In addition to that, we propose a shared task on one of the challenging SDU tasks, i.e., acronym extraction and disambiguation in multiple languages text. Extended abstract up to 2 pages are also welcome. Document structure and layout learning and recognition. Optimal transport-based machine learning paradigms; Trustworthy machine learning from the perspective of optimal transport. Causal inference is one of the main areas of focus in artificial intelligence (AI) and machine learning (ML) communities. Publication in HC-SSL does not prohibit authors from publishing their papers in archival venues such as NeurIPS/ICLR/ICML or IEEE/ACM Conferences and Journals. Liang Zhao, Jiangzhuo Chen, Feng Chen, Wei Wang, Chang-Tien Lu, and Naren Ramakrishnan. Key obstacles include lack of high-quality data, difficulty in embedding complex scientific and engineering knowledge in learning, and the need for high-dimensional design space exploration under constrained budgets. Design, Automation and Test in Europe Conference (DATE 2020), long paper, (acceptance rate: 26%), accepted. Finally, there is an increasing interest in AI in moving beyond traditional supervised learning approaches towards learning causal models, which can support the identification of targeted behavioral interventions. Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment. We will also have a video component for remote participation. Note: The workshop is a collaboration between NASSMA organisation, Deepmind and UM6P. IEEE Transactions on Neural Networks and Learning Systems (Impact Factor: 14.255), accepted. These lead to security considerations: (1) securing personal health information, genetic material, intellectual property, and digital health records, (2) balancing privacy rights and data ownership concerns in solutions using network and mobile data, (3) defending AI for biology use cases to deter automated attacks at scale. In addition to the keynote and presentations of accepted works, the workshop will include both a general discussion session on defining and addressing the key challenges in this area , and a lightning tutorial session that will include brief overviews and demos of relevant tools, including open source frameworks such as Ecole. Negar Etemadyrad, Yuyang Gao, Qingzhe Li, Xiaojie Guo, Frank Krueger, Qixiang Lin, Deqiang Qiu, and Liang Zhao. Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao. [Best Paper Candidate]. Yuyang Gao, Lingfei Wu, Houman Homayoun, and Liang Zhao. Geoinformatica, (impact factor: 2.392), Volume 20, Issue 4, pp 765-795, Oct 2016. PDF suitable for ArXiv repository (4 to 8 pages). Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. These submissions would benefit from additional exposure and discussion that can shape a better future publication. In Proceedings of the IEEE International Conference on Big Data (BigData 2014), pp. Handwritten recognition in business documents. Tanmoy Chowdhury, Chen Ling, Xuchao Zhang, Xujiang Zhao, Guangji Bai, Jian Pei, Haifeng Chen, Liang Zhao. If it turns out that the architecture is not appropriate for the task, the user must repeatedly adjust the architecture and retrain the network until an acceptable architecture has been obtained. Information extraction and information retrieval for scientific documents; Question answering and question generation for scholarly documents; Word sense disambiguation, acronym identification and expansion, and definition extraction; Document summarization, text mining, document topic classification, and machine reading comprehension for scientific documents; Graph analysis applications including knowledge graph construction and representation, graph reasoning and query knowledge graphs; Biomedical image processing, scientific image plagiarism detection, and data visualization; Code/Pseudo-code generation from text and im-age/diagram captioning, New language understanding resources such as new syn-tactic/semantic parsers, language models or techniques to encode scholarly text; Survey or analysis papers on scientific document under-standing and new tasks and challenges related to each scientific domain; Factuality, data verification, and anti-science detection. Spatial Auto-regressive Dependency Interpretable Learning Based on Spatial Topological Constraints. Attendance is open to all registered participants. It will start with a 60-minute mini-tutorial covering the basics of RL in games, and will include 2-4 invited talks by prominent contributors to the field, paper presentations, a poster session, and will close with a discussion panel. Submitting a short or long paper to VDS will give authors a chance to present at VDS events at both ACM KDD 2022(hybrid) and IEEE VIS 2022( hybrid). All submissions must be anonymous and conform to AAAI standards for double-blind review. However, you may visit "Cookie Settings" to provide a controlled consent. 40, no. Junxiang Wang and Liang Zhao. The deadline for the submissions is July 31st, 2022 11.59 PM (Anywhere on Earth time). The workshop will include original contributions on theory, methods, systems, and applications of data mining, machine learning, databases, network theory, natural language processing, knowledge representation, artificial intelligence, semantic web, and big data analytics in web-based healthcare applications, with a focus on applications in population and personalized health. However, ML systems may be non-deterministic; they may re-use high-quality implementations of ML algorithms; and, the semantics of models they produce may be incomprehensible. Explainable Agency captures the idea that AI systems will need to be trusted by human agents and, as autonomous agents themselves must be able to explain their decisions and the reasoning that produced their choices (Langley et al., 2017). We will accept the extended abstracts of the relevant and recently published work too. In addition, several invited speakers with distinguished professional background will give talks related the frontier topics of GNN. 1-39, November 2016. Xiaojie Guo, Yuanqi Du, Liang Zhao. Please note that foreign students must allow for 3 to 6 months to complete all the formalities required to study in Canada. Yujie Fan, Yiming Zhang, Shifu Hou, Lingwei Chen, Yanfang Ye, Chuan Shi, Liang Zhao, Shouhuai Xu. in Proceedings of the 22st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2016), applied data science track, accepted (acceptance rate: 19.9%), pp. We have invited several distinguished speakers with their research interests spanning from the theoretical to experimental aspects of complex networks. We invite submissions of full papers, as well as works-in-progress, position papers, and papers describing open problems and challenges. For papers that rely heavily on empirical evaluations, the experimental methods and results should be clear, well executed, and repeatable. The consideration and experience of adversarial ML from industry and policy making. 1, Sec. Please use vds@ieeevis.org to get in touch with us, or follow us on Twitter at @VisualDataSci. At the AAAI 2022 Workshop on Video Transcript Understanding (VTU @ AAAI 2022), we aim to bring together researchers from various domains to make the best of the knowledge that all these videos contain. [code] This workshop will follow a dual-track format. Yuyang Gao, Giorgio Ascoli, Liang Zhao. Deep Classifier Cascades for Open World Recognition. We expect 50~75 participants and potentially more according to our past experiences. Submissions will be accepted via the Easychair submission website. Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs. SIAM International Conference on Data Mining (SDM 2023) (Acceptance Rate: 27.4%), accepted. Submissions will be peer-reviewed, single-blinded, and assessed based on their novelty, technical quality, significance, clarity, and relevance regarding the workshop topics. A challenge is how to integrate people into the learning loop in a way that is transparent, efficient, and beneficial to the human-AI team as a whole, supporting different requirements and users with different levels of expertise. 205-214, San Francisco, California, Aug 2016. The eligibility criteria for attending the workshop will be registration in the conference/workshop as per AAAI norms. 4 pages) papers describing research at the intersection of AI and science/engineering domains including chemistry, physics, power systems, materials, catalysis, health sciences, computing systems design and optimization, epidemiology, agriculture, transportation, earth and environmental sciences, genomics and bioinformatics, civil and mechanical engineering etc. Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu Aggarwal, and Chang-Tien Lu. The workshop will be organized as a full day meeting. SIGKDD Explorations, Vol. The fundamental mechanism of an online marketplace is to match supply and demand to generate transactions, with objectives considering service quality, participants experience, financial and operational efficiency. Our goal is to build a stronger community of researchers exploring these methods, and to find synergies among these related approaches and alternatives. SDU will also host a session for presenting the short research papers and the system reports of the shared tasks. Deadlines are shown in America/Los_Angeles time. 47, no. AI System Robustness: participants will consider techniques for detecting and mitigating vulnerabilities at each of the processing stages of an AI system, including: the input stage of sensing and measurement, the data conditioning stage, during training and application of machine learning algorithms, the human-machine teaming stage, and during operational use. Second, psychological experiments in laboratories and in the field, in partnership with technology companies (e.g., using apps), to measure behavioral outcomes are being increasingly used for informing intervention design. Neurocomputing (Impact Factor: 5.719), accepted. Jinliang Ding, Liang Zhao, Changxin Liu, and Tianyou Chai. Information theory has demonstrated great potential to solve the above challenges. Deadline: Fri Jun 09 2023 04:59:00 GMT-0700 Yahoo! Objectives of ADAM include outlining the main research challenges in this area, cross-pollinating collaborations between AI researchers and domain experts in engineering design and manufacturing, and sketching open problems of common interest. Topics of interest in the biomedical space include: Topics of general interest to cyber-security include: Submission site:https://easychair.org/conferences/?conf=aics22, Tamara Broderick (MIT CSAIL, tamarab@mit.edu), James Holt (Laboratory for Physical Sciences, USA, holt@lps.umd.edu), Edward Raff (Booz Allen Hamilton, USA, Raff_Edward@bah.com), Ahmad Ridley (National Security Agency), Dennis Ross (MIT Lincoln Laboratory, USA, dennis.ross@ll.mit.edu), Arunesh Sinha (Singapore Management University, Singapore, aruneshs@smu.edu.sg), Diane Staheli (MIT Lincoln Laboratory, USA, diane.staheli@ll.mit.edu), William W. Streilein (MIT Lincoln Laboratory, USA, wws@ll.mit.edu), Milind Tambe (Harvard University, USA, milind_tambe@harvard.edu), Yevgeniy Vorobeychik (Washington University in Saint Louis, USA, eug.vorobey@gmail.com) Allan Wollaber (MIT Lincoln Laboratory, USA, Allan.Wollaber@ll.mit.edu), Supplemental workshop site:http://aics.site/. Causality has received significant interest in ML in recent years in part due to its utility for generalization and robustness. considered to be more practical and more related with real-world applications. Securing personal information, genomics, and intellectual property, Adversarial attacks and defenses on biomedical datasets, Detecting and preventing spread of misinformation, Usable security and privacy for digital health information, Phishing and other attacks using health information, Novel use of biometrics to enhance security, Machine learning (including RL) security and resiliency, Automation of data labeling and ML techniques, Operational and commercial applications of AI, Explanations of security decisions and vulnerability of explanations. December, 12-16, 2022. Submission site:https://cmt3.research.microsoft.com/DSTC102022, Koichiro Yoshino,Address: 2-2-2, Seika, Sohraku, Kyoto, 6190288, JapanAffiliation: RIKENPhone: +81-774-95-1360Email: koichiro.yoshino@riken.jp, Yun-Nung (Vivian) ChenAddress: No. BEAN: Interpretable and Efficient Learning with Biologically-Enhanced Artificial Neuronal Assembly. The goal of ITCI22 is to bring together researchers working at the intersection of information theory, causal inference and machine learning in order to foster new collaborations and provide a venue to brainstorm new ideas, exemplify to the information theory community causal inference and discovery as an application area and highlight important technical challenges motivated by practical ML problems, draw the attention of the wider machine learning community to the problems at the intersection of causal inference and information theory, and demonstrate to the community the utility of information-theoretic tools to tackle causal ML problems. This cookie is set by GDPR Cookie Consent plugin. How can the financial services industry balance the regulatory compliance and model governance pressures with adaptive models, Methods to combine scientific knowledge and data to build accurate predictive models, Adaptive experiment design under resource constraints, Learning cheap surrogate models to accelerate simulations, Learning effective representations for structured data, Uncertainty quantification and reasoning tools for decision-making, Explainable AI for both prediction and decision-making, Integrating AI tools into existing workflows, Challenges in applying and deployment of AI in the real-world. Besides academia, many companies and institutions are researching on topics specific to their particular domains. The Institute for Operations Research and the Management Sciences, [Submission deadline extended, June 3] KDD 2022 Workshop on Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail, and Beyond, We are excited to announce our upcoming workshop at. Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, and Yanfang Ye. ACM, 2013. The role of adjacent fields of study (e.g, computational social science) in mitigating issues of bias and trust in AI. For further information, please have a look at the call for contributions. "A Uniform Representation for Trajectory Learning Tasks", 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL 2017), short paper, DOI=10.1145/3139958.3140017, Redondo Beach, CA, USA, Nov 2017. Furthermore, DNNs are data greedy in the context of supervised learning, and not well developed for limited label learning, for instance for semi-supervised learning, self-supervised learning, or unsupervised learning. 4 pages), and position (max. Both the research papers track and the applied data science papers track will take . At least three research trends are informing insights in this field. Submission Site:https://cmt3.research.microsoft.com/SAS2022, Abdelrahman Mohamed (Facebook, abdo@fb.com), Hung-yi Lee (NTU, hungyilee@ntu.edu.tw), Shinji Watanabe (CMU, shinjiw@ieee.org), Tara Sainath (Google, tsainath@google.com), Karen Livescu (TTIC, klivescu@ttic.edu), Shang-Wen Li (Facebook, shangwel@fb.com), Ewan Dunbar (University of Toronto, ewan.dunbar@utoronto.ca) Emmanuel Dupoux (EHESS/Facebook, dpx@fb.com), Workshop URL:https://aaai-sas-2022.github.io/. Graph Neural Networks: Foundations, Frontiers, and Applications. Full papers: Submissions must represent original material that has not appeared elsewhere for publication and that is not under review for another refereed publication. 5, pp. Inspired by the question, there is a trend in the machine learning community to adopt self-supervised approaches to pre-train deep networks. to protect data owner privacy in FL. Topics of interest include but are not limited to: Acronyms, i.e., short forms of long phrases, are common in scientific writing. Novel algorithms and theories to improve model robustness. . Submissions introducing interesting experimental phenomena and open problems of optimal transport and structured data modeling are welcome as well. Track 1 covers the issues and algorithms pertinent to general online marketplaces as well as specific problems and applications arising from those diverse domains, such as ridesharing, online retail, food delivery, house rental, real estate, and more. Disentangled Spatiotemporal Graph Generative Model. Innovation, Service, and Rising Star Awards. To push forward the research on acronym understanding in scientific text, we propose two shared tasks on acronym extraction (i.e., recognizing acronyms and phrases in text) and disambiguation (i.e., finding the correct expansion for an ambiguous acronym). The submitted papers written in English must be in PDF format according to the AAAI camera ready style. The industry session will emphasize practical industrial product developments using GNNs. This workshop seeks to explore new ideas on AI safety with particular focus on addressing the following questions: Contributions are sought in (but are not limited to) the following topics: To deliver a truly memorable event, we will follow a highly interactive format that will include invited talks and thematic sessions. We are interested in a broad range of topics, both foundational and applied. One recommended setting for Latex file is:\documentclass[sigconf, review]{acmart}. We will specifically invite participants of the DSTC10 tasks, track organizers, and authors of accepted papers in the general technical track. This date takes priority over those shown below and could be extended for some programs. and Simone Stumpf (Univ. "Key Player Identification in Underground Forums over Attributed Heterogeneous Information Network Embedding Framework",The 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), long paper, (acceptance rate: 19.4%), Beijing, China, accepted. This workshop aims to explore and advance the current state of research and practice, including but not limited to the following topics: In addition to the invited talks and the panel discussion on topics related to Document Intelligence, the workshop program will include paper sessions which provides an opportunity to present peer-reviewed work on the topic related to Document Intelligence. Undergraduate (bachelor's, certificate, etc. The cookie is used to store the user consent for the cookies in the category "Other. Frontiers in Big Data, accepted, 2021. Universit de MontralOffice of Admissions and RecruitmentC. RES: A Robust Framework for Guiding Visual Explanation. Advances in AI technology, particularly perception and planning, have enabled unprecedented advances in autonomy, with autonomous systems playing an increasingly important role in day-to-day lives, with applications including IoT, drones, and autonomous vehicles. The papers have to be submitted through EasyChair. KDD is the premier Data Science conference. Submission link:https://easychair.org/cfp/raisa-2022, William Streilein, MIT Lincoln Laboratory, 244 Wood St., Lexington, MA, 02420, (781) 981-7200, wws@ll.mit.edu, Olivia Brown (MIT Lincoln Laboratory, Olivia.Brown@ll.mit.edu), Rajmonda Caceres (MIT Lincoln Laboratory, Rajmonda.Caceres@ll.mit.edu), Tina Eliassi-Rad (Northeastern University, teliassirad@northeastern.edu), David Martinez (MIT Lincoln Laboratory, dmartinez@ll.mit.edu), Sanjeev Mohindra (MIT Lincoln Laboratory, smohindra@ll.mit.edu), Elham Tabassi (National Institute of Standards and Technology, elham.tabassi@nist.gov), Workshop URL:https://sites.google.com/view/raisa-2022/. Moreover, the operational context in which AI systems are deployed necessitates consideration of robustness and its relation to principles of fairness, privacy, and explainability. Machine Learning-Based Delay-Aware UAV Detection and Operation Mode Identification over Encrypted Wi-Fi Traffic. For authors who do not wish their papers to be posted online, please mention this in the workshop submission. At the same time, multimodal hate-speech detection is an important problem but has not received much attention. Novel algorithmic solutions to causal inference or discovery problems using information-theoretic tools or assumptions. It does not store any personal data. Liang Gou, Bosch Research (IEEE VIS liaison), Claudia Plant, University of Vienna (KDD liaison), Alvitta Ottley, Washington University, St. Louis, Junming Shao, University of Electronic Science and Technology of China, Visualization in Data Science (VDS at ACM KDD and IEEE VIS), Visualization in Data Science (VDS at ACM KDD and IEEE VIS). We invite participants to submit papers by the 12th of November, based on but not limited to, the following topics: RL in various formalisms: one-shot games, turn-based, and Markov games, partially-observable games, continuous games, cooperative games; deep RL in games; combining search and RL in games; inverse RL in games; foundations, theory, and game-theoretic algorithms for RL; opponent modeling; analyses of learning dynamics in games; evolutionary methods for RL in games; RL in games without the rules; search and planning; and online learning in games. simulation, evaluation and experimentation. Junxiang Wang, Hongyi Li, Liang Zhao. "Multi-Task Learning for Spatio-Temporal Event Forecasting." Submissions will go through a double-blind review process. All the submissions should be anonymous. KDD 2022. Junxiang Wang, Liang Zhao, Yanfang Ye, and Yuji Zhang. Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang, Kun Xu, Liang Zhao, Xi Peng, Yinglong Xia and Charu Aggarwal, "Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding", In the Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2019), research track (acceptance rate: 14.2%), accepted, Alaska, USA, Aug 2019. This workshop starts with acknowledging the fundamental challenges of robustness and adaptiveness in financial services modeling and explores systematic solutions to solve these underlying problems to prevent future failures. Fang Jin, Wei Wang, Liang Zhao, Edward Dougherty, Yang Cao, Chang-Tien Lu, and Naren Ramakrishnan. Question answering on business documents. Online marketplace is a digital platform that connects buyers (demand) and sellers (supply) and provides exposure opportunities that individual participants would not otherwise have access to. For example: The workshop will be a 1-day event with a number of invited talks by prominent researchers, a panel discussion, and a combination of oral and poster presentations of accepted papers. the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018) (acceptance rate: 20.6%), Stockholm, Sweden, Jul 2018, accepted. 2022. KDD 2022 is a dual-track conference that provides distinct programming in research and applied data science. [slides] sup-port vector machine (SVM), decision tree, random forest, etc.) There is a need for the research community to develop novel solutions for these practical issues. Submissions tackling new problems or more than one of the aforementioned topics simultaneously are encouraged. Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018), Oral presentation (acceptance rate: 11.0%), pp. The 35th Conference on Neural Information Processing Systems (NeurIPS 2021), (Acceptance Rate: 26%), accepted. However, research in the AI field also shows that their performance in the wild is far from practical due to the lack of model efficiency and robustness towards open-world data and scenarios. Novel AI-based techniques to improve modeling of engineering systems. Note: This is the inaugural event of a conference dedicated to Graph Machine Learning. Reasons include: (1) a lack of certification of AI for security, (2) a lack of formal study of the implications of practical constraints (e.g., power, memory, storage) for AI systems in the cyber domain, (3) known vulnerabilities such as evasion, poisoning attacks, (4) lack of meaningful explanations for security analysts, and (5) lack of analyst trust in AI solutions. This year the AICS emphasis will be on practical considerations in the real world when deploying AI systems for security with a special focus on convergence of AI and cyber-security in the biomedical field. 9, no. upon methodologies and applications for extracting useful knowledge from data [1]. Interactive Machine Learning (IML) is concerned with the development of algorithms for enabling machines to cooperate with human agents. Online and Distributed Robust Regressions with Extremely Noisy Labels. Xuchao Zhang, Liang Zhao, Zhiqian Chen, and Chang-Tien Lu. Short or position papers of up to 4 pages are also welcome. This workshop aims to bring together FL researchers and practitioners to address the additional security and privacy threats and challenges in FL to make its mass adoption and widespread acceptance in the community. Workshops are one day unless otherwise noted in the individual descriptions. AAAI, specifically, is a great venue for our workshop because its audience spans many ML and AI communities. Liming Zhang, Dieter Pfoser, Liang Zhao. Prof. Max Welling, University of Amsterdam and Microsoft ResearchProf. Authors are strongly encouraged to make data and code publicly available whenever possible. 2022. Estimating the Circuit Deobfuscating Runtime based on Graph Deep Learning. Liang Zhao, Feng Chen, and Yanfang Ye. Hence, AI methods are required to understand and protect the cyber domain. Instead of grading each piece of work individually, which can take up a bulk of extra time, intelligent scoring tools allow teachers the ability to have their students work automatically graded. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc. The AAAI template https://aaai.org/Conferences/AAAI-22/aaai22call/ should be used for all submissions. Liang Zhao, Olga Gkountouna, and Dieter Pfoser. Please note that the KDD Cup workshop will have no proceedings and the authors retain full rights to submit or post the paper at any other venue. Deep learning and statistical methods for data mining. The discussion in the workshop can lead to implementing FL solutions that are more accurate, robust and interpretable, and gain the trust of the FL participants. [materials][data]. The financial services industry relies heavily on AI and Machine Learning solutions across all business functions and services. NOTE: Mandatory abstract deadline on Oct 13, 2022. The workshop will focus on the application of AI to problems in cyber-security. Short or position papers of up to 4 pages are also welcome. November 11-17, 2023. Your Style Your Identity: LeveragingWriting and Photography Styles for Drug Trafficker Identification in Darknet Markets over Attributed Heterogeneous Information Network, The Web Conference (WWW 2019), short paper, (acceptance rate: 20%), accepted, 2019.
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