Search Results for author: Lin Yang

Found 118 papers, 19 papers with code

Achieving Near-Optimal Regret for Bandit Algorithms with Uniform Last-Iterate Guarantee

no code implementations20 Feb 2024 Junyan Liu, Yunfan Li, Lin Yang

This paper introduces a stronger performance measure, the uniform last-iterate (ULI) guarantee, capturing both cumulative and instantaneous performance of bandit algorithms.

PathMMU: A Massive Multimodal Expert-Level Benchmark for Understanding and Reasoning in Pathology

no code implementations29 Jan 2024 Yuxuan Sun, Hao Wu, Chenglu Zhu, Sunyi Zheng, Qizi Chen, Kai Zhang, Yunlong Zhang, Dan Wan, Xiaoxiao Lan, Mengyue Zheng, Jingxiong Li, Xinheng Lyu, Tao Lin, Lin Yang

To address this, we introduce PathMMU, the largest and highest-quality expert-validated pathology benchmark for Large Multimodal Models (LMMs).

Benchmarking PathCLIP for Pathology Image Analysis

no code implementations5 Jan 2024 Sunyi Zheng, Xiaonan Cui, Yuxuan Sun, Jingxiong Li, Honglin Li, Yunlong Zhang, Pingyi Chen, Xueping Jing, Zhaoxiang Ye, Lin Yang

Additionally, we assess the robustness of PathCLIP in the task of image-image retrieval, revealing that PathCLIP performs less effectively than PLIP on Osteosarcoma but performs better on WSSS4LUAD under diverse corruptions.

Benchmarking Decision Making +4

Multi-modal Learning with Missing Modality in Predicting Axillary Lymph Node Metastasis

no code implementations3 Jan 2024 Shichuan Zhang, Sunyi Zheng, Zhongyi Shui, Honglin Li, Lin Yang

Using multi-modal data, whole slide images (WSIs) and clinical information, can improve the performance of deep learning models in the diagnosis of axillary lymph node metastasis.

Decision Making whole slide images

Unleashing the Power of Prompt-driven Nucleus Instance Segmentation

1 code implementation27 Nov 2023 Zhongyi Shui, Yunlong Zhang, Kai Yao, Chenglu Zhu, Sunyi Zheng, Jingxiong Li, Honglin Li, Yuxuan Sun, Ruizhe Guo, Lin Yang

In this paper, we present a novel prompt-driven framework that consists of a nucleus prompter and SAM for automatic nucleus instance segmentation.

Image Segmentation Instance Segmentation +3

Test-Time Training for Semantic Segmentation with Output Contrastive Loss

1 code implementation14 Nov 2023 Yunlong Zhang, Yuxuan Sun, Sunyi Zheng, Zhongyi Shui, Chenglu Zhu, Lin Yang

Although deep learning-based segmentation models have achieved impressive performance on public benchmarks, generalizing well to unseen environments remains a major challenge.

Domain Adaptation Image Classification +1

Attention-Challenging Multiple Instance Learning for Whole Slide Image Classification

1 code implementation13 Nov 2023 Yunlong Zhang, Honglin Li, Yuxuan Sun, Sunyi Zheng, Chenglu Zhu, Lin Yang

In the application of Multiple Instance Learning (MIL) methods for Whole Slide Image (WSI) classification, attention mechanisms often focus on a subset of discriminative instances, which are closely linked to overfitting.

Image Classification Multiple Instance Learning

Review on Decarbonizing the Transportation Sector in China: Overview, Analysis, and Perspectives

no code implementations1 Oct 2023 Jiewei Li, Ling Jin, Han Deng, Lin Yang

This review identifies challenges and effective strategies to decarbonize China's rapidly growing transportation sector, currently the third largest carbon emitter, considering China's commitment to peak carbon emissions by 2030 and achieve carbon neutrality by 2060.

Decision Making

Masked conditional variational autoencoders for chromosome straightening

no code implementations25 Jun 2023 Jingxiong Li, Sunyi Zheng, Zhongyi Shui, Shichuan Zhang, Linyi Yang, Yuxuan Sun, Yunlong Zhang, Honglin Li, Yuanxin Ye, Peter M. A. van Ooijen, Kang Li, Lin Yang

This yields a non-trivial reconstruction task, allowing the model to effectively preserve chromosome banding patterns and structure details in the reconstructed results.

On the Model-Misspecification in Reinforcement Learning

no code implementations19 Jun 2023 Yunfan Li, Lin Yang

However, in the face of model misspecification (a disparity between the ground-truth and optimal function approximators), it is shown that policy-based approaches can be robust even when the policy function approximation is under a large locally-bounded misspecification error, with which the function class may exhibit a $\Omega(1)$ approximation error in specific states and actions, but remains small on average within a policy-induced state distribution.

Open-Ended Question Answering reinforcement-learning +1

Low-Switching Policy Gradient with Exploration via Online Sensitivity Sampling

no code implementations15 Jun 2023 Yunfan Li, Yiran Wang, Yu Cheng, Lin Yang

We show that, our algorithm obtains an $\varepsilon$-optimal policy with only $\widetilde{O}(\frac{\text{poly}(d)}{\varepsilon^3})$ samples, where $\varepsilon$ is the suboptimality gap and $d$ is a complexity measure of the function class approximating the policy.

Reinforcement Learning (RL)

Semi-supervised Cell Recognition under Point Supervision

no code implementations14 Jun 2023 Zhongyi Shui, Yizhi Zhao, Sunyi Zheng, Yunlong Zhang, Honglin Li, Shichuan Zhang, Xiaoxuan Yu, Chenglu Zhu, Lin Yang

Overall, we use the current models to generate pseudo labels for unlabeled images, which are in turn utilized to supervise the models training.

whole slide images

PathAsst: A Generative Foundation AI Assistant Towards Artificial General Intelligence of Pathology

1 code implementation24 May 2023 Yuxuan Sun, Chenglu Zhu, Sunyi Zheng, Kai Zhang, Lin Sun, Zhongyi Shui, Yunlong Zhang, Honglin Li, Lin Yang

Secondly, by leveraging the collected data, we construct PathCLIP, a pathology-dedicated CLIP, to enhance PathAsst's capabilities in interpreting pathology images.

Instruction Following Language Modelling +1

MEDNC: Multi-ensemble deep neural network for COVID-19 diagnosis

no code implementations25 Apr 2023 Lin Yang, Shuihua Wang, Yudong Zhang

Coronavirus disease 2019 (COVID-19) has spread all over the world for three years, but medical facilities in many areas still aren't adequate.

Computed Tomography (CT) COVID-19 Diagnosis +1

DPA-P2PNet: Deformable Proposal-aware P2PNet for Accurate Point-based Cell Detection

no code implementations5 Mar 2023 Zhongyi Shui, Sunyi Zheng, Chenglu Zhu, Shichuan Zhang, Xiaoxuan Yu, Honglin Li, Jingxiong Li, Pingyi Chen, Lin Yang

Unlike mainstream PCD methods that rely on intermediate density map representations, the Point-to-Point network (P2PNet) has recently emerged as an end-to-end solution for PCD, demonstrating impressive cell detection accuracy and efficiency.

Cell Detection

On-Demand Communication for Asynchronous Multi-Agent Bandits

no code implementations15 Feb 2023 Yu-Zhen Janice Chen, Lin Yang, Xuchuang Wang, Xutong Liu, Mohammad Hajiesmaili, John C. S. Lui, Don Towsley

We propose ODC, an on-demand communication protocol that tailors the communication of each pair of agents based on their empirical pull times.

Biomedical image analysis competitions: The state of current participation practice

no code implementations16 Dec 2022 Matthias Eisenmann, Annika Reinke, Vivienn Weru, Minu Dietlinde Tizabi, Fabian Isensee, Tim J. Adler, Patrick Godau, Veronika Cheplygina, Michal Kozubek, Sharib Ali, Anubha Gupta, Jan Kybic, Alison Noble, Carlos Ortiz de Solórzano, Samiksha Pachade, Caroline Petitjean, Daniel Sage, Donglai Wei, Elizabeth Wilden, Deepak Alapatt, Vincent Andrearczyk, Ujjwal Baid, Spyridon Bakas, Niranjan Balu, Sophia Bano, Vivek Singh Bawa, Jorge Bernal, Sebastian Bodenstedt, Alessandro Casella, Jinwook Choi, Olivier Commowick, Marie Daum, Adrien Depeursinge, Reuben Dorent, Jan Egger, Hannah Eichhorn, Sandy Engelhardt, Melanie Ganz, Gabriel Girard, Lasse Hansen, Mattias Heinrich, Nicholas Heller, Alessa Hering, Arnaud Huaulmé, Hyunjeong Kim, Bennett Landman, Hongwei Bran Li, Jianning Li, Jun Ma, Anne Martel, Carlos Martín-Isla, Bjoern Menze, Chinedu Innocent Nwoye, Valentin Oreiller, Nicolas Padoy, Sarthak Pati, Kelly Payette, Carole Sudre, Kimberlin Van Wijnen, Armine Vardazaryan, Tom Vercauteren, Martin Wagner, Chuanbo Wang, Moi Hoon Yap, Zeyun Yu, Chun Yuan, Maximilian Zenk, Aneeq Zia, David Zimmerer, Rina Bao, Chanyeol Choi, Andrew Cohen, Oleh Dzyubachyk, Adrian Galdran, Tianyuan Gan, Tianqi Guo, Pradyumna Gupta, Mahmood Haithami, Edward Ho, Ikbeom Jang, Zhili Li, Zhengbo Luo, Filip Lux, Sokratis Makrogiannis, Dominik Müller, Young-tack Oh, Subeen Pang, Constantin Pape, Gorkem Polat, Charlotte Rosalie Reed, Kanghyun Ryu, Tim Scherr, Vajira Thambawita, Haoyu Wang, Xinliang Wang, Kele Xu, Hung Yeh, Doyeob Yeo, Yixuan Yuan, Yan Zeng, Xin Zhao, Julian Abbing, Jannes Adam, Nagesh Adluru, Niklas Agethen, Salman Ahmed, Yasmina Al Khalil, Mireia Alenyà, Esa Alhoniemi, Chengyang An, Talha Anwar, Tewodros Weldebirhan Arega, Netanell Avisdris, Dogu Baran Aydogan, Yingbin Bai, Maria Baldeon Calisto, Berke Doga Basaran, Marcel Beetz, Cheng Bian, Hao Bian, Kevin Blansit, Louise Bloch, Robert Bohnsack, Sara Bosticardo, Jack Breen, Mikael Brudfors, Raphael Brüngel, Mariano Cabezas, Alberto Cacciola, Zhiwei Chen, Yucong Chen, Daniel Tianming Chen, Minjeong Cho, Min-Kook Choi, Chuantao Xie Chuantao Xie, Dana Cobzas, Julien Cohen-Adad, Jorge Corral Acero, Sujit Kumar Das, Marcela de Oliveira, Hanqiu Deng, Guiming Dong, Lars Doorenbos, Cory Efird, Sergio Escalera, Di Fan, Mehdi Fatan Serj, Alexandre Fenneteau, Lucas Fidon, Patryk Filipiak, René Finzel, Nuno R. Freitas, Christoph M. Friedrich, Mitchell Fulton, Finn Gaida, Francesco Galati, Christoforos Galazis, Chang Hee Gan, Zheyao Gao, Shengbo Gao, Matej Gazda, Beerend Gerats, Neil Getty, Adam Gibicar, Ryan Gifford, Sajan Gohil, Maria Grammatikopoulou, Daniel Grzech, Orhun Güley, Timo Günnemann, Chunxu Guo, Sylvain Guy, Heonjin Ha, Luyi Han, Il Song Han, Ali Hatamizadeh, Tian He, Jimin Heo, Sebastian Hitziger, SeulGi Hong, Seungbum Hong, Rian Huang, Ziyan Huang, Markus Huellebrand, Stephan Huschauer, Mustaffa Hussain, Tomoo Inubushi, Ece Isik Polat, Mojtaba Jafaritadi, SeongHun Jeong, Bailiang Jian, Yuanhong Jiang, Zhifan Jiang, Yueming Jin, Smriti Joshi, Abdolrahim Kadkhodamohammadi, Reda Abdellah Kamraoui, Inha Kang, Junghwa Kang, Davood Karimi, April Khademi, Muhammad Irfan Khan, Suleiman A. Khan, Rishab Khantwal, Kwang-Ju Kim, Timothy Kline, Satoshi Kondo, Elina Kontio, Adrian Krenzer, Artem Kroviakov, Hugo Kuijf, Satyadwyoom Kumar, Francesco La Rosa, Abhi Lad, Doohee Lee, Minho Lee, Chiara Lena, Hao Li, Ling Li, Xingyu Li, Fuyuan Liao, Kuanlun Liao, Arlindo Limede Oliveira, Chaonan Lin, Shan Lin, Akis Linardos, Marius George Linguraru, Han Liu, Tao Liu, Di Liu, Yanling Liu, João Lourenço-Silva, Jingpei Lu, Jiangshan Lu, Imanol Luengo, Christina B. Lund, Huan Minh Luu, Yi Lv, Uzay Macar, Leon Maechler, Sina Mansour L., Kenji Marshall, Moona Mazher, Richard McKinley, Alfonso Medela, Felix Meissen, Mingyuan Meng, Dylan Miller, Seyed Hossein Mirjahanmardi, Arnab Mishra, Samir Mitha, Hassan Mohy-ud-Din, Tony Chi Wing Mok, Gowtham Krishnan Murugesan, Enamundram Naga Karthik, Sahil Nalawade, Jakub Nalepa, Mohamed Naser, Ramin Nateghi, Hammad Naveed, Quang-Minh Nguyen, Cuong Nguyen Quoc, Brennan Nichyporuk, Bruno Oliveira, David Owen, Jimut Bahan Pal, Junwen Pan, Wentao Pan, Winnie Pang, Bogyu Park, Vivek Pawar, Kamlesh Pawar, Michael Peven, Lena Philipp, Tomasz Pieciak, Szymon Plotka, Marcel Plutat, Fattaneh Pourakpour, Domen Preložnik, Kumaradevan Punithakumar, Abdul Qayyum, Sandro Queirós, Arman Rahmim, Salar Razavi, Jintao Ren, Mina Rezaei, Jonathan Adam Rico, ZunHyan Rieu, Markus Rink, Johannes Roth, Yusely Ruiz-Gonzalez, Numan Saeed, Anindo Saha, Mostafa Salem, Ricardo Sanchez-Matilla, Kurt Schilling, Wei Shao, Zhiqiang Shen, Ruize Shi, Pengcheng Shi, Daniel Sobotka, Théodore Soulier, Bella Specktor Fadida, Danail Stoyanov, Timothy Sum Hon Mun, Xiaowu Sun, Rong Tao, Franz Thaler, Antoine Théberge, Felix Thielke, Helena Torres, Kareem A. Wahid, Jiacheng Wang, Yifei Wang, Wei Wang, Xiong Wang, Jianhui Wen, Ning Wen, Marek Wodzinski, Ye Wu, Fangfang Xia, Tianqi Xiang, Chen Xiaofei, Lizhan Xu, Tingting Xue, Yuxuan Yang, Lin Yang, Kai Yao, Huifeng Yao, Amirsaeed Yazdani, Michael Yip, Hwanseung Yoo, Fereshteh Yousefirizi, Shunkai Yu, Lei Yu, Jonathan Zamora, Ramy Ashraf Zeineldin, Dewen Zeng, Jianpeng Zhang, Bokai Zhang, Jiapeng Zhang, Fan Zhang, Huahong Zhang, Zhongchen Zhao, Zixuan Zhao, Jiachen Zhao, Can Zhao, Qingshuo Zheng, Yuheng Zhi, Ziqi Zhou, Baosheng Zou, Klaus Maier-Hein, Paul F. Jäger, Annette Kopp-Schneider, Lena Maier-Hein

Of these, 84% were based on standard architectures.


Unsupervised Dense Nuclei Detection and Segmentation with Prior Self-activation Map For Histology Images

no code implementations14 Oct 2022 Pingyi Chen, Chenglu Zhu, Zhongyi Shui, Jiatong Cai, Sunyi Zheng, Shichuan Zhang, Lin Yang

To this end, we propose a self-supervised learning based approach with a Prior Self-activation Module (PSM) that generates self-activation maps from the input images to avoid labeling costs and further produce pseudo masks for the downstream task.

Image Segmentation Medical Image Segmentation +3

TC-SKNet with GridMask for Low-complexity Classification of Acoustic scene

no code implementations5 Oct 2022 Luyuan Xie, Yan Zhong, Lin Yang, Zhaoyu Yan, Zhonghai Wu, Junjie Wang

In our experiments, the performance gain brought by GridMask is stronger than spectrum augmentation in ASCs.

AutoML Data Augmentation

Adaptive Decision Making at the Intersection for Autonomous Vehicles Based on Skill Discovery

no code implementations24 Jul 2022 Xianqi He, Lin Yang, Chao Lu, Zirui Li, Jianwei Gong

But in uncertain environments, they are not reliable, so learning-based methods are proposed, especially reinforcement learning (RL) methods.

Autonomous Driving Decision Making +3

End-to-end cell recognition by point annotation

no code implementations1 Jul 2022 Zhongyi Shui, Shichuan Zhang, Chenglu Zhu, BingChuan Wang, Pingyi Chen, Sunyi Zheng, Lin Yang

Reliable quantitative analysis of immunohistochemical staining images requires accurate and robust cell detection and classification.

Cell Detection Multi-Task Learning

ChrSNet: Chromosome Straightening using Self-attention Guided Networks

no code implementations1 Jul 2022 Sunyi Zheng, Jingxiong Li, Zhongyi Shui, Chenglu Zhu, Yunlong Zhang, Pingyi Chen, Lin Yang

Karyotyping is an important procedure to assess the possible existence of chromosomal abnormalities.

Benchmarking the Robustness of Deep Neural Networks to Common Corruptions in Digital Pathology

1 code implementation30 Jun 2022 Yunlong Zhang, Yuxuan Sun, Honglin Li, Sunyi Zheng, Chenglu Zhu, Lin Yang

Evaluated on two resulting benchmark datasets, we find that (1) a variety of deep neural network models suffer from a significant accuracy decrease (double the error on clean images) and the unreliable confidence estimation on corrupted images; (2) A low correlation between the validation and test errors while replacing the validation set with our benchmark can increase the correlation.


Model-based Offline Imitation Learning with Non-expert Data

no code implementations11 Jun 2022 Jeongwon Park, Lin Yang

Although Behavioral Cloning (BC) in theory suffers compounding errors, its scalability and simplicity still makes it an attractive imitation learning algorithm.

Continuous Control Imitation Learning

Invariant Content Synergistic Learning for Domain Generalization of Medical Image Segmentation

no code implementations5 May 2022 Yuxin Kang, Hansheng Li, Xuan Zhao, Dongqing Hu, Feihong Liu, Lei Cui, Jun Feng, Lin Yang

In this paper, we propose a method, named Invariant Content Synergistic Learning (ICSL), to improve the generalization ability of DCNNs on unseen datasets by controlling the inductive bias.

Domain Generalization Image Segmentation +4

The low-entropy hydration shell at the binding site of spike RBD determines the contagiousness of SARS-CoV-2 variants

no code implementations27 Apr 2022 Lin Yang, Shuai Guo, Chengyu Houc, Jiacheng Lia, Liping Shi, Chenchen Liao, Rongchun Shi, Xiaoliang Ma, Bing Zheng, Yi Fang, Lin Ye, Xiaodong He

The low-entropy level of hydration shells at the binding site of a spike protein is found to be an important indicator of the contagiousness of the coronavirus.

Harmonizing Pathological and Normal Pixels for Pseudo-healthy Synthesis

1 code implementation29 Mar 2022 Yunlong Zhang, Xin Lin, Yihong Zhuang, LiyanSun, Yue Huang, Xinghao Ding, Guisheng Wang, Lin Yang, Yizhou Yu

Comprehensive experiments on the T2 modality of BraTS demonstrate that the proposed method substantially outperforms the state-of-the-art methods.

Generative Adversarial Network Image Enhancement +4

Weakly Supervised Learning for cell recognition in immunohistochemical cytoplasm staining images

no code implementations27 Feb 2022 Shichuan Zhang, Chenglu Zhu, Honglin Li, Jiatong Cai, Lin Yang

We have evaluated our framework on immunohistochemical cytoplasm staining images, and the results demonstrate that our method outperforms recent cell recognition approaches.

Multi-Task Learning Representation Learning +1

Space Layout of Low-entropy Hydration Shells Guides Protein Binding

no code implementations22 Feb 2022 Lin Yang, Shuai Guo, Chengyu Hou, Chencheng Liao, Jiacheng Li, Liping Shi, Xiaoliang Ma, Shenda Jiang, Bing Zheng, Yi Fang, Lin Ye, Xiaodong He

According to an analysis of determined protein complex structures, shape matching between the largest low-entropy hydration shell region of a protein and that of its partner at the binding sites is revealed as a regular pattern.

Distributed Bandits with Heterogeneous Agents

no code implementations23 Jan 2022 Lin Yang, Yu-Zhen Janice Chen, Mohammad Hajiesmaili, John CS Lui, Don Towsley

The goal for each agent is to find its optimal local arm, and agents can cooperate by sharing their observations with others.

Decision Making

Cross-Patch Dense Contrastive Learning for Semi-Supervised Segmentation of Cellular Nuclei in Histopathologic Images

1 code implementation CVPR 2022 Huisi Wu, Zhaoze Wang, Youyi Song, Lin Yang, Jing Qin

We study the semi-supervised learning problem, using a few labeled data and a large amount of unlabeled data to train the network, by developing a cross-patch dense contrastive learning framework, to segment cellular nuclei in histopathologic images.

Contrastive Learning Image Segmentation +1

Cooperative Stochastic Bandits with Asynchronous Agents and Constrained Feedback

no code implementations NeurIPS 2021 Lin Yang, Yu-Zhen Janice Chen, Stephen Pasteris, Mohammad Hajiesmaili, John C. S. Lui, Don Towsley

This paper studies a cooperative multi-armed bandit problem with $M$ agents cooperating together to solve the same instance of a $K$-armed stochastic bandit problem with the goal of maximizing the cumulative reward of agents.

Decision Making

On the Value of Interaction and Function Approximation in Imitation Learning

no code implementations NeurIPS 2021 Nived Rajaraman, Yanjun Han, Lin Yang, Jingbo Liu, Jiantao Jiao, Kannan Ramchandran

In contrast, when the MDP transition structure is known to the learner such as in the case of simulators, we demonstrate fundamental differences compared to the tabular setting in terms of the performance of an optimal algorithm, Mimic-MD (Rajaraman et al. (2020)) when extended to the function approximation setting.

Imitation Learning Multi-class Classification

Low-Latency Online Speaker Diarization with Graph-Based Label Generation

no code implementations27 Nov 2021 Yucong Zhang, Qinjian Lin, Weiqing Wang, Lin Yang, Xuyang Wang, Junjie Wang, Ming Li

To ensure the low latency in the online setting, we introduce a variant of AHC, namely chkpt-AHC, to cluster the speakers.

Clustering speaker-diarization +1

Discovery-and-Selection: Towards Optimal Multiple Instance Learning for Weakly Supervised Object Detection

no code implementations18 Oct 2021 Shiwei Zhang, Wei Ke, Lin Yang

Weakly supervised object detection (WSOD) is a challenging task that requires simultaneously learn object classifiers and estimate object locations under the supervision of image category labels.

Multiple Instance Learning Object +2

Decentralized Cooperative Multi-Agent Reinforcement Learning with Exploration

no code implementations29 Sep 2021 Weichao Mao, Tamer Basar, Lin Yang, Kaiqing Zhang

Many real-world applications of multi-agent reinforcement learning (RL), such as multi-robot navigation and decentralized control of cyber-physical systems, involve the cooperation of agents as a team with aligned objectives.

Multi-agent Reinforcement Learning Q-Learning +3

Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation

no code implementations10 Jul 2021 Hao Zheng, Jun Han, Hongxiao Wang, Lin Yang, Zhuo Zhao, Chaoli Wang, Danny Z. Chen

Unlike the current literature on task-specific self-supervised pretraining followed by supervised fine-tuning, we utilize SSL to learn task-agnostic knowledge from heterogeneous data for various medical image segmentation tasks.

Image Segmentation Medical Image Segmentation +4

Generalizing Nucleus Recognition Model in Multi-source Images via Pruning

no code implementations6 Jul 2021 Jiatong Cai, Chenglu Zhu, Can Cui, Honglin Li, Tong Wu, Shichuan Zhang, Lin Yang

In addition, the model is optimized by fine-tuning on merged domains to eliminate the interference of class mismatching among various domains.

Domain Generalization

A comparative study of neural network techniques for automatic software vulnerability detection

no code implementations29 Apr 2021 Gaigai Tang, Lianxiao Meng, Shuangyin Ren, Weipeng Cao, Qiang Wang, Lin Yang

To solve this problem, we have conducted extensive experiments to test the performance of the two most typical neural networks (i. e., Bi-LSTM and RVFL) with the two most classical data preprocessing methods (i. e., the vector representation and the program symbolization methods) on software vulnerability detection problems and obtained a series of interesting research conclusions, which can provide valuable guidelines for researchers and engineers.

Vulnerability Detection

TransfoRNN: Capturing the Sequential Information in Self-Attention Representations for Language Modeling

no code implementations4 Apr 2021 Tze Yuang Chong, Xuyang Wang, Lin Yang, Junjie Wang

Also, the TransfoRNN model was applied on the LibriSpeech speech recognition task and has shown comparable results with the Transformer models.

Language Modelling speech-recognition +1

Hydrophobic interaction determines docking affinity of SARS CoV 2 variants with antibodies

no code implementations28 Feb 2021 Jiacheng Li, Chengyu Hou, Menghao Wang, Chencheng Liao, Shuai Guo, Liping Shi, Xiaoliang Ma, Hongchi Zhang, Shenda Jiang, Bing Zheng, Lin Ye, Lin Yang, Xiaodong He

Preliminary epidemiologic, phylogenetic and clinical findings suggest that several novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have increased transmissibility and decreased efficacy of several existing vaccines.

Correction to the photometric magnitudes of the Gaia Early Data Release 3

no code implementations4 Jan 2021 Lin Yang, HaiBo Yuan, Ruoyi Zhang, Zexi Niu, Yang Huang, Fuqing Duan, Yi Fang

In this letter, we have carried out an independent validation of the Gaia EDR3 photometry using about 10, 000 Landolt standard stars from Clem & Landolt (2013).

Solar and Stellar Astrophysics Astrophysics of Galaxies

Unlabeled Data Guided Semi-supervised Histopathology Image Segmentation

no code implementations17 Dec 2020 Hongxiao Wang, Hao Zheng, Jianxu Chen, Lin Yang, Yizhe Zhang, Danny Z. Chen

Second, we devise an effective data selection policy for judiciously sampling the generated images: (1) to make the generated training set better cover the dataset, the clusters that are underrepresented in the original training set are covered more; (2) to make the training process more effective, we identify and oversample the images of "hard cases" in the data for which annotated training data may be scarce.

Clustering Image Generation +3

Is Long Horizon RL More Difficult Than Short Horizon RL?

no code implementations NeurIPS 2020 Ruosong Wang, Simon S. Du, Lin Yang, Sham Kakade

In a COLT 2018 open problem, Jiang and Agarwal conjectured that, for tabular, episodic reinforcement learning problems, there exists a sample complexity lower bound which exhibits a polynomial dependence on the horizon --- a conjecture which is consistent with all known sample complexity upper bounds.

reinforcement-learning Reinforcement Learning (RL)

Adversarial Bandits with Corruptions: Regret Lower Bound and No-regret Algorithm

no code implementations NeurIPS 2020 Lin Yang, Mohammad Hajiesmaili, Mohammad Sadegh Talebi, John C. S. Lui, Wing Shing Wong

We characterize the regret of ExpRb as a function of the corruption budget and show that for the case of a known corruption budget, the regret of ExpRb is tight.

Planning with General Objective Functions: Going Beyond Total Rewards

no code implementations NeurIPS 2020 Ruosong Wang, Peilin Zhong, Simon S. Du, Russ R. Salakhutdinov, Lin Yang

Standard sequential decision-making paradigms aim to maximize the cumulative reward when interacting with the unknown environment., i. e., maximize $\sum_{h = 1}^H r_h$ where $H$ is the planning horizon.

Decision Making

A Thermodynamics Model for Mechanochemical Synthesis of Gold Nanoparticles: Implications for Solvent-free Nanoparticle Production

no code implementations25 Nov 2020 Lin Yang, Audrey Moores, Tomislav Friščić, Nikolas Provatas

Mechanochemistry is becoming an established method for the sustainable, solid-phase synthesis of scores of nano-materials and molecules, ranging from active pharmaceutical ingredients to materials for cleantech.

Chemical Physics

SuperOCR: A Conversion from Optical Character Recognition to Image Captioning

no code implementations21 Nov 2020 Baohua Sun, Michael Lin, Hao Sha, Lin Yang

The existing methods normally detect where the characters are, and then recognize the character for each detected location.

Image Captioning License Plate Recognition +2

A hydrophobic-interaction-based mechanism trigger docking between the SARS CoV 2 spike and angiotensin-converting enzyme 2

no code implementations27 Aug 2020 Jiacheng Li, Xiaoliang Ma, Shuai Guo, Chengyu Hou, Liping Shi, Hongchi Zhang, Bing Zheng, Chencheng Liao, Lin Yang, Lin Ye, Xiaodong He

The hydrophobic interaction between the SARS-CoV-2 S and ACE2 protein is found to be significantly greater than that between SARS-CoV S and ACE2.

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

Nearly Linear Row Sampling Algorithm for Quantile Regression

no code implementations ICML 2020 Yi Li, Ruosong Wang, Lin Yang, Hanrui Zhang

We give a row sampling algorithm for the quantile loss function with sample complexity nearly linear in the dimensionality of the data, improving upon the previous best algorithm whose sampling complexity has at least cubic dependence on the dimensionality.


Acoustic Word Embedding System for Code-Switching Query-by-example Spoken Term Detection

no code implementations24 May 2020 Murong Ma, Haiwei Wu, Xuyang Wang, Lin Yang, Jun-Jie Wang, Ming Li

In this paper, we propose a deep convolutional neural network-based acoustic word embedding system on code-switching query by example spoken term detection.

Word Embeddings

DIHARD II is Still Hard: Experimental Results and Discussions from the DKU-LENOVO Team

no code implementations23 Feb 2020 Qingjian Lin, Weicheng Cai, Lin Yang, Jun-Jie Wang, Jun Zhang, Ming Li

Our diarization system includes multiple modules, namely voice activity detection (VAD), segmentation, speaker embedding extraction, similarity scoring, clustering, resegmentation and overlap detection.

Action Detection Activity Detection +1

Lesion Harvester: Iteratively Mining Unlabeled Lesions and Hard-Negative Examples at Scale

1 code implementation21 Jan 2020 Jinzheng Cai, Adam P. Harrison, Youjing Zheng, Ke Yan, Yuankai Huo, Jing Xiao, Lin Yang, Le Lu

This is the goal of our work, where we develop a powerful system to harvest missing lesions from the DeepLesion dataset at high precision.

End-to-End Adversarial Shape Learning for Abdomen Organ Deep Segmentation

no code implementations15 Oct 2019 Jinzheng Cai, Yingda Xia, Dong Yang, Daguang Xu, Lin Yang, Holger Roth

However, it is challenging to train the conventional CNN-based segmentation models that aware of the shape and topology of organs.

Organ Segmentation Pancreas Segmentation +1

SuperTML: Two-Dimensional Word Embedding and Transfer Learning Using ImageNet Pretrained CNN Models for the Classifications on Tabular Data

no code implementations28 May 2019 Baohua Sun, Lin Yang, Wenhan Zhang, Michael Lin, Patrick Dong, Charles Young and Jason Dong

The recent work of Super Characters method using two-dimensional word embedding achieved state-of-the-art results in text classification tasks, showcasing the promise of this new approach.

text-classification Text Classification +1

SuperCaptioning: Image Captioning Using Two-dimensional Word Embedding

no code implementations25 May 2019 Baohua Sun, Lin Yang, Michael Lin, Charles Young, Patrick Dong, Wenhan Zhang, Jason Dong

In this paper, we propose the SuperCaptioning method, which borrows the idea of two-dimensional word embedding from Super Characters method, and processes the information of language and vision together in one single CNN model.

General Classification Image Captioning +4

SuperChat: Dialogue Generation by Transfer Learning from Vision to Language using Two-dimensional Word Embedding and Pretrained ImageNet CNN Models

no code implementations7 May 2019 Baohua Sun, Lin Yang, Michael Lin, Charles Young, Jason Dong, Wenhan Zhang, Patrick Dong

The recent work of Super Characters method using two-dimensional word embedding achieved state-of-the-art results in text classification tasks, showcasing the promise of this new approach.

Dialogue Generation General Classification +3

SPDA: Superpixel-based Data Augmentation for Biomedical Image Segmentation

no code implementations28 Feb 2019 Yizhe Zhang, Lin Yang, Hao Zheng, Peixian Liang, Colleen Mangold, Raquel G. Loreto, David. P. Hughes, Danny Z. Chen

To better mimic human visual perception, we think it is desirable for the deep learning model to be able to perceive not only raw images but also SP images.

Data Augmentation Image Segmentation +1

Squared English Word: A Method of Generating Glyph to Use Super Characters for Sentiment Analysis

no code implementations24 Jan 2019 Baohua Sun, Lin Yang, Catherine Chi, Wenhan Zhang, Michael Lin

The Super Characters method addresses sentiment analysis problems by first converting the input text into images and then applying 2D-CNN models to classify the sentiment.

General Classification Sentence +1

Cascade Decoder: A Universal Decoding Method for Biomedical Image Segmentation

no code implementations15 Jan 2019 Peixian Liang, Jianxu Chen, Hao Zheng, Lin Yang, Yizhe Zhang, Danny Z. Chen

The cascade decoder structure aims to conduct more effective decoding of hierarchically encoded features and is more compatible with common encoders than the known decoders.

Decoder Image Segmentation +2

A New Ensemble Learning Framework for 3D Biomedical Image Segmentation

1 code implementation10 Dec 2018 Hao Zheng, Yizhe Zhang, Lin Yang, Peixian Liang, Zhuo Zhao, Chaoli Wang, Danny Z. Chen

In this paper, we propose a new ensemble learning framework for 3D biomedical image segmentation that combines the merits of 2D and 3D models.

3D Medical Imaging Segmentation Ensemble Learning +3

Near-Optimal Time and Sample Complexities for Solving Markov Decision Processes with a Generative Model

no code implementations NeurIPS 2018 Aaron Sidford, Mengdi Wang, Xian Wu, Lin Yang, Yinyu Ye

In this paper we consider the problem of computing an $\epsilon$-optimal policy of a discounted Markov Decision Process (DMDP) provided we can only access its transition function through a generative sampling model that given any state-action pair samples from the transition function in $O(1)$ time.

CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement

no code implementations18 Jul 2018 Youbao Tang, Jinzheng Cai, Le Lu, Adam P. Harrison, Ke Yan, Jing Xiao, Lin Yang, Ronald M. Summers

The first GAN reduces the noise in the CT image and the second GAN generates a higher resolution image with enhanced boundaries and high contrast.

Computed Tomography (CT) Image Enhancement +3

Iterative Attention Mining for Weakly Supervised Thoracic Disease Pattern Localization in Chest X-Rays

no code implementations3 Jul 2018 Jinzheng Cai, Le Lu, Adam P. Harrison, Xiaoshuang Shi, Pingjun Chen, Lin Yang

Given image labels as the only supervisory signal, we focus on harvesting, or mining, thoracic disease localizations from chest X-ray images.

General Classification Image Classification

Deep Learning Based Instance Segmentation in 3D Biomedical Images Using Weak Annotation

no code implementations28 Jun 2018 Zhuo Zhao, Lin Yang, Hao Zheng, Ian H. Guldner, Si-Yuan Zhang, Danny Z. Chen

Our approach needs only 3D bounding boxes for all instances and full voxel annotation for a small fraction of the instances, and uses a novel two-stage 3D instance segmentation model utilizing these two kinds of annotation, respectively.

3D Instance Segmentation Segmentation +1

Ultra Power-Efficient CNN Domain Specific Accelerator with 9.3TOPS/Watt for Mobile and Embedded Applications

no code implementations30 Apr 2018 Baohua Sun, Lin Yang, Patrick Dong, Wenhan Zhang, Jason Dong, Charles Young

Furthermore, in order to better support real-world deployment for various application scenarios, especially with low-end mobile and embedded platforms and MCUs (Microcontroller Units), we also designed algorithms to fully utilize the CNN-DSA accelerator efficiently by reducing the dependency on external accelerator computation resources, including implementation of Fully-Connected (FC) layers within the accelerator and compression of extracted features from the CNN-DSA accelerator.

Pancreas Segmentation in CT and MRI Images via Domain Specific Network Designing and Recurrent Neural Contextual Learning

no code implementations30 Mar 2018 Jinzheng Cai, Le Lu, Fuyong Xing, Lin Yang

Automatic pancreas segmentation in radiology images, eg., computed tomography (CT) and magnetic resonance imaging (MRI), is frequently required by computer-aided screening, diagnosis, and quantitative assessment.

Computed Tomography (CT) Pancreas Segmentation +1

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

Dimensionality Reduction for Stationary Time Series via Stochastic Nonconvex Optimization

no code implementations NeurIPS 2018 Minshuo Chen, Lin Yang, Mengdi Wang, Tuo Zhao

Specifically, our goal is to estimate the principle component of time series data with respect to the covariance matrix of the stationary distribution.

Dimensionality Reduction Stochastic Optimization +2

Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Network

no code implementations CVPR 2018 Zizhao Zhang, Lin Yang, Yefeng Zheng

In this work, we propose a generic cross-modality synthesis approach with the following targets: 1) synthesizing realistic looking 3D images using unpaired training data, 2) ensuring consistent anatomical structures, which could be changed by geometric distortion in cross-modality synthesis and 3) improving volume segmentation by using synthetic data for modalities with limited training samples.

Computed Tomography (CT) Generative Adversarial Network +3

Photographic Text-to-Image Synthesis with a Hierarchically-nested Adversarial Network

1 code implementation CVPR 2018 Zizhao Zhang, Yuanpu Xie, Lin Yang

This paper presents a novel method to deal with the challenging task of generating photographic images conditioned on semantic image descriptions.

Image Generation Semantic Similarity +1

A New Registration Approach for Dynamic Analysis of Calcium Signals in Organs

no code implementations1 Feb 2018 Peixian Liang, Jianxu Chen, Pavel A. Brodskiy, Qinfeng Wu, Yejia Zhang, Yizhe Zhang, Lin Yang, Jeremiah J. Zartman, Danny Z. Chen

A key to analyzing spatial-temporal patterns of $Ca^{2+}$ signal waves is to accurately align the pouches across image sequences.

Accurate Weakly Supervised Deep Lesion Segmentation on CT Scans: Self-Paced 3D Mask Generation from RECIST

no code implementations25 Jan 2018 Jinzheng Cai, You-Bao Tang, Le Lu, Adam P. Harrison, Ke Yan, Jing Xiao, Lin Yang, Ronald M. Summers

Toward this end, we introduce a convolutional neural network based weakly supervised self-paced segmentation (WSSS) method to 1) generate the initial lesion segmentation on the axial RECIST-slice; 2) learn the data distribution on RECIST-slices; 3) adapt to segment the whole volume slice by slice to finally obtain a volumetric segmentation.

Generative Adversarial Network Lesion Segmentation +2

Recursive Exponential Weighting for Online Non-convex Optimization

no code implementations13 Sep 2017 Lin Yang, Cheng Tan, Wing Shing Wong

In this paper, we investigate the online non-convex optimization problem which generalizes the classic {online convex optimization problem by relaxing the convexity assumption on the cost function.

Uncertainty measurement with belief entropy on interference effect in Quantum-Like Bayesian Networks

no code implementations8 Sep 2017 Zhiming Huang, Lin Yang, Wen Jiang

Social dilemmas have been regarded as the essence of evolution game theory, in which the prisoner's dilemma game is the most famous metaphor for the problem of cooperation.

Overcoming the time limitation in Molecular Dynamics simulation of crystal nucleation: a persistent-embryo approach

no code implementations31 Aug 2017 Yang Sun, Huajing Song, Feng Zhang, Lin Yang, Zhuo Ye, Mikhail I. Mendelev, Cai-Zhuang Wang, Kai-Ming Ho

The crystal nucleation from liquid in most cases is too rare to be accessed within the limited timescales of the conventional molecular dynamics (MD) simulation.

Materials Science Soft Condensed Matter

Recent Advances in the Applications of Convolutional Neural Networks to Medical Image Contour Detection

no code implementations24 Aug 2017 Zizhao Zhang, Fuyong Xing, Hai Su, Xiaoshuang Shi, Lin Yang

Then we review their recent applications in medical image analysis and point out limitations, with the goal to light some potential directions in medical image analysis.

Contour Detection

TandemNet: Distilling Knowledge from Medical Images Using Diagnostic Reports as Optional Semantic References

no code implementations10 Aug 2017 Zizhao Zhang, Pingjun Chen, Manish Sapkota, Lin Yang

In this paper, we introduce the semantic knowledge of medical images from their diagnostic reports to provide an inspirational network training and an interpretable prediction mechanism with our proposed novel multimodal neural network, namely TandemNet.

Language Modelling

Improving Deep Pancreas Segmentation in CT and MRI Images via Recurrent Neural Contextual Learning and Direct Loss Function

no code implementations16 Jul 2017 Jinzheng Cai, Le Lu, Yuanpu Xie, Fuyong Xing, Lin Yang

The output layer of this network module is then connected to recurrent layers and can be fine-tuned for contextual learning, in an end-to-end manner.

Pancreas Segmentation Segmentation

MDNet: A Semantically and Visually Interpretable Medical Image Diagnosis Network

no code implementations CVPR 2017 Zizhao Zhang, Yuanpu Xie, Fuyong Xing, Mason McGough, Lin Yang

In this paper, we propose MDNet to establish a direct multimodal mapping between medical images and diagnostic reports that can read images, generate diagnostic reports, retrieve images by symptom descriptions, and visualize attention, to provide justifications of the network diagnosis process.

Language Modelling Sentence

Microscopic Muscle Image Enhancement

no code implementations17 Dec 2016 Xiangfei Kong, Lin Yang

Ring artifacts problems are addressed and a kernel propagation strategy is proposed to speedup the algorithm and deals with the high non-uniformity of the blur kernels on muscle images.

Deblurring Image Deconvolution +1

SemiContour: A Semi-supervised Learning Approach for Contour Detection

no code implementations CVPR 2016 Zizhao Zhang, Fuyong Xing, Xiaoshuang Shi, Lin Yang

In this paper, we investigate the usage of semi-supervised learning (SSL) to obtain competitive detection accuracy with very limited training data (three labeled images).

Contour Detection Ensemble Learning

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