CakeResume 找人才
進階搜尋
On
4 到 6 年
6 到 10 年
10 到 15 年
15 年以上
就學中
・
目前會考慮了解新的機會
全職 / 對遠端工作有興趣
4 到 6 年
國立中正大學(National Chung Cheng University)
・
Computer Science and Information Engineering
Computer Vision Engineer @Academia Sinica2015 ~ 現在
・
Computer Vision Engineer
一個月內
陳昱希 Computer Vision Engineer Yu-Hsi Chen has rich experience in developing computer vision and machine learning algorithms. In his recent work at Academia Sinica, he has focused on using machine learning to solve traditional computer vision and image / video processing problems. His developed NeighborTrack is a state-of-the-art single object tracking system in the field. During his school days, he used verilog on FPGA to implement the 3A system of the camera. website: Yu-hsi Chen (franktpmvu.github.io) Taipei City, Taiwan Yu-hsi Chen (franktpmvu.github
目前會考慮了解新的機會
全職 / 對遠端工作有興趣
6 到 10 年
LUNGHWA university
・
Master of ScienceBlockchain Enginner & AI Lead @Portal Network
Blockchain engineer & Blockchain consulting
一個月內
全職 / 對遠端工作有興趣
4 到 6 年
Principal Engineer @Coretronic Corporation, 中強光電2020 ~ 2022
・
Machine Learning Engineer
一個月內
Senior Software Developer, Wuduker Inc., JanuaryOctober 2020 iSchedule, a preference aware scheduling system. Responsible for designing RESTful API, database schema and core scheduling solver Anomaly detection system with Deep Metric Learning Develop deep learning model with PyTroch and PyTorch-Lightning Consulting service. Including Spark pipeline optimization, deep learning model development and general Python/C++ development Machine Learning Engineer, Pinkoi Inc., DecemberDecember 2019 Recommendation System, including item-based/store-based recommendation, keyword suggestion, making significant improvement on recommendation quality and coverage. Machine Learning Algorithm Design Data Pipeline, including on-site advertising and
就職中
全職 / 對遠端工作有興趣
6 到 10 年
國立台灣大學
・
經濟學
Research Assistant of National Taiwan University @National Taiwan University2023 ~ 現在
・
Graduate research assistant
半年內
YEN-TING CHEN (陳彥廷) I am a graduate student in the Department of Psychology at National Taiwan University ( NTU). For me, diving into psychometrics and exploring data with reasonable statistical method is to clarify a new world of understanding people around us. Whether it's a quirky little issue or a big, serious one, I've got curiosity and grabbed my attention to figure out problems using the tools or theories of psychometrics and data analysis . Right now, I am turning curiosity into discoveries in the wild world of Psychology and All kinds of Data
就學中
兼職 / 對遠端工作有興趣
4 到 6 年
National Taiwan University
・
Psychometrics (Division of Psychology), Methodology (Division of Psychology)
AI, Machine Learning and Data Manager @IRT Saint Exupery2021 ~ 現在
・
Data Analyst、Data Scientist、AI Engineer、Project Manager
一個月內
Benjamin Deporte [email protected] AI, Machine Learning and Data Officer Innovative AI/ML seasoned leader with strong mathematical background and hands-on knowledge of machine learning algorithms and best practices. Specialized in Cybersecurity, Healthcare and Aerospace. Demonstrated driving business value through 10+ years of experience within different businesses, in direct management or thought leadership roles. Leadership, networking, communication and language skills. Skills Expertise in Artificial Intelligence and Machine Learning Specialization in Cybersecurity, Healthcare and Aerospace. Leadership abilities, networking and communication skills Business acumen in multicultural, global organizations Work
就職中
全職 / 對遠端工作有興趣
6 到 10 年
Télécom Paris
・
Cybersecurity
曾任
Senior Software Engineer @DOINT2021 ~ 2023
・
Software engineer, Image Processing engineer, Algorithm engineer
三個月內
Docker Doxygen Swig (API for python from C++) OpenCV OpenCL Linux Skill multi-threads distributed computing serialization/deserialization CICD data version control (DVC) MLOps Image Processing PCA Interactive Segmentation Connected Component Image Stitching Direct Linear Transformation Kalman Filter (Tracking) SIFT Hough HoG Image Deblurring Depth Estimation ISP Machine Learning Framework Transformation Data Augmentation Transfer Learning Model Pruning Model Quantization Performance Evaluation Parameter Fine-tuning Model : SVM, LeNet, AlexNet, VGG, GoogLeNet, SSD, YOLO, MobileNet, ShuffleNet, FaceNet, Xception, MatrixNet, CenterNet, CSPNet, M2Det, EfficientNet/Det Projects HPC Keyword Spotting Automatic Speech Recognition Distributed Inference System Social Distancing Estimation (Lidar
待業中
全職 / 對遠端工作有興趣
6 到 10 年
National Taiwan University
・
Communication Engineering
機器學習工程師 @日新軟體股份有限公司2021 ~ 現在
・
AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
半年內
focus mainly on object detection, sensor fusion and sensor calibration. 3+ years of experience in machine learning. Used to conduct research in medical AI projects and possess experience in implement real-world end-to-end ML project . Skills Programming Languages Python C++ SQL Machine Learning TensorFlow Pytorch Scikit-learn Matplotlib Others FastAPI Docker Redis Linux Certification Taiwan AI Academy - AI Technical Professionals Program NVIDIA DLI Certificate – Applications of AI for Anomaly Detection Work Experience Machine Learning Engineer NEUTEC • MayPresent Develop, optimize and maintain the machine learning algorithm for internal process automation. Deploy machine
就職中
全職 / 對遠端工作有興趣
4 到 6 年
國立臺北科技大學
・
機電整合所AI & Embedded Systems Consultant @Self Employed2021 ~ 現在
・
Deep Learning Engineer
超過一年
Kishan Gondaliya Experienced embedded software engineer working on Embedded Systems and Deep Learning to enable vision and voice-based machine learning algorithms on low-power FPGA and edge embedded devices. ~8 years of experience consists in writing, debugging, and optimizing software/firmware for embedded [email protected] Ahmedabad, Gujarat, India Skillset Languages: Frameworks: Dev Tools: HW Platform: Cloud (GCP): Cloud (AWS): Other: C, Python, C++ Tensorflow (TFlite, TFmicro), Keras, Caffe, Darknet Anaconda, Git, Gerrit, Perforce, Pycharm, CVS, Jira, Confluence Google Coral TPU, Lattice ECP5, U+, Crosslin-NX FPGA, Raspberry Pi, Intel Movidius, NVIDIA
就職中
全職 / 對遠端工作有興趣
4 到 6 年
Charotar University of Science & Technology
・
Electronics & CommunicationData Scientist | Associate Researcher @China Engineering Consultants, Inc.2020 ~ 現在
・
資料分析師
超過一年
就職中
全職 / 對遠端工作有興趣
6 到 10 年
國立東華大學(National Dong Hwa University)
・
應用數學研究所最輕量、快速的招募方案，數百家企業的選擇
搜尋履歷，主動聯繫求職者，提升招募效率。
- 瀏覽所有搜尋結果
- 每日可無限次數開啟陌生對話
- 搜尋僅開放付費企業檢視的履歷
- 檢視使用者信箱 & 電話
搜尋技巧
1
嘗試搜尋最精準的關鍵字組合
資深 後端 php laravel
2
將須完全符合的字詞放在雙引號中
"社群行銷"
3
在不想搜尋到的字詞前面加上減號，如果想濾掉中文字，需搭配雙引號使用 (-"人資")
UI designer -UX
職場能力評價定義
專業技能
該領域中具備哪些專業能力（例如熟悉 SEO 操作，且會使用相關工具）。
問題解決能力
能洞察、分析問題，並擬定方案有效解決問題。
變通能力
遇到突發事件能冷靜應對，並隨時調整專案、客戶、技術的相對優先序。
溝通能力
有效傳達個人想法，且願意傾聽他人意見並給予反饋。
時間管理能力
了解工作項目的優先順序，有效運用時間，準時完成工作內容。
團隊合作能力
具有向心力與團隊責任感，願意傾聽他人意見並主動溝通協調。
領導力
專注於團隊發展，有效引領團隊採取行動，達成共同目標。
專業背景
目前狀態
就職中
求職階段
專業
數據科學家
產業
工作年資
小於 1 年
管理經歷
無
技能
語言能力
English
・
專業
Chinese
・
母語或雙語
求職偏好
希望獲得的職位
機器學習工程師
預期工作模式
全職
期望的工作地點
Taipei, 台灣, Kaohsiung City, 台灣
遠端工作意願
對遠端工作有興趣
接案服務
否
學歷
學校
Tsinghua University
主修科系
Computer Science
Hsuehkuan Lu
Machine Learning Engineer
Highly focused, cooperative, and with strong learning ability. Passionate about machine learning, natural language processing/understanding, and data science. Practical experiences in ML projects with Python, and GraphQL API design. Proficient in implementing algorithms and researching.
Education
2016 - 2019
Tsinghua University
Master of Science, Computer Science
Knowledge Engineering Group (KEG) Lab
2012 - 2016
National Central University
Bachelor of Science, Computer Science and Information Engineering
Work Experience
Algorithm Engineer • HIPR PacSoft Technologies
August 2020 - Present
- Model MySQL 30+ tables, and Elasticsearch 10+ indices.
- Design GraphQL APIs with Flask, and write unit tests.
- Design NLP data processing pipeline (500M+ data) ranges from Google Scholar, world university rankings, journal rankings to institution rankings.
- Design distributed crawling and computing systems with Dask, and asynchronous data processing methods (3-4x faster).
- Import object-relational mapping of Elasticsearch, improving the organization of search engine indices mappings, and simplifying queries.
Projects
Impactio
- Develop social network applications for academic researchers.
- Design large data pipeline for institutions (750K+), journals (35K+), authors (250M+), and publications (230M+).
- Design distributed crawling and on-the-fly merging systems for Google Scholar profile with Dask (avg. 3-5 MIN per user).
- Design cursor-based pagination method with GraphQL to improve built-in offset-based pagination method by 10%+ efficiency.
- Main backend APIs developer in the project (70%+).
News Miner
- Developed news centering and trend/topic analysis applications.
- Designed English news data processing pipeline (5K+ per day), and topical news clustering with semantic representations.
- Adopted Word2Vec distributed representations with k-means clustering to produce text features, and designed a single-pass clustering method to merge related news.
- Handled 100K+ news in 10 MIN, largely improved the processing performance by 250%-300% comparing to k-means clustering.
POS Tagging and Dependency Parsing
- Combined POS tagging with dependency parsing so as to alleviate the error propagation problems and enriched sequence tagging information across tasks.
- Experimental results on dataset Universal Dependency 2.0 achieved 81.14 with LAS (Labelled Attachment Score) averagely, while baseline scored 72.14 with LAS (11% improvement).
- The ablation tests indicated that the POS tagging information largely improved the performance of dependency parsing by 10%.
- Tagging system was implemented in Tensorflow with Python, and was able to annotate 1K+ sentences per MIN.
Wikipedia Data Processing and Joint Representations of Entities and Texts
- Tackled the parallel corpus reliance on the cross-lingual problems and enriched textual information with external knowledge information.
- Designed a weakly-supervised algorithm to produce aligned cross-lingual corpus (avg. 300K+ paragraphs per language pair).
- Jointly modeled knowledge entities and texts with the model derived from Skip-Gram with Negative Sampling algorithm and made word vectors (300d) public.
- Achieved 44.99 Pearson-r in SemEval-2017 Track 4a task (En-Es), while end-to-end LASER model achieved 40.87 Pearson-r (10% improvement).
- Proposed a cross-lingual information retrievement task, and our proposed method achieved 80% Top-10 Accuracy, while the strongest baseline acquired 61% Top-10 Accuracy (30% significant improvement).
Skills
Programming Languages
Python
C++
Java
Framework and Data Analysis
Tensorflow
PyTorch
Pandas
Jupyter Lab
Dask
GraphQL
Database and Search Engine
MySQL
Elasticsearch
MongoDB
VCS and CI/CD Tools
Git
Bitbucket
Alembic
Jenkins
Publications
- Hsuehkuan Lu, Yixin Cao, Lei Hou, and Juanzi Li. Knowledge-Enhanced Bilingual Textual Representations for Cross-Lingual Semantic Textual Similarity. International Conference of Pioneering Computer Scientists, Engineers and Educators (ICPCSEE), 2019. CCIS Volume 1058, pages 425-440.
- Hsuehkuan Lu, Lei Hou, and Juanzi Li. How Important Is POS to Dependency Parsing? Joint POS Tagging and Dependency Parsing Neural Networks. Chinese Computational Lingustics (CCL), 2019. LNCS, Volume 11856, pages 625-637.
呂學寬
機器學習工程師
Machine Learning Engineer
專注力強，樂於合作，學習能力強。對機器學習、自然語言處理/理解以及資料科學充滿熱情。擅長以Python做數據分析，實作機器學習專案，以及設計 GraphQL API。具備熟練實作算法模型以及研究能力。
Email: [email protected]
Phone: (+886) 905193233
工作經驗
算法工程師 • HIPR PacSoft Technologies
八月 2020 - Present
- MySQL 30+表架構模型建立，以及 Elasticsearch 10+索引架構模型建立。
- 利用 GraphQL + Flask 設計後端 API，並撰寫單元測試。
- 自然語言處理資料處理流程設計（合計約5億筆資料），包含Google Scholar、世界大學排名、期刊排名，以及學術機構排名資料。
- 設計 Dask 分布式計算、爬蟲（16+ workers），以及 Asyncio 非同步資料處理流程（約提升3-4倍效能）。
專案
Impactio
- 針對學術研究者設計的社交網絡。
- 設計大量資料處理流程：學術機構 (750K+)、期刊 (35K+)、作者 (250M+) 以及學術論文 (230M+)。
- 利用 Dask 設計 Google Scholar 使用者資料分布式爬蟲方法，以及實時合併處理系統 (平均每個使用者 3-5 MIN)。
- 設計 GraphQL cursor-based 分頁方法，優化內建 offset-based 分頁方法，效率提升約 10%+。
- 專案後端 API 服務的主要開發者 (70%+)。
News Miner
- 開發跨新聞媒體及趨勢、主題分析應用。
- 設計英文新聞的資料處理流程 (每日5K+)，以及新聞主題聚類方法設計、文本語義表示學習。
- 採用 Word2Vec 詞向量 + k-means 聚類方法生成文本特徵，並設計單向聚類方法合併相似新聞。
- 系統平均 10 分鐘能處理 100K+ 筆新聞，而採用 k-means 方法則需要 10x 以上的時間才能達到收斂。
詞性標註與依存句法分析
- 結合詞性標註到依存句法任務中，以降低彼此任務間的錯誤信息傳遞，並增強跨任務間的結構信息。
- 在 Universal Dependency 2.0 的數據集上，我們提出的方法達到 81.14 LAS (多語言平均)，baseline 為 72.14 LAS，提出方法提升約 11%。
- 對照實驗顯示詞性信息對於依存句法分析的預測有約 10%+的影響。
- 標注系統由 Tensorflow + Python 實作，處理速度約每分鐘1K+。
維基百科數據處理及聯合知識文本表示學習
- 解決跨語言方法對於平行語料的依賴，並嘗試結合知識實體到文本中以增強文本信息。
- 設計弱監督算法生成維基百科跨語言語料 (平均每語言對 300K+ 段落)。
- 算法基於負採樣 Skip-Gram 算法聯合學習知識實體、文本表示，並公開實驗訓練出的詞向量 (300d)。
- 在 SemEval-2017 Track 4a 跨語言 (En-Es) 文本語義相似度任務中達到 44.99 Pearson-r，對比端到端模型 LASER 40.87 Pearson-r 提升近 10%。
- 提出跨語言信息檢索任務，我們的方法達到 80% Top-10 Accuracy，對比 baseline 實驗 61% 有大幅提升 (30%)。
技能
程式語言
Python
C++
Java
框架及資料分析工具
Tensorflow
PyTorch
Pandas
Jupyter Lab
Dask
GraphQL
資料庫及搜尋引擎
MySQL
Elasticsearch
MongoDB
版控及CI/CD工具
Git
Bitbucket
Alembic
Jenkins
論文發表
- Hsuehkuan Lu, Yixin Cao, Lei Hou, and Juanzi Li. Knowledge-Enhanced Bilingual Textual Representations for Cross-Lingual Semantic Textual Similarity. International Conference of Pioneering Computer Scientists, Engineers and Educators (ICPCSEE), 2019. CCIS Volume 1058, pages 425-440.
- Hsuehkuan Lu, Lei Hou, and Juanzi Li. How Important Is POS to Dependency Parsing? Joint POS Tagging and Dependency Parsing Neural Networks. Chinese Computational Lingustics (CCL), 2019. LNCS, Volume 11856, pages 625-637.
End
Hsuehkuan Lu
Machine Learning Engineer
Highly focused, cooperative, and with strong learning ability. Passionate about machine learning, natural language processing/understanding, and data science. Practical experiences in ML projects with Python, and GraphQL API design. Proficient in implementing algorithms and researching.
Education
2016 - 2019
Tsinghua University
Master of Science, Computer Science
Knowledge Engineering Group (KEG) Lab
2012 - 2016
National Central University
Bachelor of Science, Computer Science and Information Engineering
Work Experience
Algorithm Engineer • HIPR PacSoft Technologies
August 2020 - Present
- Model MySQL 30+ tables, and Elasticsearch 10+ indices.
- Design GraphQL APIs with Flask, and write unit tests.
- Design NLP data processing pipeline (500M+ data) ranges from Google Scholar, world university rankings, journal rankings to institution rankings.
- Design distributed crawling and computing systems with Dask, and asynchronous data processing methods (3-4x faster).
- Import object-relational mapping of Elasticsearch, improving the organization of search engine indices mappings, and simplifying queries.
Projects
Impactio
- Develop social network applications for academic researchers.
- Design large data pipeline for institutions (750K+), journals (35K+), authors (250M+), and publications (230M+).
- Design distributed crawling and on-the-fly merging systems for Google Scholar profile with Dask (avg. 3-5 MIN per user).
- Design cursor-based pagination method with GraphQL to improve built-in offset-based pagination method by 10%+ efficiency.
- Main backend APIs developer in the project (70%+).
News Miner
- Developed news centering and trend/topic analysis applications.
- Designed English news data processing pipeline (5K+ per day), and topical news clustering with semantic representations.
- Adopted Word2Vec distributed representations with k-means clustering to produce text features, and designed a single-pass clustering method to merge related news.
- Handled 100K+ news in 10 MIN, largely improved the processing performance by 250%-300% comparing to k-means clustering.
POS Tagging and Dependency Parsing
- Combined POS tagging with dependency parsing so as to alleviate the error propagation problems and enriched sequence tagging information across tasks.
- Experimental results on dataset Universal Dependency 2.0 achieved 81.14 with LAS (Labelled Attachment Score) averagely, while baseline scored 72.14 with LAS (11% improvement).
- The ablation tests indicated that the POS tagging information largely improved the performance of dependency parsing by 10%.
- Tagging system was implemented in Tensorflow with Python, and was able to annotate 1K+ sentences per MIN.
Wikipedia Data Processing and Joint Representations of Entities and Texts
- Tackled the parallel corpus reliance on the cross-lingual problems and enriched textual information with external knowledge information.
- Designed a weakly-supervised algorithm to produce aligned cross-lingual corpus (avg. 300K+ paragraphs per language pair).
- Jointly modeled knowledge entities and texts with the model derived from Skip-Gram with Negative Sampling algorithm and made word vectors (300d) public.
- Achieved 44.99 Pearson-r in SemEval-2017 Track 4a task (En-Es), while end-to-end LASER model achieved 40.87 Pearson-r (10% improvement).
- Proposed a cross-lingual information retrievement task, and our proposed method achieved 80% Top-10 Accuracy, while the strongest baseline acquired 61% Top-10 Accuracy (30% significant improvement).
Skills
Programming Languages
Python
C++
Java
Framework and Data Analysis
Tensorflow
PyTorch
Pandas
Jupyter Lab
Dask
GraphQL
Database and Search Engine
MySQL
Elasticsearch
MongoDB
VCS and CI/CD Tools
Git
Bitbucket
Alembic
Jenkins
Publications
- Hsuehkuan Lu, Yixin Cao, Lei Hou, and Juanzi Li. Knowledge-Enhanced Bilingual Textual Representations for Cross-Lingual Semantic Textual Similarity. International Conference of Pioneering Computer Scientists, Engineers and Educators (ICPCSEE), 2019. CCIS Volume 1058, pages 425-440.
- Hsuehkuan Lu, Lei Hou, and Juanzi Li. How Important Is POS to Dependency Parsing? Joint POS Tagging and Dependency Parsing Neural Networks. Chinese Computational Lingustics (CCL), 2019. LNCS, Volume 11856, pages 625-637.
呂學寬
機器學習工程師
Machine Learning Engineer
專注力強，樂於合作，學習能力強。對機器學習、自然語言處理/理解以及資料科學充滿熱情。擅長以Python做數據分析，實作機器學習專案，以及設計 GraphQL API。具備熟練實作算法模型以及研究能力。
Email: [email protected]
Phone: (+886) 905193233
工作經驗
算法工程師 • HIPR PacSoft Technologies
八月 2020 - Present
- MySQL 30+表架構模型建立，以及 Elasticsearch 10+索引架構模型建立。
- 利用 GraphQL + Flask 設計後端 API，並撰寫單元測試。
- 自然語言處理資料處理流程設計（合計約5億筆資料），包含Google Scholar、世界大學排名、期刊排名，以及學術機構排名資料。
- 設計 Dask 分布式計算、爬蟲（16+ workers），以及 Asyncio 非同步資料處理流程（約提升3-4倍效能）。
專案
Impactio
- 針對學術研究者設計的社交網絡。
- 設計大量資料處理流程：學術機構 (750K+)、期刊 (35K+)、作者 (250M+) 以及學術論文 (230M+)。
- 利用 Dask 設計 Google Scholar 使用者資料分布式爬蟲方法，以及實時合併處理系統 (平均每個使用者 3-5 MIN)。
- 設計 GraphQL cursor-based 分頁方法，優化內建 offset-based 分頁方法，效率提升約 10%+。
- 專案後端 API 服務的主要開發者 (70%+)。
News Miner
- 開發跨新聞媒體及趨勢、主題分析應用。
- 設計英文新聞的資料處理流程 (每日5K+)，以及新聞主題聚類方法設計、文本語義表示學習。
- 採用 Word2Vec 詞向量 + k-means 聚類方法生成文本特徵，並設計單向聚類方法合併相似新聞。
- 系統平均 10 分鐘能處理 100K+ 筆新聞，而採用 k-means 方法則需要 10x 以上的時間才能達到收斂。
詞性標註與依存句法分析
- 結合詞性標註到依存句法任務中，以降低彼此任務間的錯誤信息傳遞，並增強跨任務間的結構信息。
- 在 Universal Dependency 2.0 的數據集上，我們提出的方法達到 81.14 LAS (多語言平均)，baseline 為 72.14 LAS，提出方法提升約 11%。
- 對照實驗顯示詞性信息對於依存句法分析的預測有約 10%+的影響。
- 標注系統由 Tensorflow + Python 實作，處理速度約每分鐘1K+。
維基百科數據處理及聯合知識文本表示學習
- 解決跨語言方法對於平行語料的依賴，並嘗試結合知識實體到文本中以增強文本信息。
- 設計弱監督算法生成維基百科跨語言語料 (平均每語言對 300K+ 段落)。
- 算法基於負採樣 Skip-Gram 算法聯合學習知識實體、文本表示，並公開實驗訓練出的詞向量 (300d)。
- 在 SemEval-2017 Track 4a 跨語言 (En-Es) 文本語義相似度任務中達到 44.99 Pearson-r，對比端到端模型 LASER 40.87 Pearson-r 提升近 10%。
- 提出跨語言信息檢索任務，我們的方法達到 80% Top-10 Accuracy，對比 baseline 實驗 61% 有大幅提升 (30%)。
技能
程式語言
Python
C++
Java
框架及資料分析工具
Tensorflow
PyTorch
Pandas
Jupyter Lab
Dask
GraphQL
資料庫及搜尋引擎
MySQL
Elasticsearch
MongoDB
版控及CI/CD工具
Git
Bitbucket
Alembic
Jenkins
論文發表
- Hsuehkuan Lu, Yixin Cao, Lei Hou, and Juanzi Li. Knowledge-Enhanced Bilingual Textual Representations for Cross-Lingual Semantic Textual Similarity. International Conference of Pioneering Computer Scientists, Engineers and Educators (ICPCSEE), 2019. CCIS Volume 1058, pages 425-440.
- Hsuehkuan Lu, Lei Hou, and Juanzi Li. How Important Is POS to Dependency Parsing? Joint POS Tagging and Dependency Parsing Neural Networks. Chinese Computational Lingustics (CCL), 2019. LNCS, Volume 11856, pages 625-637.
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