Search Results for author: Lin Zhang

Found 104 papers, 41 papers with code

AgentGroupChat: An Interactive Group Chat Simulacra For Better Eliciting Emergent Behavior

1 code implementation20 Mar 2024 Zhouhong Gu, Xiaoxuan Zhu, Haoran Guo, Lin Zhang, Yin Cai, Hao Shen, Jiangjie Chen, Zheyu Ye, Yifei Dai, Yan Gao, Yao Hu, Hongwei Feng, Yanghua Xiao

Language significantly influences the formation and evolution of Human emergent behavior, which is crucial in understanding collective intelligence within human societies.

Audio-Synchronized Visual Animation

no code implementations8 Mar 2024 Lin Zhang, Shentong Mo, Yijing Zhang, Pedro Morgado

We hope our established benchmark can open new avenues for controllable visual generation.

Decentralised, Collaborative, and Privacy-preserving Machine Learning for Multi-Hospital Data

1 code implementation31 Jan 2024 Congyu Fang, Adam Dziedzic, Lin Zhang, Laura Oliva, Amol Verma, Fahad Razak, Nicolas Papernot, Bo wang

In addition, the ML models trained with DeCaPH framework in general outperform those trained solely with the private datasets from individual parties, showing that DeCaPH enhances the model generalizability.

Mortality Prediction Privacy Preserving

D3GU: Multi-Target Active Domain Adaptation via Enhancing Domain Alignment

1 code implementation10 Jan 2024 Lin Zhang, Linghan Xu, Saman Motamed, Shayok Chakraborty, Fernando de la Torre

Unsupervised domain adaptation (UDA) for image classification has made remarkable progress in transferring classification knowledge from a labeled source domain to an unlabeled target domain, thanks to effective domain alignment techniques.

Classification Image Classification +1

Dig-CSI: A Distributed and Generative Model Assisted CSI Feedback Training Framework

no code implementations10 Dec 2023 Zhilin Du, Haozhen Li, Zhenyu Liu, Shilong Fan, Xinyu Gu, Lin Zhang

The advent of deep learning (DL)-based models has significantly advanced Channel State Information (CSI) feedback mechanisms in wireless communication systems.


Concept-free Causal Disentanglement with Variational Graph Auto-Encoder

no code implementations17 Nov 2023 Jingyun Feng, Lin Zhang, Lili Yang

Existing approaches often rely on Variational Auto-Encoder (VAE) or its causal structure learning-based refinement, which suffer from sub-optimality in VAEs due to the independence factor assumption and unavailability of concept labels, respectively.

Disentanglement Meta-Learning

EALM: Introducing Multidimensional Ethical Alignment in Conversational Information Retrieval

1 code implementation2 Oct 2023 Yiyao Yu, Junjie Wang, Yuxiang Zhang, Lin Zhang, Yujiu Yang, Tetsuya Sakai

Artificial intelligence (AI) technologies should adhere to human norms to better serve our society and avoid disseminating harmful or misleading information, particularly in Conversational Information Retrieval (CIR).

Ethics Information Retrieval +1

Specializing Small Language Models towards Complex Style Transfer via Latent Attribute Pre-Training

1 code implementation19 Sep 2023 Ruiqi Xu, Yongfeng Huang, Xin Chen, Lin Zhang

In this work, we introduce the concept of complex text style transfer tasks, and constructed complex text datasets based on two widely applicable scenarios.

Attribute Contrastive Learning +2

LoRA-FA: Memory-efficient Low-rank Adaptation for Large Language Models Fine-tuning

no code implementations7 Aug 2023 Longteng Zhang, Lin Zhang, Shaohuai Shi, Xiaowen Chu, Bo Li

The low-rank adaptation (LoRA) method can largely reduce the amount of trainable parameters for fine-tuning large language models (LLMs), however, it still requires expensive activation memory to update low-rank weights.

Eva: A General Vectorized Approximation Framework for Second-order Optimization

no code implementations4 Aug 2023 Lin Zhang, Shaohuai Shi, Bo Li

Second-order optimization algorithms exhibit excellent convergence properties for training deep learning models, but often incur significant computation and memory overheads.

Piecing Together Clues: A Benchmark for Evaluating the Detective Skills of Large Language Models

no code implementations11 Jul 2023 Zhouhong Gu, Lin Zhang, Jiangjie Chen, Haoning Ye, Xiaoxuan Zhu, Zihan Li, Zheyu Ye, Yan Gao, Yao Hu, Yanghua Xiao, Hongwei Feng

We introduces the DetectBench, a reading comprehension dataset designed to assess a model's ability to jointly ability in key information detection and multi-hop reasoning when facing complex and implicit information.

Common Sense Reasoning Decision Making +2

Evaluation and Optimization of Gradient Compression for Distributed Deep Learning

1 code implementation15 Jun 2023 Lin Zhang, Longteng Zhang, Shaohuai Shi, Xiaowen Chu, Bo Li

To accelerate distributed training, many gradient compression methods have been proposed to alleviate the communication bottleneck in synchronous stochastic gradient descent (S-SGD), but their efficacy in real-world applications still remains unclear.


D2Match: Leveraging Deep Learning and Degeneracy for Subgraph Matching

1 code implementation10 Jun 2023 Xuanzhou Liu, Lin Zhang, Jiaqi Sun, Yujiu Yang, Haiqin Yang

Subgraph matching is a fundamental building block for graph-based applications and is challenging due to its high-order combinatorial nature.

Combinatorial Optimization

Progression Cognition Reinforcement Learning with Prioritized Experience for Multi-Vehicle Pursuit

1 code implementation8 Jun 2023 Xinhang Li, Yiying Yang, Zheng Yuan, Zhe Wang, Qinwen Wang, Chen Xu, Lei LI, Jianhua He, Lin Zhang

For the more challenging problem of pursuing multiple evading vehicles, these algorithms typically select a fixed target evading vehicle for pursuing vehicles without considering dynamic traffic situation, which significantly reduces pursuing success rate.

Multi-agent Reinforcement Learning reinforcement-learning

Range-Based Equal Error Rate for Spoof Localization

1 code implementation28 May 2023 Lin Zhang, Xin Wang, Erica Cooper, Nicholas Evans, Junichi Yamagishi

To properly measure misclassified ranges and better evaluate spoof localization performance, we upgrade point-based EER to range-based EER.

A Diffusion Model for Event Skeleton Generation

1 code implementation27 May 2023 Fangqi Zhu, Lin Zhang, Jun Gao, Bing Qin, Ruifeng Xu, Haiqin Yang

Event skeleton generation, aiming to induce an event schema skeleton graph with abstracted event nodes and their temporal relations from a set of event instance graphs, is a critical step in the temporal complex event schema induction task.

Denoising Graph Generation

Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks

1 code implementation23 May 2023 Peng Xu, Lin Zhang, Xuanzhou Liu, Jiaqi Sun, Yue Zhao, Haiqin Yang, Bei Yu

Neural architecture search (NAS) for Graph neural networks (GNNs), called NAS-GNNs, has achieved significant performance over manually designed GNN architectures.

Neural Architecture Search

Feature Expansion for Graph Neural Networks

1 code implementation10 May 2023 Jiaqi Sun, Lin Zhang, Guangyi Chen, Kun Zhang, Peng Xu, Yujiu Yang

Graph neural networks aim to learn representations for graph-structured data and show impressive performance, particularly in node classification.

Node Classification Representation Learning

Detection of Pavement Cracks by Deep Learning Models of Transformer and UNet

no code implementations25 Apr 2023 Yu Zhang, Lin Zhang

In this study, we investigated nine promising models to evaluate their performance in pavement surface crack detection by model accuracy, computational complexity, and model stability.

H2TNE: Temporal Heterogeneous Information Network Embedding in Hyperbolic Spaces

1 code implementation14 Apr 2023 Qijie Bai, JiaWen Guo, Haiwei Zhang, Changli Nie, Lin Zhang, Xiaojie Yuan

Temporal heterogeneous information network (temporal HIN) embedding, aiming to represent various types of nodes of different timestamps into low dimensional spaces while preserving structural and semantic information, is of vital importance in diverse real-life tasks.

Link Prediction Network Embedding +2

HybridCVLNet: A Hybrid CSI Feedback System and its Domain Adaptation

no code implementations30 Mar 2023 Haozhen Li, Xinyu Gu, Boyuan Zhang, Dongliang Li, Zhenyu Liu, Lin Zhang

Deep Learning (DL)-based channel state information (CSI) feedback is a promising technique for the transmitter to accurately acquire the CSI of massive multiple-input multiple-output (MIMO) systems.

Domain Adaptation Transfer Learning

Artificial Intelligence: 70 Years Down the Road

no code implementations6 Mar 2023 Lin Zhang

Artificial intelligence (AI) has a history of nearly a century from its inception to the present day.


DeAR: Accelerating Distributed Deep Learning with Fine-Grained All-Reduce Pipelining

1 code implementation24 Feb 2023 Lin Zhang, Shaohuai Shi, Xiaowen Chu, Wei Wang, Bo Li, Chengjian Liu

Communication scheduling has been shown to be effective in accelerating distributed training, which enables all-reduce communications to be overlapped with backpropagation computations.


Unpaired Translation from Semantic Label Maps to Images by Leveraging Domain-Specific Simulations

no code implementations21 Feb 2023 Lin Zhang, Tiziano Portenier, Orcun Goksel

We introduce a contrastive learning framework for generating photorealistic images from simulated label maps, by learning from unpaired sets of both.

Contrastive Learning Image Generation +1

A Large-scale Friend Suggestion Architecture

no code implementations24 Dec 2022 Lin Zhang, Rui Li

There has been little work on designing friend suggestion when facing these difficulties, and for the first time we aim to tackle this in large scale online games.

Unsupervised Instance and Subnetwork Selection for Network Data

no code implementations24 Dec 2022 Lin Zhang, Nicholas Moskwa, Melinda Larsen, Petko Bogdanov

We address these challenges within an unsupervised framework for joint subnetwork and instance selection in network data, called UISS, via a convex self-representation objective.

An Information-Theoretic Approach to Transferability in Task Transfer Learning

no code implementations20 Dec 2022 Yajie Bao, Yang Li, Shao-Lun Huang, Lin Zhang, Lizhong Zheng, Amir Zamir, Leonidas Guibas

Task transfer learning is a popular technique in image processing applications that uses pre-trained models to reduce the supervision cost of related tasks.

Model Selection Transfer Learning

RRSR:Reciprocal Reference-based Image Super-Resolution with Progressive Feature Alignment and Selection

no code implementations8 Nov 2022 Lin Zhang, Xin Li, Dongliang He, Fu Li, Yili Wang, Zhaoxiang Zhang

While previous state-of-the-art RefSR methods mainly focus on improving the efficacy and robustness of reference feature transfer, it is generally overlooked that a well reconstructed SR image should enable better SR reconstruction for its similar LR images when it is referred to as.

feature selection Image Super-Resolution

Solving Math Word Problems via Cooperative Reasoning induced Language Models

1 code implementation28 Oct 2022 Xinyu Zhu, Junjie Wang, Lin Zhang, Yuxiang Zhang, Ruyi Gan, Jiaxing Zhang, Yujiu Yang

This inspires us to develop a cooperative reasoning-induced PLM for solving MWPs, called Cooperative Reasoning (CoRe), resulting in a human-like reasoning architecture with system 1 as the generator and system 2 as the verifier.

Arithmetic Reasoning Math

Graded-Q Reinforcement Learning with Information-Enhanced State Encoder for Hierarchical Collaborative Multi-Vehicle Pursuit

1 code implementation24 Oct 2022 Yiying Yang, Xinhang Li, Zheng Yuan, Qinwen Wang, Chen Xu, Lin Zhang

However, existing works on MVP pay little attention to the importance of information exchange and cooperation among pursuing vehicles under the complex urban traffic environment.

Decision Making

Zero-Shot Learners for Natural Language Understanding via a Unified Multiple Choice Perspective

1 code implementation16 Oct 2022 Ping Yang, Junjie Wang, Ruyi Gan, Xinyu Zhu, Lin Zhang, Ziwei Wu, Xinyu Gao, Jiaxing Zhang, Tetsuya Sakai

We propose a new paradigm for zero-shot learners that is format agnostic, i. e., it is compatible with any format and applicable to a list of language tasks, such as text classification, commonsense reasoning, coreference resolution, and sentiment analysis.

Multiple-choice Natural Language Inference +4

Improving Your Graph Neural Networks: A High-Frequency Booster

1 code implementation15 Oct 2022 Jiaqi Sun, Lin Zhang, Shenglin Zhao, Yujiu Yang

Graph neural networks (GNNs) hold the promise of learning efficient representations of graph-structured data, and one of its most important applications is semi-supervised node classification.

Node Classification Vocal Bursts Intensity Prediction

Learning "O" Helps for Learning More: Handling the Concealed Entity Problem for Class-incremental NER

no code implementations10 Oct 2022 Ruotian Ma, Xuanting Chen, Lin Zhang, Xin Zhou, Junzhe Wang, Tao Gui, Qi Zhang, Xiang Gao, Yunwen Chen

In this work, we conduct an empirical study on the "Unlabeled Entity Problem" and find that it leads to severe confusion between "O" and entities, decreasing class discrimination of old classes and declining the model's ability to learn new classes.

Class Incremental Learning Contrastive Learning +3

Provably Uncertainty-Guided Universal Domain Adaptation

no code implementations19 Sep 2022 Yifan Wang, Lin Zhang, Ran Song, Paul L. Rosin, Yibin Li, Wei zhang

It fully utilizes the relationship between a target sample and its neighbors in the source domain to avoid the influence of domain misalignment.

Universal Domain Adaptation Unsupervised Domain Adaptation

Spoofing-Aware Attention based ASV Back-end with Multiple Enrollment Utterances and a Sampling Strategy for the SASV Challenge 2022

no code implementations1 Sep 2022 Chang Zeng, Lin Zhang, Meng Liu, Junichi Yamagishi

Current state-of-the-art automatic speaker verification (ASV) systems are vulnerable to presentation attacks, and several countermeasures (CMs), which distinguish bona fide trials from spoofing ones, have been explored to protect ASV.

Speaker Verification

Exploiting Inter-Sample Affinity for Knowability-Aware Universal Domain Adaptation

no code implementations19 Jul 2022 Yifan Wang, Lin Zhang, Ran Song, Hongliang Li, Paul L. Rosin, Wei zhang

Specifically, we introduce a knowability-based labeling scheme which can be divided into two steps: 1) Knowability-guided detection of known and unknown samples based on the intrinsic structure of the neighborhoods of samples, where we leverage the first singular vectors of the affinity matrices to obtain the knowability of every target sample.

Universal Domain Adaptation

Safe Reinforcement Learning for a Robot Being Pursued but with Objectives Covering More Than Capture-avoidance

no code implementations2 Jul 2022 Huanhui Cao, Zhiyuan Cai, Hairuo Wei, Wenjie Lu, Lin Zhang, Hao Xiong

Reinforcement Learning (RL) algorithms show amazing performance in recent years, but placing RL in real-world applications such as self-driven vehicles may suffer safety problems.

Position Reinforcement Learning (RL) +1

Scalable K-FAC Training for Deep Neural Networks with Distributed Preconditioning

1 code implementation30 Jun 2022 Lin Zhang, Shaohuai Shi, Wei Wang, Bo Li

The second-order optimization methods, notably the D-KFAC (Distributed Kronecker Factored Approximate Curvature) algorithms, have gained traction on accelerating deep neural network (DNN) training on GPU clusters.

WHU-Stereo: A Challenging Benchmark for Stereo Matching of High-Resolution Satellite Images

1 code implementation6 Jun 2022 Shenhong Li, Sheng He, San Jiang, Wanshou Jiang, Lin Zhang

The WHU-Stereo dataset can serve as a challenging benchmark for stereo matching of high-resolution satellite images, and performance evaluation of deep learning models.

Stereo Matching

Multi-task Deep Neural Networks for Massive MIMO CSI Feedback

no code implementations18 Apr 2022 Boyuan Zhang, Haozhen Li, Xin Liang, Xinyu Gu, Lin Zhang

Deep learning has been widely applied for the channel state information (CSI) feedback in frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) system.

Multi-Task Learning

The PartialSpoof Database and Countermeasures for the Detection of Short Fake Speech Segments Embedded in an Utterance

no code implementations11 Apr 2022 Lin Zhang, Xin Wang, Erica Cooper, Nicholas Evans, Junichi Yamagishi

Since the short spoofed speech segments to be embedded by attackers are of variable length, six different temporal resolutions are considered, ranging from as short as 20 ms to as large as 640 ms. Third, we propose a new CM that enables the simultaneous use of the segment-level labels at different temporal resolutions as well as utterance-level labels to execute utterance- and segment-level detection at the same time.

Speaker Verification Speech Synthesis +2

TMS: A Temporal Multi-scale Backbone Design for Speaker Embedding

no code implementations17 Mar 2022 Ruiteng Zhang, Jianguo Wei, Xugang Lu, Wenhuan Lu, Di Jin, Junhai Xu, Lin Zhang, Yantao Ji, Jianwu Dang

Therefore, in the most current state-of-the-art network architectures, only a few branches corresponding to a limited number of temporal scales could be designed for speaker embeddings.

Speaker Verification

Fine-tuning Global Model via Data-Free Knowledge Distillation for Non-IID Federated Learning

1 code implementation CVPR 2022 Lin Zhang, Li Shen, Liang Ding, DaCheng Tao, Ling-Yu Duan

Instead, we propose a data-free knowledge distillation method to fine-tune the global model in the server (FedFTG), which relieves the issue of direct model aggregation.

Data-free Knowledge Distillation Federated Learning

$ \text{T}^3 $OMVP: A Transformer-based Time and Team Reinforcement Learning Scheme for Observation-constrained Multi-Vehicle Pursuit in Urban Area

1 code implementation1 Mar 2022 Zheng Yuan, Tianhao Wu, Qinwen Wang, Yiying Yang, Lei LI, Lin Zhang

Although there are some achievements in the field of MVP in the open space environment, the urban area brings complicated road structures and restricted moving spaces as challenges to the resolution of MVP games.

Decision Making

Self-Augmented Unpaired Image Dehazing via Density and Depth Decomposition

1 code implementation CVPR 2022 Yang Yang, Chaoyue Wang, Risheng Liu, Lin Zhang, Xiaojie Guo, DaCheng Tao

With estimated scene depth, our method is capable of re-rendering hazy images with different thicknesses which further benefits the training of the dehazing network.

Image Dehazing

Learning from Temporal Gradient for Semi-supervised Action Recognition

1 code implementation CVPR 2022 Junfei Xiao, Longlong Jing, Lin Zhang, Ju He, Qi She, Zongwei Zhou, Alan Yuille, Yingwei Li

Our method achieves the state-of-the-art performance on three video action recognition benchmarks (i. e., Kinetics-400, UCF-101, and HMDB-51) under several typical semi-supervised settings (i. e., different ratios of labeled data).

Action Recognition Temporal Action Localization

CdtGRN: Construction of qualitative time-delayed gene regulatory networks with a deep learning method

no code implementations30 Oct 2021 Ruijie Xu, Lin Zhang, Yu Chen

Therefore, it is of great significance to elucidate the regulation mechanism over time points.

CS-Rep: Making Speaker Verification Networks Embracing Re-parameterization

1 code implementation26 Oct 2021 Ruiteng Zhang, Jianguo Wei, Wenhuan Lu, Lin Zhang, Yantao Ji, Junhai Xu, Xugang Lu

Automatic speaker verification (ASV) systems, which determine whether two speeches are from the same speaker, mainly focus on verification accuracy while ignoring inference speed.

Speaker Verification

FLBoost: On-the-Fly Fine-tuning Boosts Federated Learning via Data-free Distillation

no code implementations29 Sep 2021 Lin Zhang, Li Shen, Liang Ding, DaCheng Tao, Lingyu Duan

On the contrary, we propose a new solution: on-the-fly fine-tuning the global model in server via data-free distillation to boost its performance, dubbed FLBoost to relieve the issue of direct model aggregation.

Federated Learning

Estimating Mean Speed-of-Sound from Sequence-Dependent Geometric Disparities

no code implementations24 Sep 2021 Xenia Augustin, Lin Zhang, Orcun Goksel

We demonstrate the effectiveness of our proposed method for tomographic SoS reconstruction.

Maximum Likelihood Estimation for Multimodal Learning with Missing Modality

no code implementations24 Aug 2021 Fei Ma, Xiangxiang Xu, Shao-Lun Huang, Lin Zhang

Moreover, we develop a generalized form of the softmax function to effectively implement maximum likelihood estimation in an end-to-end manner.

MT-ORL: Multi-Task Occlusion Relationship Learning

1 code implementation ICCV 2021 Panhe Feng, Qi She, Lei Zhu, Jiaxin Li, Lin Zhang, Zijian Feng, Changhu Wang, Chunpeng Li, Xuejing Kang, Anlong Ming

Retrieving occlusion relation among objects in a single image is challenging due to sparsity of boundaries in image.


A Credibility-aware Swarm-Federated Deep Learning Framework in Internet of Vehicles

1 code implementation9 Aug 2021 Zhe Wang, Xinhang Li, Tianhao Wu, Chen Xu, Lin Zhang

This paper proposes a Swarm-Federated Deep Learning framework in the IoV system (IoV-SFDL) that integrates SL into the FDL framework.

BIG-bench Machine Learning Edge-computing

Edge of chaos as a guiding principle for modern neural network training

no code implementations20 Jul 2021 Lin Zhang, Ling Feng, Kan Chen, Choy Heng Lai

Motivated by the edge of chaos principle behind the optimal performance of neural networks, we study the role of various hyperparameters in modern neural network training algorithms in terms of the order-chaos phase diagram.

Accelerating Distributed K-FAC with Smart Parallelism of Computing and Communication Tasks

no code implementations14 Jul 2021 Shaohuai Shi, Lin Zhang, Bo Li

Specifically, 1) we first characterize the performance bottlenecks of D-KFAC, 2) we design and implement a pipelining mechanism for Kronecker factors computation and communication with dynamic tensor fusion, and 3) we develop a load balancing placement for inverting multiple matrices on GPU clusters.

Temporal Graph Signal Decomposition

no code implementations25 Jun 2021 Maxwell McNeil, Lin Zhang, Petko Bogdanov

We propose a general, dictionary-based framework for temporal graph signal decomposition (TGSD).

Imputation Period Estimation +1

A One-Shot Texture-Perceiving Generative Adversarial Network for Unsupervised Surface Inspection

no code implementations12 Jun 2021 Lingyun Gu, Lin Zhang, Zhaokui Wang

Visual surface inspection is a challenging task owing to the highly diverse appearance of target surfaces and defective regions.

Generative Adversarial Network

Causal Discovery of Flight Service Process Based on Event Sequence

no code implementations28 Apr 2021 Zhiwei Xing, Lin Zhang, Huan Xia, Qian Luo, Zhao-xin Chen

In the existing ground support research, there has not yet been a process model that directly obtains support from the ground support log to study the causal relationship between service nodes and flight delays.

Causal Discovery

An Initial Investigation for Detecting Partially Spoofed Audio

no code implementations6 Apr 2021 Lin Zhang, Xin Wang, Erica Cooper, Junichi Yamagishi, Jose Patino, Nicholas Evans

By definition, partially-spoofed utterances contain a mix of both spoofed and bona fide segments, which will likely degrade the performance of countermeasures trained with entirely spoofed utterances.

Voice Anti-spoofing

A Dynamics Perspective of Pursuit-Evasion Games of Intelligent Agents with the Ability to Learn

no code implementations3 Apr 2021 Hao Xiong, Huanhui Cao, Lin Zhang, Wenjie Lu

It is shown that, in a pursuit-evasion game with a dynamics formulation, an evader is not able to escape from a slightly faster pursuer with an effective learned pursuit strategy, based on agile maneuvers and an effective learned evasion strategy.

reinforcement-learning Reinforcement Learning (RL)

Learning Ultrasound Rendering from Cross-Sectional Model Slices for Simulated Training

no code implementations20 Jan 2021 Lin Zhang, Tiziano Portenier, Orcun Goksel

Given the high level of expertise required for navigation and interpretation of ultrasound images, computational simulations can facilitate the training of such skills in virtual reality.


A Multi-intersection Vehicular Cooperative Control based on End-Edge-Cloud Computing

no code implementations1 Dec 2020 Mingzhi Jiang, Tianhao Wu, Zhe Wang, Yi Gong, Lin Zhang, Ren Ping Liu

In particular, we propose a Multi-intersection Vehicular Cooperative Control (MiVeCC) to enable cooperation among vehicles in a large area with multiple unsignalized intersections.

Cloud Computing Management

Penalized model-based clustering of fMRI data

no code implementations13 Oct 2020 Andrew DiLernia, Karina Quevedo, Jazmin Camchong, Kelvin Lim, Wei Pan, Lin Zhang

To this end, we propose a random covariance clustering model (RCCM) to concurrently cluster subjects based on their FC networks, estimate the unique FC networks of each subject, and to infer shared network features.


ConvGRU in Fine-grained Pitching Action Recognition for Action Outcome Prediction

no code implementations18 Aug 2020 Tianqi Ma, Lin Zhang, Xiumin Diao, Ou Ma

Considering that the different outcomes are closely connected to the subtle differences in actions, fine-grained action recognition is a practical method for action outcome prediction.

Fine-grained Action Recognition Management +1

Mask Detection and Breath Monitoring from Speech: on Data Augmentation, Feature Representation and Modeling

no code implementations12 Aug 2020 Haiwei Wu, Lin Zhang, Lin Yang, Xuyang Wang, Jun-Jie Wang, Dong Zhang, Ming Li

This paper introduces our approaches for the Mask and Breathing Sub-Challenge in the Interspeech COMPARE Challenge 2020.

Data Augmentation

Multi-resolution Super Learner for Voxel-wise Classification of Prostate Cancer Using Multi-parametric MRI

1 code implementation2 Jul 2020 Jin Jin, Lin Zhang, Ethan Leng, Gregory J. Metzger, Joseph S. Koopmeiners

While current research has shown the importance of Multi-parametric MRI (mpMRI) in diagnosing prostate cancer (PCa), further investigation is needed for how to incorporate the specific structures of the mpMRI data, such as the regional heterogeneity and between-voxel correlation within a subject.

BIG-bench Machine Learning

Deep Image Translation for Enhancing Simulated Ultrasound Images

no code implementations18 Jun 2020 Lin Zhang, Tiziano Portenier, Christoph Paulus, Orcun Goksel

To incorporate anatomical information potentially lost in low quality images, we additionally provide segmentation maps to image translation.

Image-to-Image Translation Translation

One-Shot Object Detection without Fine-Tuning

1 code implementation8 May 2020 Xiang Li, Lin Zhang, Yau Pun Chen, Yu-Wing Tai, Chi-Keung Tang

Deep learning has revolutionized object detection thanks to large-scale datasets, but their object categories are still arguably very limited.

Metric Learning Object +3

Towards Palmprint Verification On Smartphones

no code implementations30 Mar 2020 Yingyi Zhang, Lin Zhang, Ruixin Zhang, Shaoxin Li, Jilin Li, Feiyue Huang

First, to facilitate the study of palmprint verification on smartphones, we established an annotated palmprint dataset named MPD, which was collected by multi-brand smartphones in two separate sessions with various backgrounds and illumination conditions.

Learning Global and Local Consistent Representations for Unsupervised Image Retrieval via Deep Graph Diffusion Networks

no code implementations5 Jan 2020 Zhiyong Dou, Haotian Cui, Lin Zhang, Bo wang

Diffusion has shown great success in improving accuracy of unsupervised image retrieval systems by utilizing high-order structures of image manifold.

Image Retrieval Retrieval

Phase Contrast Microscopy Cell PopulationSegmentation: A Survey

no code implementations25 Nov 2019 Lin Zhang

Phase contrast microscopy (PCM) has been widely used in biomedicine research, which allows users to observe objectives without staining or killing them.

Cell Tracking

Optimal Machine Intelligence at the Edge of Chaos

no code implementations11 Sep 2019 Ling Feng, Lin Zhang, Choy Heng Lai

It has long been suggested that the biological brain operates at some critical point between two different phases, possibly order and chaos.

An Information-Theoretic Metric of Transferability for Task Transfer Learning

1 code implementation ICLR 2019 Yajie Bao, Yang Li, Shao-Lun Huang, Lin Zhang, Amir R. Zamir, Leonidas J. Guibas

An important question in task transfer learning is to determine task transferability, i. e. given a common input domain, estimating to what extent representations learned from a source task can help in learning a target task.

General Classification Scene Understanding +1

An Efficient Approach for Cell Segmentation in Phase Contrast Microscopy Images

no code implementations31 Mar 2019 Lin Zhang

In this paper, we propose a new model to segment cells in phase contrast microscopy images.

Cell Segmentation

DSL: Discriminative Subgraph Learning via Sparse Self-Representation

no code implementations24 Mar 2019 Lin Zhang, Petko Bogdanov

In this work we propose an optimization framework for discriminative subgraph learning (DSL) which simultaneously enforces (i) sparsity, (ii) connectivity and (iii) high discriminative power of the resulting subgraphs of features.

feature selection

Implicit Modeling with Uncertainty Estimation for Intravoxel Incoherent Motion Imaging

no code implementations22 Oct 2018 Lin Zhang, Valery Vishnevskiy, Andras Jakab, Orcun Goksel

Intravoxel incoherent motion (IVIM) imaging allows contrast-agent free in vivo perfusion quantification with magnetic resonance imaging (MRI).

An empirical learning-based validation procedure for simulation workflow

no code implementations11 Sep 2018 Zhuqing Liu, Liyuanjun Lai, Lin Zhang

Simulation workflow is a top-level model for the design and control of simulation process.

Deep Smoke Segmentation

no code implementations4 Sep 2018 Feiniu Yuan, Lin Zhang, Xue Xia, Boyang Wan, Qinghua Huang, Xuelong. Li

According to results of our deep segmentation method, we can easily and accurately perform smoke detection from videos.

Decoder Segmentation +1

Temporal Interpolation via Motion Field Prediction

1 code implementation12 Apr 2018 Lin Zhang, Neerav Karani, Christine Tanner, Ender Konukoglu

Temporal interpolation of navigator slices an be used to reduce the number of navigator acquisitions without degrading specificity in stacking.

4D reconstruction Specificity

Self-Supervised Siamese Learning on Stereo Image Pairs for Depth Estimation in Robotic Surgery

no code implementations17 May 2017 Menglong Ye, Edward Johns, Ankur Handa, Lin Zhang, Philip Pratt, Guang-Zhong Yang

Robotic surgery has become a powerful tool for performing minimally invasive procedures, providing advantages in dexterity, precision, and 3D vision, over traditional surgery.

Depth Estimation Depth Prediction

Real-time 3D Tracking of Articulated Tools for Robotic Surgery

no code implementations11 May 2016 Menglong Ye, Lin Zhang, Stamatia Giannarou, Guang-Zhong Yang

The proposed method is based on the CAD model of the tools as well as robot kinematics to generate online part-based templates for efficient 2D matching and 3D pose estimation.

3D Pose Estimation Skills Assessment

Simulation of X-ray diffraction profiles for bent anisotropic crystals

1 code implementation5 Feb 2015 Manuel Sanchez del Rio, Nicolas Perez-Bocanegra, Xianbo Shi, Veijo Honkimaki, Lin Zhang

The equations for calculating diffraction profiles for bent crystals are revisited for both meridional and sagittal bending.

Materials Science Optics

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