Search Results for author: Lu Zhang

Found 144 papers, 51 papers with code

Deep Feature Gaussian Processes for Single-Scene Aerosol Optical Depth Reconstruction

no code implementations27 May 2024 ShengJie Liu, Lu Zhang

Experiments on two AOD datasets with real-world cloud patterns showed that the proposed method outperformed deep CNN and random forest, achieving R$^2$ of 0. 7431 on MODIS AOD and R$^2$ of 0. 9211 on EMIT AOD, compared to deep CNN's R$^2$ of 0. 6507 and R$^2$ of 0. 8619.

Asymptotic Properties of the Distributional Synthetic Controls

no code implementations2 May 2024 Lu Zhang, Xiaomeng Zhang, Xinyu Zhang

This paper enhances our comprehension of the Distributional Synthetic Control (DSC) proposed by Gunsilius (2023), focusing on its asymptotic properties.

CORP: A Multi-Modal Dataset for Campus-Oriented Roadside Perception Tasks

no code implementations4 Apr 2024 Beibei Wang, Shuang Meng, Lu Zhang, Chenjie Wang, Jingjing Huang, Yao Li, Haojie Ren, Yuxuan Xiao, Yuru Peng, Jianmin Ji, Yu Zhang, Yanyong Zhang

Numerous roadside perception datasets have been introduced to propel advancements in autonomous driving and intelligent transportation systems research and development.

Autonomous Driving Instance Segmentation +1

Heterogeneous Peridynamic Neural Operators: Discover Biotissue Constitutive Law and Microstructure From Digital Image Correlation Measurements

no code implementations27 Mar 2024 Siavash Jafarzadeh, Stewart Silling, Lu Zhang, Colton Ross, Chung-Hao Lee, S. M. Rakibur Rahman, Shuodao Wang, Yue Yu

Then, in the second phase we reinitialize the learnt bond force and the kernel function, and training them together with a fiber orientation field for each material point.

Boosting Continual Learning of Vision-Language Models via Mixture-of-Experts Adapters

1 code implementation18 Mar 2024 Jiazuo Yu, Yunzhi Zhuge, Lu Zhang, Dong Wang, Huchuan Lu, You He

Continual learning can empower vision-language models to continuously acquire new knowledge, without the need for access to the entire historical dataset.

Continual Learning Incremental Learning +1

Real-time Transformer-based Open-Vocabulary Detection with Efficient Fusion Head

1 code implementation11 Mar 2024 Tiancheng Zhao, Peng Liu, Xuan He, Lu Zhang, Kyusong Lee

End-to-end transformer-based detectors (DETRs) have shown exceptional performance in both closed-set and open-vocabulary object detection (OVD) tasks through the integration of language modalities.

Object object-detection +2

Long-Term Fair Decision Making through Deep Generative Models

1 code implementation20 Jan 2024 Yaowei Hu, Yongkai Wu, Lu Zhang

This paper studies long-term fair machine learning which aims to mitigate group disparity over the long term in sequential decision-making systems.

Decision Making Fairness

Striking a Balance in Fairness for Dynamic Systems Through Reinforcement Learning

1 code implementation12 Jan 2024 Yaowei Hu, Jacob Lear, Lu Zhang

While significant advancements have been made in the field of fair machine learning, the majority of studies focus on scenarios where the decision model operates on a static population.

Fairness reinforcement-learning

Scene 3-D Reconstruction System in Scattering Medium

no code implementations14 Dec 2023 Zhuoyifan Zhang, Lu Zhang, Liang Wang, Haoming Wu

The research on neural radiance fields for new view synthesis has experienced explosive growth with the development of new models and extensions.

3D Reconstruction Pose Estimation

Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel

no code implementations2 Nov 2023 Xuan Li, Zhanke Zhou, Jiangchao Yao, Yu Rong, Lu Zhang, Bo Han

To tackle this issue, we propose a method to abstract the collective information of atomic groups into a few $\textit{Neural Atoms}$ by implicitly projecting the atoms of a molecular.

Drug Discovery

Video Frame Interpolation with Many-to-many Splatting and Spatial Selective Refinement

no code implementations29 Oct 2023 Ping Hu, Simon Niklaus, Lu Zhang, Stan Sclaroff, Kate Saenko

In this work, we first propose a fully differentiable Many-to-Many (M2M) splatting framework to interpolate frames efficiently.

Computational Efficiency Motion Estimation +1

PathRL: An End-to-End Path Generation Method for Collision Avoidance via Deep Reinforcement Learning

no code implementations20 Oct 2023 Wenhao Yu, Jie Peng, Quecheng Qiu, Hanyu Wang, Lu Zhang, Jianmin Ji

However, two roadblocks arise for training a DRL policy that outputs paths: (1) The action space for potential paths often involves higher dimensions comparing to low-level commands, which increases the difficulties of training; (2) It takes multiple time steps to track a path instead of a single time step, which requires the path to predicate the interactions of the robot w. r. t.

Collision Avoidance Robot Navigation

Magicremover: Tuning-free Text-guided Image inpainting with Diffusion Models

no code implementations4 Oct 2023 Siyuan Yang, Lu Zhang, Liqian Ma, Yu Liu, Jingjing Fu, You He

In this paper, we propose MagicRemover, a tuning-free method that leverages the powerful diffusion models for text-guided image inpainting.

Denoising Image Inpainting

Algorithmic Recourse for Anomaly Detection in Multivariate Time Series

no code implementations28 Sep 2023 Xiao Han, Lu Zhang, Yongkai Wu, Shuhan Yuan

Anomaly detection in multivariate time series has received extensive study due to the wide spectrum of applications.

Anomaly Detection Time Series +1

Short-term power load forecasting method based on CNN-SAEDN-Res

no code implementations2 Sep 2023 Yang Cui, Han Zhu, Yijian Wang, Lu Zhang, Yang Li

In this method, feature extraction module is composed of a two-dimensional convolutional neural network, which is used to mine the local correlation between data and obtain high-dimensional data features.

Decoder Load Forecasting +1

Meta-learning enhanced next POI recommendation by leveraging check-ins from auxiliary cities

1 code implementation18 Aug 2023 Jinze Wang, Lu Zhang, Zhu Sun, Yew-Soon Ong

Particularly, a city-level correlation strategy is devised to attentively capture common patterns among cities, so as to transfer more relevant knowledge from more correlated cities.

Meta-Learning

Tracking Anything in High Quality

1 code implementation26 Jul 2023 Jiawen Zhu, Zhenyu Chen, Zeqi Hao, Shijie Chang, Lu Zhang, Dong Wang, Huchuan Lu, Bin Luo, Jun-Yan He, Jin-Peng Lan, Hanyuan Chen, Chenyang Li

To further improve the quality of tracking masks, a pretrained MR model is employed to refine the tracking results.

Object Semantic Segmentation +3

Exploiting Field Dependencies for Learning on Categorical Data

1 code implementation18 Jul 2023 Zhibin Li, Piotr Koniusz, Lu Zhang, Daniel Edward Pagendam, Peyman Moghadam

Instead of modelling statistics of features globally (i. e., by the covariance matrix of features), we learn a global field dependency matrix that captures dependencies between fields and then we refine the global field dependency matrix at the instance-wise level with different weights (so-called local dependency modelling) w. r. t.

Meta-Learning

Segment Anything Model (SAM) for Radiation Oncology

no code implementations20 Jun 2023 Lian Zhang, Zhengliang Liu, Lu Zhang, Zihao Wu, Xiaowei Yu, Jason Holmes, Hongying Feng, Haixing Dai, Xiang Li, Quanzheng Li, Dajiang Zhu, Tianming Liu, Wei Liu

Given that SAM, a model pre-trained purely on natural images, can handle the delineation of OARs from medical images with clinically acceptable accuracy, these results highlight SAM's robust generalization capabilities with consistent accuracy in automatic segmentation for radiotherapy.

Segmentation

Artificial General Intelligence for Medical Imaging

no code implementations8 Jun 2023 Xiang Li, Lu Zhang, Zihao Wu, Zhengliang Liu, Lin Zhao, Yixuan Yuan, Jun Liu, Gang Li, Dajiang Zhu, Pingkun Yan, Quanzheng Li, Wei Liu, Tianming Liu, Dinggang Shen

In this review, we explore the potential applications of Artificial General Intelligence (AGI) models in healthcare, focusing on foundational Large Language Models (LLMs), Large Vision Models, and Large Multimodal Models.

Video Diffusion Models with Local-Global Context Guidance

1 code implementation5 Jun 2023 Siyuan Yang, Lu Zhang, Yu Liu, Zhizhuo Jiang, You He

We construct a local-global context guidance strategy to capture the multi-perceptual embedding of the past fragment to boost the consistency of future prediction.

Future prediction Unconditional Video Generation +1

Instruction-ViT: Multi-Modal Prompts for Instruction Learning in ViT

no code implementations29 Apr 2023 Zhenxiang Xiao, Yuzhong Chen, Lu Zhang, Junjie Yao, Zihao Wu, Xiaowei Yu, Yi Pan, Lin Zhao, Chong Ma, Xinyu Liu, Wei Liu, Xiang Li, Yixuan Yuan, Dinggang Shen, Dajiang Zhu, Tianming Liu, Xi Jiang

Prompts have been proven to play a crucial role in large language models, and in recent years, vision models have also been using prompts to improve scalability for multiple downstream tasks.

Image Classification

Exploring the Trade-Offs: Unified Large Language Models vs Local Fine-Tuned Models for Highly-Specific Radiology NLI Task

no code implementations18 Apr 2023 Zihao Wu, Lu Zhang, Chao Cao, Xiaowei Yu, Haixing Dai, Chong Ma, Zhengliang Liu, Lin Zhao, Gang Li, Wei Liu, Quanzheng Li, Dinggang Shen, Xiang Li, Dajiang Zhu, Tianming Liu

To this end, in this study, we evaluate the performance of ChatGPT/GPT-4 on a radiology NLI task and compare it to other models fine-tuned specifically on task-related data samples.

Specificity Task 2

HGCC: Enhancing Hyperbolic Graph Convolution Networks on Heterogeneous Collaborative Graph for Recommendation

no code implementations6 Apr 2023 Lu Zhang, Ning Wu

Due to the naturally power-law distributed nature of user-item interaction data in recommendation tasks, hyperbolic space modeling has recently been introduced into collaborative filtering methods.

Collaborative Filtering

When Brain-inspired AI Meets AGI

no code implementations28 Mar 2023 Lin Zhao, Lu Zhang, Zihao Wu, Yuzhong Chen, Haixing Dai, Xiaowei Yu, Zhengliang Liu, Tuo Zhang, Xintao Hu, Xi Jiang, Xiang Li, Dajiang Zhu, Dinggang Shen, Tianming Liu

Artificial General Intelligence (AGI) has been a long-standing goal of humanity, with the aim of creating machines capable of performing any intellectual task that humans can do.

In-Context Learning

Core-Periphery Principle Guided Redesign of Self-Attention in Transformers

no code implementations27 Mar 2023 Xiaowei Yu, Lu Zhang, Haixing Dai, Yanjun Lyu, Lin Zhao, Zihao Wu, David Liu, Tianming Liu, Dajiang Zhu

Designing more efficient, reliable, and explainable neural network architectures is critical to studies that are based on artificial intelligence (AI) techniques.

DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4

1 code implementation20 Mar 2023 Zhengliang Liu, Yue Huang, Xiaowei Yu, Lu Zhang, Zihao Wu, Chao Cao, Haixing Dai, Lin Zhao, Yiwei Li, Peng Shu, Fang Zeng, Lichao Sun, Wei Liu, Dinggang Shen, Quanzheng Li, Tianming Liu, Dajiang Zhu, Xiang Li

The digitization of healthcare has facilitated the sharing and re-using of medical data but has also raised concerns about confidentiality and privacy.

Benchmarking De-identification +4

Refined Pseudo labeling for Source-free Domain Adaptive Object Detection

no code implementations7 Mar 2023 Siqi Zhang, Lu Zhang, Zhiyong Liu

Domain adaptive object detection (DAOD) assumes that both labeled source data and unlabeled target data are available for training, but this assumption does not always hold in real-world scenarios.

object-detection Object Detection +1

FIT: Frequency-based Image Translation for Domain Adaptive Object Detection

no code implementations7 Mar 2023 Siqi Zhang, Lu Zhang, Zhiyong Liu, Hangtao Feng

Domain adaptive object detection (DAOD) aims to adapt the detector from a labelled source domain to an unlabelled target domain.

object-detection Object Detection +1

Achieving Counterfactual Fairness for Anomaly Detection

1 code implementation4 Mar 2023 Xiao Han, Lu Zhang, Yongkai Wu, Shuhan Yuan

Ensuring fairness in anomaly detection models has received much attention recently as many anomaly detection applications involve human beings.

Anomaly Detection counterfactual +1

NR Conformance Testing of Analog Radio-over-LWIR FSO Fronthaul link for 6G Distributed MIMO Networks

no code implementations9 Feb 2023 Rafael Puerta, Mengyao Han, Mahdieh Joharifar, Richard Schatz, Yan-Ting Sun, Yuchuan Fan, Anders Djupsjöbacka, Grégory Maisons, Johan Abautret, Roland Teissier, Lu Zhang, Sandis Spolitis, Muguang Wang, Vjaceslavs Bobrovs, Sebastian Lourdudoss, Xianbin Yu, Sergei Popov, Oskars Ozolins, Xiaodan Pang

We experimentally test the compliance with 5G/NR 3GPP technical specifications of an analog radio-over-FSO link at 9 {\mu}m. The ACLR and EVM transmitter requirements are fulfilled validating the suitability of LWIR FSO for 6G fronthaul.

Gyri vs. Sulci: Disentangling Brain Core-Periphery Functional Networks via Twin-Transformer

no code implementations31 Jan 2023 Xiaowei Yu, Lu Zhang, Haixing Dai, Lin Zhao, Yanjun Lyu, Zihao Wu, Tianming Liu, Dajiang Zhu

To solve this fundamental problem, we design a novel Twin-Transformer framework to unveil the unique functional roles of gyri and sulci as well as their relationship in the whole brain function.

Anatomy

MetaNO: How to Transfer Your Knowledge on Learning Hidden Physics

no code implementations28 Jan 2023 Lu Zhang, Huaiqian You, Tian Gao, Mo Yu, Chung-Hao Lee, Yue Yu

Gradient-based meta-learning methods have primarily been applied to classical machine learning tasks such as image classification.

Image Classification Meta-Learning

Objective quality assessment of medical images and videos: Review and challenges

no code implementations14 Dec 2022 Rafael Rodrigues, Lucie Lévêque, Jesús Gutiérrez, Houda Jebbari, Meriem Outtas, Lu Zhang, Aladine Chetouani, Shaymaa Al-Juboori, Maria Martini, Antonio M. G. Pinheiro

Quality assessment is a key element for the evaluation of hardware and software involved in image and video acquisition, processing, and visualization.

On Root Cause Localization and Anomaly Mitigation through Causal Inference

1 code implementation8 Dec 2022 Xiao Han, Lu Zhang, Yongkai Wu, Shuhan Yuan

After that, we further propose an anomaly mitigation approach that aims to recommend mitigation actions on abnormal features to revert the abnormal outcomes such that the counterfactuals guided by the causal mechanism are normal.

Anomaly Detection Causal Inference

Generating Textual Adversaries with Minimal Perturbation

1 code implementation12 Nov 2022 Xingyi Zhao, Lu Zhang, Depeng Xu, Shuhan Yuan

Many word-level adversarial attack approaches for textual data have been proposed in recent studies.

Adversarial Attack

ISA-Net: Improved spatial attention network for PET-CT tumor segmentation

no code implementations4 Nov 2022 Zhengyong Huang, Sijuan Zou, Guoshuai Wang, Zixiang Chen, Hao Shen, HaiYan Wang, Na Zhang, Lu Zhang, Fan Yang, Haining Wangg, Dong Liang, Tianye Niu, Xiaohua Zhuc, Zhanli Hua

In this paper, we propose a deep learning segmentation method based on multimodal positron emission tomography-computed tomography (PET-CT), which combines the high sensitivity of PET and the precise anatomical information of CT. We design an improved spatial attention network(ISA-Net) to increase the accuracy of PET or CT in detecting tumors, which uses multi-scale convolution operation to extract feature information and can highlight the tumor region location information and suppress the non-tumor region location information.

Segmentation STS +1

BI AVAN: Brain inspired Adversarial Visual Attention Network

no code implementations27 Oct 2022 Heng Huang, Lin Zhao, Xintao Hu, Haixing Dai, Lu Zhang, Dajiang Zhu, Tianming Liu

Visual attention is a fundamental mechanism in the human brain, and it inspires the design of attention mechanisms in deep neural networks.

Data-Driven Joint Inversions for PDE Models

no code implementations17 Oct 2022 Kui Ren, Lu Zhang

The task of simultaneously reconstructing multiple physical coefficients in partial differential equations from observed data is ubiquitous in applications.

Hierarchical Few-Shot Object Detection: Problem, Benchmark and Method

1 code implementation8 Oct 2022 Lu Zhang, Yang Wang, Jiaogen Zhou, Chenbo Zhang, Yinglu Zhang, Jihong Guan, Yatao Bian, Shuigeng Zhou

In this paper, we propose and solve a new problem called hierarchical few-shot object detection (Hi-FSOD), which aims to detect objects with hierarchical categories in the FSOD paradigm.

Contrastive Learning Few-Shot Object Detection +2

Cascaded Multi-Modal Mixing Transformers for Alzheimer's Disease Classification with Incomplete Data

no code implementations1 Oct 2022 Linfeng Liu, Siyu Liu, Lu Zhang, Xuan Vinh To, Fatima Nasrallah, Shekhar S. Chandra

The model uses a novel Cascaded Modality Transformer architecture with cross-attention to incorporate multi-modal information for more informed predictions.

A Multi-Channel Next POI Recommendation Framework with Multi-Granularity Check-in Signals

1 code implementation1 Sep 2022 Zhu Sun, Yu Lei, Lu Zhang, Chen Li, Yew-Soon Ong, Jie Zhang

Being equipped with three modules (i. e., global user behavior encoder, local multi-channel encoder, and region-aware weighting strategy), MCMG is capable of capturing both fine- and coarse-grained sequential regularities as well as exploring the dynamic impact of multi-channel by differentiating the region check-in patterns.

Automatically Discovering Novel Visual Categories with Self-supervised Prototype Learning

1 code implementation1 Aug 2022 Lu Zhang, Lu Qi, Xu Yang, Hong Qiao, Ming-Hsuan Yang, Zhiyong Liu

In the first stage, we obtain a robust feature extractor, which could serve for all images with base and novel categories.

Representation Learning Self-Supervised Learning

Intra-Modal Constraint Loss For Image-Text Retrieval

1 code implementation11 Jul 2022 Jianan Chen, Lu Zhang, Qiong Wang, Cong Bai, Kidiyo Kpalma

Cross-modal retrieval has drawn much attention in both computer vision and natural language processing domains.

Cross-Modal Retrieval Retrieval +1

Coupling Visual Semantics of Artificial Neural Networks and Human Brain Function via Synchronized Activations

no code implementations22 Jun 2022 Lin Zhao, Haixing Dai, Zihao Wu, Zhenxiang Xiao, Lu Zhang, David Weizhong Liu, Xintao Hu, Xi Jiang, Sheng Li, Dajiang Zhu, Tianming Liu

However, whether there exists semantic correlations/connections between the visual representations in ANNs and those in BNNs remains largely unexplored due to both the lack of an effective tool to link and couple two different domains, and the lack of a general and effective framework of representing the visual semantics in BNNs such as human functional brain networks (FBNs).

Image Classification Representation Learning

Zero-shot object goal visual navigation

1 code implementation15 Jun 2022 Qianfan Zhao, Lu Zhang, Bin He, Hong Qiao, Zhiyong Liu

Object goal visual navigation is a challenging task that aims to guide a robot to find the target object based on its visual observation, and the target is limited to the classes pre-defined in the training stage.

Knowledge Graphs Object +5

MetaNOR: A Meta-Learnt Nonlocal Operator Regression Approach for Metamaterial Modeling

no code implementations4 Jun 2022 Lu Zhang, Huaiqian You, Yue Yu

We propose MetaNOR, a meta-learnt approach for transfer-learning operators based on the nonlocal operator regression.

regression Transfer Learning

Representing Brain Anatomical Regularity and Variability by Few-Shot Embedding

no code implementations26 May 2022 Lu Zhang, Xiaowei Yu, Yanjun Lyu, Zhengwang Wu, Haixing Dai, Lin Zhao, Li Wang, Gang Li, Tianming Liu, Dajiang Zhu

Our experimental results show that: 1) the learned embedding vectors can quantitatively encode the commonality and individuality of cortical folding patterns; 2) with the embeddings we can robustly infer the complicated many-to-many anatomical correspondences among different brains and 3) our model can be successfully transferred to new populations with very limited training samples.

Few-Shot Learning

Eye-gaze-guided Vision Transformer for Rectifying Shortcut Learning

no code implementations25 May 2022 Chong Ma, Lin Zhao, Yuzhong Chen, Lu Zhang, Zhenxiang Xiao, Haixing Dai, David Liu, Zihao Wu, Zhengliang Liu, Sheng Wang, Jiaxing Gao, Changhe Li, Xi Jiang, Tuo Zhang, Qian Wang, Dinggang Shen, Dajiang Zhu, Tianming Liu

To address this problem, we propose to infuse human experts' intelligence and domain knowledge into the training of deep neural networks.

A Unified and Biologically-Plausible Relational Graph Representation of Vision Transformers

no code implementations20 May 2022 Yuzhong Chen, Yu Du, Zhenxiang Xiao, Lin Zhao, Lu Zhang, David Weizhong Liu, Dajiang Zhu, Tuo Zhang, Xintao Hu, Tianming Liu, Xi Jiang

The key characteristic of these ViT models is to adopt different aggregation strategies of spatial patch information within the artificial neural networks (ANNs).

Mask-guided Vision Transformer (MG-ViT) for Few-Shot Learning

no code implementations20 May 2022 Yuzhong Chen, Zhenxiang Xiao, Lin Zhao, Lu Zhang, Haixing Dai, David Weizhong Liu, Zihao Wu, Changhe Li, Tuo Zhang, Changying Li, Dajiang Zhu, Tianming Liu, Xi Jiang

However, for data-intensive models such as vision transformer (ViT), current fine-tuning based FSL approaches are inefficient in knowledge generalization and thus degenerate the downstream task performances.

Active Learning Few-Shot Learning

TJ4DRadSet: A 4D Radar Dataset for Autonomous Driving

1 code implementation28 Apr 2022 Lianqing Zheng, Zhixiong Ma, Xichan Zhu, Bin Tan, Sen Li, Kai Long, Weiqi Sun, Sihan Chen, Lu Zhang, Mengyue Wan, Libo Huang, Jie Bai

The next-generation high-resolution automotive radar (4D radar) can provide additional elevation measurement and denser point clouds, which has great potential for 3D sensing in autonomous driving.

3D Object Detection Autonomous Driving +1

EPiDA: An Easy Plug-in Data Augmentation Framework for High Performance Text Classification

no code implementations NAACL 2022 Minyi Zhao, Lu Zhang, Yi Xu, Jiandong Ding, Jihong Guan, Shuigeng Zhou

However, to the best of our knowledge, most existing methods consider only either the diversity or the quality of augmented data, thus cannot fully mine the potential of DA for NLP.

Data Augmentation text-classification +1

Unseen Object Instance Segmentation with Fully Test-time RGB-D Embeddings Adaptation

no code implementations21 Apr 2022 Lu Zhang, Siqi Zhang, Xu Yang, Hong Qiao, Zhiyong Liu

In this paper, we emphasize the adaptation process across sim2real domains and model it as a learning problem on the BatchNorm parameters of a simulation-trained model.

Knowledge Distillation Segmentation +4

Weakly Aligned Feature Fusion for Multimodal Object Detection

no code implementations21 Apr 2022 Lu Zhang, Zhiyong Liu, Xiangyu Zhu, Zhan Song, Xu Yang, Zhen Lei, Hong Qiao

In this article, we propose a general multimodal detector named aligned region CNN (AR-CNN) to tackle the position shift problem.

Object object-detection +2

Disentangling Spatial-Temporal Functional Brain Networks via Twin-Transformers

no code implementations20 Apr 2022 Xiaowei Yu, Lu Zhang, Lin Zhao, Yanjun Lyu, Tianming Liu, Dajiang Zhu

In this work, we propose a novel Twin-Transformers framework to simultaneously infer common and individual functional networks in both spatial and temporal space, in a self-supervised manner.

Achieving Long-Term Fairness in Sequential Decision Making

1 code implementation4 Apr 2022 Yaowei Hu, Lu Zhang

The problem of fair sequential decision making is then formulated as a constrained optimization problem with the utility as the objective and the long-term and short-term fairness as constraints.

Decision Making Fairness

Recent Few-Shot Object Detection Algorithms: A Survey with Performance Comparison

no code implementations27 Mar 2022 Tianying Liu, Lu Zhang, Yang Wang, Jihong Guan, Yanwei Fu, Jiajia Zhao, Shuigeng Zhou

To this end, the Few-Shot Object Detection (FSOD) has been topical recently, as it mimics the humans' ability of learning to learn, and intelligently transfers the learned generic object knowledge from the common heavy-tailed, to the novel long-tailed object classes.

Few-Shot Object Detection Meta-Learning +3

Series Photo Selection via Multi-view Graph Learning

no code implementations18 Mar 2022 Jin Huang, Lu Zhang, Yongshun Gong, Jian Zhang, Xiushan Nie, Yilong Yin

Series photo selection (SPS) is an important branch of the image aesthetics quality assessment, which focuses on finding the best one from a series of nearly identical photos.

Aesthetics Quality Assessment Graph Learning

Hyperspectral Imaging for cherry tomato

no code implementations10 Mar 2022 Yun Xiang, Qijun Chen, Zhongjin Su, Lu Zhang, Zuohui Chen, Guozhi Zhou, Zhuping Yao, Qi Xuan, Yuan Cheng

Cherry tomato (Solanum Lycopersicum) is popular with consumers over the world due to its special flavor.

regression

Transformer-based Network for RGB-D Saliency Detection

no code implementations1 Dec 2021 Yue Wang, Xu Jia, Lu Zhang, Yuke Li, James Elder, Huchuan Lu

TFFM conducts a sufficient feature fusion by integrating features from multiple scales and two modalities over all positions simultaneously.

Saliency Detection

SAFA: Structure Aware Face Animation

1 code implementation9 Nov 2021 Qiulin Wang, Lu Zhang, Bo Li

On the other hand, some area of the generated image might be occluded in the source image, which makes it difficult for GAN to generate realistic appearance.

Trajectory Prediction with Graph-based Dual-scale Context Fusion

1 code implementation2 Nov 2021 Lu Zhang, Peiliang Li, Jing Chen, Shaojie Shen

In this paper, we present a graph-based trajectory prediction network named the Dual Scale Predictor (DSP), which encodes both the static and dynamical driving context in a hierarchical manner.

Motion Forecasting motion prediction +1

DP-SSL: Towards Robust Semi-supervised Learning with A Few Labeled Samples

no code implementations NeurIPS 2021 Yi Xu, Jiandong Ding, Lu Zhang, Shuigeng Zhou

Extensive experiments on four standard SSL benchmarks show that DP-SSL can provide reliable labels for unlabeled data and achieve better classification performance on test sets than existing SSL methods, especially when only a small number of labeled samples are available.

Multiple-choice Semi-Supervised Image Classification

Weakly-supervised Text Classification Based on Keyword Graph

1 code implementation EMNLP 2021 Lu Zhang, Jiandong Ding, Yi Xu, Yingyao Liu, Shuigeng Zhou

Among them, keyword-driven methods are the mainstream where user-provided keywords are exploited to generate pseudo-labels for unlabeled texts.

text-classification Text Classification

Achieving Counterfactual Fairness for Causal Bandit

no code implementations21 Sep 2021 Wen Huang, Lu Zhang, Xintao Wu

In online recommendation, customers arrive in a sequential and stochastic manner from an underlying distribution and the online decision model recommends a chosen item for each arriving individual based on some strategy.

Causal Inference counterfactual +1

A review of computational tools for generating metagenome-assembled genomes from metagenomic sequencing data

no code implementations2 Sep 2021 Chao Yang, Debajyoti Chowdhury, Zhenmiao Zhang, William K. Cheung, Aiping Lu, Zhao Xiang Bian, Lu Zhang

Metagenomics has equipped us with new avenues of investigating the microbiome, from studying a single species to a complex community in a dynamic ecosystem.

Cultural Vocal Bursts Intensity Prediction

Lyra: A Benchmark for Turducken-Style Code Generation

1 code implementation27 Aug 2021 Qingyuan Liang, Zeyu Sun, Qihao Zhu, Wenjie Zhang, Lian Yu, Yingfei Xiong, Lu Zhang

Since a declarative language is typically embedded in an imperative language (i. e., the turducken-style programming) in real-world software development, the promising results on declarative languages can hardly lead to significant reduction of manual software development efforts.

Code Generation

Pathfinder: Parallel quasi-Newton variational inference

5 code implementations9 Aug 2021 Lu Zhang, Bob Carpenter, Andrew Gelman, Aki Vehtari

Pathfinder returns draws from the approximation with the lowest estimated Kullback-Leibler (KL) divergence to the true posterior.

Pathfinder Variational Inference

Multi-Task Audio Source Separation

1 code implementation14 Jul 2021 Lu Zhang, Chenxing Li, Feng Deng, Xiaorui Wang

In detail, the proposed model follows a two-stage pipeline, which separates the three types of audio signals and then performs signal compensation separately.

Audio Source Separation Multi-task Audio Source Seperation +3

Incorporating Multi-Target in Multi-Stage Speech Enhancement Model for Better Generalization

no code implementations9 Jul 2021 Lu Zhang, Mingjiang Wang, Andong Li, Zehua Zhang, Xuyi Zhuang

In this study, we make full use of the contribution of multi-target joint learning to the model generalization capability, and propose a lightweight and low-computing dilated convolutional network (DCN) model for a more robust speech denoising task.

Denoising Speech Denoising +1

Accurate Few-Shot Object Detection With Support-Query Mutual Guidance and Hybrid Loss

no code implementations CVPR 2021 Lu Zhang, Shuigeng Zhou, Jihong Guan, Ji Zhang

Most object detection methods require huge amounts of annotated data and can detect only the categories that appear in the training set.

Few-Shot Object Detection object-detection

A Syntax-Guided Edit Decoder for Neural Program Repair

1 code implementation15 Jun 2021 Qihao Zhu, Zeyu Sun, Yuan-an Xiao, Wenjie Zhang, Kang Yuan, Yingfei Xiong, Lu Zhang

Our results show that Recoder repairs 53 bugs on Defects4J v1. 2, which achieves 21. 4% improvement over the previous state-of-the-art approach for single-hunk bugs (TBar).

Code Completion Code Generation +2

Representative Functional Connectivity Learning for Multiple Clinical groups in Alzheimer's Disease

no code implementations14 Jun 2021 Lu Zhang, Xiaowei Yu, Yanjun Lyu, Li Wang, Dajiang Zhu

By mapping the learned clinical group related feature vectors to the original FC space, representative FCs were constructed for each group.

Multi-class Classification

Deep Interaction between Masking and Mapping Targets for Single-Channel Speech Enhancement

no code implementations9 Jun 2021 Lu Zhang, Mingjiang Wang, Zehua Zhang, Xuyi Zhuang

In this paper, we propose a multi-branch dilated convolutional network (DCN) to simultaneously enhance the magnitude and phase of noisy speech.

Denoising Speech Enhancement

SHD360: A Benchmark Dataset for Salient Human Detection in 360° Videos

1 code implementation24 May 2021 Yi Zhang, Lu Zhang, Kang Wang, Wassim Hamidouche, Olivier Deforges

Salient human detection (SHD) in dynamic 360{\deg} immersive videos is of great importance for various applications such as robotics, inter-human and human-object interaction in augmented reality.

Human Detection Human-Object Interaction Detection +3

An Efficient Network Solver for Dynamic Simulation of Power Systems Based on Hierarchical Inverse Computation and Modification

no code implementations22 May 2021 Lu Zhang, Bin Wang, Vivek Sarin, Weiping Shi, P. R. Kumar, Le Xie

In power system dynamic simulation, up to 90% of the computational time is devoted to solve the network equations, i. e., a set of linear equations.

CMA-Net: A Cascaded Mutual Attention Network for Light Field Salient Object Detection

1 code implementation3 May 2021 Yi Zhang, Lu Zhang, Wassim Hamidouche, Olivier Deforges

In the past few years, numerous deep learning methods have been proposed to address the task of segmenting salient objects from RGB images.

object-detection Object Detection +1

Learning Synergistic Attention for Light Field Salient Object Detection

1 code implementation28 Apr 2021 Yi Zhang, Geng Chen, Qian Chen, Yujia Sun, Yong Xia, Olivier Deforges, Wassim Hamidouche, Lu Zhang

We propose a novel Synergistic Attention Network (SA-Net) to address the light field salient object detection by establishing a synergistic effect between multi-modal features with advanced attention mechanisms.

Object object-detection +2

Generalized Equivariance and Preferential Labeling for GNN Node Classification

1 code implementation23 Feb 2021 Zeyu Sun, Wenjie Zhang, Lili Mou, Qihao Zhu, Yingfei Xiong, Lu Zhang

Existing graph neural networks (GNNs) largely rely on node embeddings, which represent a node as a vector by its identity, type, or content.

General Classification Graph Classification +1

Disease2Vec: Representing Alzheimer's Progression via Disease Embedding Tree

no code implementations13 Feb 2021 Lu Zhang, Li Wang, Tianming Liu, Dajiang Zhu

By disease em-bedding, the framework generates a disease embedding tree (DETree) which effectively represents different clinical stages as a tree trajectory reflecting AD progression and thus can be used to predict clinical status by projecting individuals onto this continuous trajectory.

Multi-class Classification

A comprehensive study on the semileptonic decay of heavy flavor mesons

no code implementations8 Dec 2020 Lu Zhang, Xian-Wei Kang, Xin-Heng Guo, Ling-Yun Dai, Tao Luo, Chao Wang

The semileptonic decay of heavy flavor mesons offers a clean environment for extraction of the Cabibbo-Kobayashi-Maskawa (CKM) matrix elements, which describes the CP-violating and flavor changing process in the Standard Model.

High Energy Physics - Phenomenology High Energy Physics - Experiment

A Unified Model for Gate Level Propagation Analysis

no code implementations7 Dec 2020 Jeremy Blackstone, Wei Hu, Alric Althoff, Armaiti Ardeshiricham, Lu Zhang, Ryan Kastner

To justify our model, we prove that Precise Hardware IFT is equivalent to gate level X-propagation and imprecise fault propagation.

Hardware Architecture

MCMH: Learning Multi-Chain Multi-Hop Rules for Knowledge Graph Reasoning

no code implementations Findings of the Association for Computational Linguistics 2020 Lu Zhang, Mo Yu, Tian Gao, Yue Yu

Multi-hop reasoning approaches over knowledge graphs infer a missing relationship between entities with a multi-hop rule, which corresponds to a chain of relationships.

Knowledge Graphs Relation

OCoR: An Overlapping-Aware Code Retriever

2 code implementations12 Aug 2020 Qihao Zhu, Zeyu Sun, Xiran Liang, Yingfei Xiong, Lu Zhang

To address these problems, we propose a novel neural architecture named OCoR, where we introduce two specifically-designed components to capture overlaps: the first embeds identifiers by character to capture the overlaps between identifiers, and the second introduces a novel overlap matrix to represent the degrees of overlaps between each natural language word and each identifier.

Retrieval

ModeNet: Mode Selection Network For Learned Video Coding

no code implementations6 Jul 2020 Théo Ladune, Pierrick Philippe, Wassim Hamidouche, Lu Zhang, Olivier Déforges

In this paper, a mode selection network (ModeNet) is proposed to enhance deep learning-based video compression.

Image Compression Video Compression

Synergistic saliency and depth prediction for RGB-D saliency detection

no code implementations3 Jul 2020 Yue Wang, Yuke Li, James H. Elder, Huchuan Lu, Runmin Wu, Lu Zhang

Evaluation on seven RGB-D datasets demonstrates that even without saliency ground truth for RGB-D datasets and using only the RGB data of RGB-D datasets at inference, our semi-supervised system performs favorable against state-of-the-art fully-supervised RGB-D saliency detection methods that use saliency ground truth for RGB-D datasets at training and depth data at inference on two largest testing datasets.

Depth Estimation Depth Prediction +1

Floodgate: inference for model-free variable importance

1 code implementation2 Jul 2020 Lu Zhang, Lucas Janson

Many modern applications seek to understand the relationship between an outcome variable $Y$ and a covariate $X$ in the presence of a (possibly high-dimensional) confounding variable $Z$.

Methodology

Semantic-driven Colorization

1 code implementation13 Jun 2020 Man M. Ho, Lu Zhang, Alexander Raake, Jinjia Zhou

As a human experience in colorization, our brains first detect and recognize the objects in the photo, then imagine their plausible colors based on many similar objects we have seen in real life, and finally colorize them, as described in the teaser.

Colorization

Towards Better Graph Representation: Two-Branch Collaborative Graph Neural Networks for Multimodal Marketing Intention Detection

no code implementations13 May 2020 Lu Zhang, Jian Zhang, Zhibin Li, Jingsong Xu

Inspired by the fact that spreading and collecting information through the Internet becomes the norm, more and more people choose to post for-profit contents (images and texts) in social networks.

Graph Classification Marketing

Efficient Uncertainty-aware Decision-making for Automated Driving Using Guided Branching

2 code implementations5 Mar 2020 Lu Zhang, Wenchao Ding, Jing Chen, Shaojie Shen

Decision-making in dense traffic scenarios is challenging for automated vehicles (AVs) due to potentially stochastic behaviors of other traffic participants and perception uncertainties (e. g., tracking noise and prediction errors, etc.).

Robotics

Binary Probability Model for Learning Based Image Compression

no code implementations21 Feb 2020 Théo Ladune, Pierrick Philippe, Wassim Hamidouche, Lu Zhang, Olivier Deforges

In this paper, we propose to enhance learned image compression systems with a richer probability model for the latent variables.

Image Compression

NLocalSAT: Boosting Local Search with Solution Prediction

1 code implementation26 Jan 2020 Wenjie Zhang, Zeyu Sun, Qihao Zhu, Ge Li, Shaowei Cai, Yingfei Xiong, Lu Zhang

However, in this method, the initialization is assigned in a random manner, which impacts the effectiveness of SLS solvers.

A Fixation-based 360° Benchmark Dataset for Salient Object Detection

2 code implementations22 Jan 2020 Yi Zhang, Lu Zhang, Wassim Hamidouche, Olivier Deforges

Experimental results show a limitation of the current methods when used for SOD in panoramic images, which indicates the proposed dataset is challenging.

object-detection RGB Salient Object Detection +1

TreeGen: A Tree-Based Transformer Architecture for Code Generation

2 code implementations22 Nov 2019 Zeyu Sun, Qihao Zhu, Yingfei Xiong, Yican Sun, Lili Mou, Lu Zhang

TreeGen outperformed the previous state-of-the-art approach by 4. 5 percentage points on HearthStone, and achieved the best accuracy among neural network-based approaches on ATIS (89. 1%) and GEO (89. 6%).

Code Generation Semantic Parsing

Quality Assessment of DIBR-synthesized views: An Overview

no code implementations16 Nov 2019 Shishun Tian, Lu Zhang, Wenbin Zou, Xia Li, Ting Su, Luce Morin, Olivier Deforges

In this paper, we provide a comprehensive survey on various current approaches for DIBR-synthesized views.

Fairness through Equality of Effort

no code implementations11 Nov 2019 Wen Huang, Yongkai Wu, Lu Zhang, Xintao Wu

We develop algorithms for determining whether an individual or a group of individuals is discriminated in terms of equality of effort.

BIG-bench Machine Learning counterfactual +1

PC-Fairness: A Unified Framework for Measuring Causality-based Fairness

no code implementations NeurIPS 2019 Yongkai Wu, Lu Zhang, Xintao Wu, Hanghang Tong

A recent trend of fair machine learning is to define fairness as causality-based notions which concern the causal connection between protected attributes and decisions.

counterfactual Fairness

On identifiability and consistency of the nugget in Gaussian spatial process models

1 code implementation15 Aug 2019 Wenpin Tang, Lu Zhang, Sudipto Banerjee

We formally establish results on the identifiability and consistency of the nugget in spatial models based upon the Gaussian process within the framework of in-fill asymptotics, i. e. the sample size increases within a sampling domain that is bounded.

Spatial Interpolation Statistics Theory Statistics Theory

Safe Trajectory Generation for Complex Urban Environments Using Spatio-temporal Semantic Corridor

2 code implementations24 Jun 2019 Wenchao Ding, Lu Zhang, Jing Chen, Shaojie Shen

Planning safe trajectories for autonomous vehicles in complex urban environments is challenging since there are numerous semantic elements (such as dynamic agents, traffic lights and speed limits) to consider.

Autonomous Vehicles Benchmarking

Weakly Aligned Cross-Modal Learning for Multispectral Pedestrian Detection

no code implementations ICCV 2019 Lu Zhang, Xiangyu Zhu, Xiangyu Chen, Xu Yang, Zhen Lei, Zhi-Yong Liu

In this paper, we propose a novel Aligned Region CNN (AR-CNN) to handle the weakly aligned multispectral data in an end-to-end way.

Position

A Grammar-Based Structural CNN Decoder for Code Generation

1 code implementation14 Nov 2018 Zeyu Sun, Qihao Zhu, Lili Mou, Yingfei Xiong, Ge Li, Lu Zhang

In this paper, we propose a grammar-based structural convolutional neural network (CNN) for code generation.

Code Generation Decoder +2

Fairness-aware Classification: Criterion, Convexity, and Bounds

no code implementations13 Sep 2018 Yongkai Wu, Lu Zhang, Xintao Wu

In this paper, we propose a general framework for learning fair classifiers which addresses previous limitations.

Classification Computational Efficiency +2

FairGAN: Fairness-aware Generative Adversarial Networks

no code implementations28 May 2018 Depeng Xu, Shuhan Yuan, Lu Zhang, Xintao Wu

In this paper, we focus on fair data generation that ensures the generated data is discrimination free.

Fairness General Classification

On Discrimination Discovery and Removal in Ranked Data using Causal Graph

no code implementations5 Mar 2018 Yongkai Wu, Lu Zhang, Xintao Wu

Existing methods in fairness-aware ranking are mainly based on statistical parity that cannot measure the true discriminatory effect since discrimination is causal.

Fairness

Crowd counting via scale-adaptive convolutional neural network

1 code implementation13 Nov 2017 Lu Zhang, Miaojing Shi, Qiaobo Chen

The task of crowd counting is to automatically estimate the pedestrian number in crowd images.

Crowd Counting

Contrast and visual saliency similarity-induced index for assessing image quality

no code implementations22 Aug 2017 Huizhen Jia, Lu Zhang, Tonghan Wang

Contrast is an inherent visual attribute that indicates image quality, and visual saliency (VS) is a quality that attracts the attention of human beings.

Attribute Image Quality Assessment

Achieving non-discrimination in prediction

no code implementations28 Feb 2017 Lu Zhang, Yongkai Wu, Xintao Wu

Based on the results, we develop a two-phase framework for constructing a discrimination-free classifier with a theoretical guarantee.

A causal framework for discovering and removing direct and indirect discrimination

no code implementations22 Nov 2016 Lu Zhang, Yongkai Wu, Xintao Wu

In this paper, we investigate the problem of discovering both direct and indirect discrimination from the historical data, and removing the discriminatory effects before the data is used for predictive analysis (e. g., building classifiers).

Decision Making

Achieving non-discrimination in data release

no code implementations22 Nov 2016 Lu Zhang, Yongkai Wu, Xintao Wu

Discrimination discovery and prevention/removal are increasingly important tasks in data mining.

Attribute

Beyond F-Formations: Determining Social Involvement in Free Standing Conversing Groups From Static Images

no code implementations CVPR 2016 Lu Zhang, Hayley Hung

In this paper, we present the first attempt to analyse differing levels of social involvement in free standing conversing groups (or the so-called F-formations) from static images.

How Transferable are Neural Networks in NLP Applications?

no code implementations EMNLP 2016 Lili Mou, Zhao Meng, Rui Yan, Ge Li, Yan Xu, Lu Zhang, Zhi Jin

Transfer learning is aimed to make use of valuable knowledge in a source domain to help model performance in a target domain.

Transfer Learning

Backward and Forward Language Modeling for Constrained Sentence Generation

no code implementations21 Dec 2015 Lili Mou, Rui Yan, Ge Li, Lu Zhang, Zhi Jin

Provided a specific word, we use RNNs to generate previous words and future words, either simultaneously or asynchronously, resulting in two model variants.

Language Modelling Machine Translation +4

On End-to-End Program Generation from User Intention by Deep Neural Networks

no code implementations25 Oct 2015 Lili Mou, Rui Men, Ge Li, Lu Zhang, Zhi Jin

This paper envisions an end-to-end program generation scenario using recurrent neural networks (RNNs): Users can express their intention in natural language; an RNN then automatically generates corresponding code in a characterby-by-character fashion.

Distilling Word Embeddings: An Encoding Approach

no code implementations15 Jun 2015 Lili Mou, Ran Jia, Yan Xu, Ge Li, Lu Zhang, Zhi Jin

Distilling knowledge from a well-trained cumbersome network to a small one has recently become a new research topic, as lightweight neural networks with high performance are particularly in need in various resource-restricted systems.

Word Embeddings

Convolutional Neural Networks over Tree Structures for Programming Language Processing

8 code implementations18 Sep 2014 Lili Mou, Ge Li, Lu Zhang, Tao Wang, Zhi Jin

Programming language processing (similar to natural language processing) is a hot research topic in the field of software engineering; it has also aroused growing interest in the artificial intelligence community.

Sentence

Building Program Vector Representations for Deep Learning

1 code implementation11 Sep 2014 Lili Mou, Ge Li, Yuxuan Liu, Hao Peng, Zhi Jin, Yan Xu, Lu Zhang

In this pioneering paper, we propose the "coding criterion" to build program vector representations, which are the premise of deep learning for program analysis.

Representation Learning

Speeding Up Tracking by Ignoring Features

no code implementations CVPR 2014 Lu Zhang, Hamdi Dibeklioglu, Laurens van der Maaten

Most modern object trackers combine a motion prior with sliding-window detection, using binary classifiers that predict the presence of the target object based on histogram features.

Object

Structure Preserving Object Tracking

no code implementations CVPR 2013 Lu Zhang, Laurens van der Maaten

We also show that SPOT can improve the performance of single-object trackers by simultaneously tracking different parts of the object.

Multi-Object Tracking Object

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