| 查看: 5947 | 回复: 29 | |||
| 【有奖交流】积极回复本帖子，参与交流，就有机会分得作者 shawn2047 的 14 个金币 ，回帖就立即获得 1 个金币，每人有 1 次机会 | |||
| 当前只显示满足指定条件的回帖，点击这里查看本话题的所有回帖 | |||
[交流]
Special issue@Machine Learning Journal: Foundations of Data Science
|
|||
|
data science is a hot topic with an extensive scope, both in terms of theory and applications. machine learning forms one of its core foundational pillars. simultaneously, data science applications provide important challenges that can often be addressed only with innovative machine learning algorithms and methodologies. this special issue will highlight the latest development of the machine learning foundations of data science and on the synergy of data science and machine learning. we welcome new developments in statistics, mathematics, informatics and computing-driven machine learning for data science, including foundations, algorithms and models, systems, innovative applications and other research contributions. following the great success of the 2021 mlj special issue with dsaa'2021, this 2022 special issue will further capture the state-of-the-art machine learning advances for data science. accepted papers will be published in mlj and presented at a journal track of the 2022 ieee international conference on data science and advanced analytics (dsaa'2022) in shenzhen, october 2022. topics of interest we welcome original and well-grounded research papers on all aspects of foundations of data science including but not limited to the following topics: machine learning foundations for data science • auto-ml • information fusion from disparate sources • feature engineering, embedding, mining and representation • learning from network and graph data • learning from data with domain knowledge • reinforcement learning • non-iid learning, nonstationary, coupled and entangled learning • heterogeneous, mixed, multimodal, multi-view and multi-distributional learning • online, streaming, dynamic and real-time learning • causality and learning causal models • multi-instance, multi-label, multi-class and multi-target learning • semi-supervised and weakly supervised learning • representation learning of complex interactions, couplings, relations • deep learning theories and models • evaluation of data science systems • open domain/set learning emerging impactful machine learning applications • data preprocessing, manipulation and augmentation • autonomous learning and optimization systems • digital, social, economic and financial (finance, fintech, blockchains and cryptocurrencies) analytics • graph and network embedding and mining • machine learning for recommender systems, marketing, online and e-commerce • augmented reality, computer vision and image processing • risk, compliance, regulation, anomaly, debt, failure and crisis • cybersecurity and information disorder, misinformation/fake detection • human-centered and domain-driven data science and learning • privacy, ethics, transparency, accountability, responsibility, trust, reproducibility and retractability • fairness, explainability and algorithm bias • green and energy-efficient, scalable, cloud/distributed and parallel analytics and infrastructures • iot, smart city, smart home, telecommunications, 5g and mobile data science and learning • government and enterprise data science • transportation, manufacturing, procurement, and industry 4.0 • energy, smart grids and renewable energies • agricultural, environmental and spatio-temporal analytics and climate change contributions must contain new, unpublished, original and fundamental work relating to the machine learning journal's mission. all submissions will be reviewed using rigorous scientific criteria whereby the novelty of the contribution will be crucial. submission instructions submit manuscripts to: https://mach.edmgr.com. select this special issue as the article type. papers must be prepared in accordance with the journal guidelines: https://www.springer.com/journal/10994 all papers will be reviewed following standard reviewing procedures for the journal. key dates we will have a continuous submission/review process starting in oct. 2021. last paper submission deadline: 1 march 2022 paper acceptance: 1 june 2022 camera-ready: 15 june 2022 guest editors longbing cao, university of technology sydney, australia joão gama, university of porto, portugal nitesh chawla, university of notre dame, united states joshua huang, shenzhen university, china |
回复此楼» 猜你喜欢
2026国自然函评费到账
已经有10人回复
-
filecode，4个jtjc了
已经有16人回复
-
售一区SCI文章T0P，我:8O.551.O54,科目全,可十急
已经有4人回复
-
人气不行了
已经有8人回复
-
今天基金会出结果吗？20260819
已经有17人回复
-
售SCI一区T0P文章，我:8O.55.1.O.54,科目全,可伽急
已经有9人回复
-
时间戳今天，20号变了
已经有5人回复
-
放榜前的不淡定
已经有14人回复
-
建议基金发布提前给出明确的时间点
已经有13人回复
-
今日不放榜？网传国自然预计 8 月 27 日可查结果
已经有20人回复
» 抢金币啦！回帖就可以得到:
-
告别流水线爽文！108万字完结仙侠《女娲石之灵石奇缘（仙界篇）》值得细品
+1/9026
-
散金祈福
+5/4020
-
散金祈福
+5/1190
-
每年这时候我都再仔细读一遍《范进中举》
+1/477
-
华西生物制药研究院招聘科研助理
+2/402
-
诚征另一半
+1/178
-
上海交通大学张航课题组招聘博士后（电化学储能）
+1/89
-
Polymers 期刊特刊 组稿
+1/79
-
焦虑
+1/69
-
强耀生物金秋开学季活动，2026年8月18日-10月31日，肽库筛选低至2W5
+3/49
-
***大叔找对象（沪深等地）
+1/34
-
瑞典-博后-固态电池-粘结剂-锂离子电池方向
+1/29
-
流放岭南浮肿了求救
+1/23
-
pcold 原核表达载体
+1/11
-
祈祷老公中国基
+1/8
-
中科院大连化学物理研究所 招聘 催化剂研发方向 科研助理 2名
+1/6
-
南方医科大学深圳医院陈烨/余涛教授课题组联合培养博士后招聘
+1/6
-
找女友
+1/5
-
出全新蔡司 Plan?APOCHROMAT 20×/0.8 平场复消色差物镜
+1/2
-
基因组大数据解析：从深渊鱼类到AI蛋白质设计-AI本地大模型部署内存到底要多大
+1/1
23楼2026-08-05 20:39:48
简单回复
tzynew2楼
2022-02-15 12:43
回复
shawn2047(金币+1): 谢谢参与
看i 发自小木虫Android客户端
超级老快7楼
2022-02-20 07:41
回复
shawn2047(金币+1): 谢谢参与
， 发自小木虫Android客户端
fufa331010楼
2026-05-25 12:29
回复
bjdxyxy3楼
2022-02-15 12:47
回复
shawn2047(金币+1): 谢谢参与
。 发自小木虫Android客户端
bjdxyxy5楼
2022-02-17 22:18
回复
bjdxyxy6楼
2022-02-18 22:54
回复
