural network structure, namely \emph{feedforward sequential memory networks (FSMN)}, to model long-term dependency in time series without using recurrent feedback.

Language Modelling speech-recognition +3

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