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. We have the following keynote speakers confirmed: Andreas Holzinger (Medical Univ. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), (Impact Factor: 14.255), accepted. Sathappan Muthiah, Patrick Butler, Rupinder Paul Khandpur, Parang Saraf, Nathan Self, Alla Rozovskaya, Liang Zhao, Jose Cadena et al. The post-lunch session will feature one long talk, two short talks, and a poster session. "Multi-Task Learning for Spatio-Temporal Event Forecasting." This is a one-day workshop, planned with a 10-minute opening, 6 invited keynotes, ~6 contributed talks, 2 poster sessions, and 2 panel discussions. Detailed information could be found on the website of the workshop. Poster session: One poster session of all accepted papers which leads for interaction and personal feedback to the research. We propose a full day workshop with the following sessions: The workshop solicits paper submissions from participants (26 pages). The workshop aims at bridging formalisms for learning and reasoning such as neural and symbolic approaches, probabilistic programming, differentiable programming, Statistical Relation Learning and using non-differentiable optimization in deep models. Spatiotemporal Innovation Center Team. Dazhou Yu, Guangji Bai, Yun Li, and Liang Zhao. OARS-KDD2022: KDD 2022 Workshop on Online and Adaptive Recommender Systems Washington DC, DC, United States, August 15, 2022 Topics: data science artificial intelligence recommender system recommendation KDD 2022 Workshop on Online and Adaptive Recommender Systems (OARS) Call For Papers ================== Submit to:https://openreview.net/group?id=AAAI.org/2022/Workshop/AdvML, Yinpeng Dong (dyp17@mails.tsinghua.edu.cn, 30 Shuangqing Road, Haidian District, Tsinghua University, Beijing, China, 100084, Phone: +86 18603303421), Yinpeng Dong (Tsinghua University, dyp17@mail.tsinghua.edu.cn), Tianyu Pang (Tsinghua University, pty17@mails.tsinghua.edu.cn), Xiao Yang (Tsinghua University, yangxiao19@mails.tsinghua.edu.cn), Eric Wong (MIT, wongeric@mit.edu), Zico Kolter (CMU, zkolter@cs.cmu.edu), Yuan He (Alibaba, heyuan.hy@alibaba-inc.com ). Papers that introduce new theoretical concepts or methods, help to develop a better understanding of new emerging concepts through extensive experiments, or demonstrate a novel application of these methods to a domain are encouraged. Consequently, standard notions of software quality and reliability such as deterministic functional correctness, black box testing, code coverage, and traditional software debugging become practically irrelevant for ML systems. At least one author of each accepted submission must present the paper at the workshop. Shi, Y., Deng, M., Yang, X., Liu, Q., Zhao, L., & Lu, C. T. "A Framework for Discovering Evolving Domain Related Spatio-Temporal Patterns in Twitter." Please submit the papers and system reports toEasyChair, Thien Huu Nguyen (University of Oregon, thien@cs.uoregon.edu), Walter Chang (Adobe Research, wachang@adobe.com), Amir Pouran Ben Veyseh (University of Oregon, apouranb@uoregon.edu), Viet Dac Lai (University of Oregon, viet@uoregon.edu), Franck Dernoncourt (Adobe Research, franck.dernoncourt@adobe.com), Workshop URL:https://sites.google.com/view/sdu-aaai22/home. 10, pp. Benchmarks to reliably evaluate attacks/defenses and measure the real progress of the field. [Best Paper Candidate], Minxing Zhang, Dazhou Yu, Yun Li, Liang Zhao. 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). Zheng Chai, Yujing Chen, Ali Anwar, Liang Zhao, Yue Cheng, Huzefa Rangwala. Check the deadlines for submitting your application. IBM Research, 2018. This workshop aims to bring together researchers from industry and academia and from different disciplines in AI and surrounding areas to explore challenges and innovations in IML. Yuyang Gao and Liang Zhao. AI is now shaping the way businesses, governments, and educational institutions do things and is making its way into classrooms, schools and districts across many countries. Our preliminary plan for the schedule is as following , DEFACTIFY@AAAI-22 Program [tentative]9:00AM-9:15AMInaugurationA brief summary of the shared tasks number of participants, best results, Session 1 multimodal fact checkingWorkshop papers 9:30AM 10:30AM, 11:00AM 12:00pmInvited talk 1 Prof. Rada Mihalcea, University of Michigan, Session 2 Best 4/5 papers from FACTIFY & MEMOTION shared taskWorkshop papers 1:00PM 2:00PM, 2:00PM 3:30PMInvited talk 2 Prof. LOUIS-PHILIPPE MORENCY, CMU, Session 2 multimodal hate speechWorkshop papers 4:00PM 5:00PM. Different from machine learning, Knowledge Discovery and Data Mining (KDD) is Junxiang Wang, Yuyang Gao, Andreas Zufle, Jingyuan Yang, and Liang Zhao. All papers must be submitted in PDF format using the AAAI-22 author kit. We invite researchers to submit either full-length research papers (8 pages) or extended abstracts (2 pages) describing novel contributions and preliminary results, respectively, to the topics above; a more extensive list of topics is available on the Workshop website. RL4ED is intended to facilitate tighter connections between researchers and practitioners interested in the broad areas of reinforcement learning (RL) and education (ED). Adverse event detection by integrating Twitter data and VAERS. The submission website ishttps://easychair.org/conferences/?conf=fl-aaai-22. Such advances would enrich the range of applicability of semi-autonomous systems to real-world tasks, most of which involve cooperation with one or more human partners. "Controllable Data Generation by Deep Learning: A Review." We hope to build upon that success. Maria Malik, Hassan Ghasemzadeh, Tinoosh Mohsenin, Rosario Cammarota, Liang Zhao, Avesta Sasan, Houman Homayoun, Setareh Rafatirad. Papers should be up to 4 pages in length (excluding references) formatted using the AAAI template. The study of complex graphs is a highly interdisciplinary field that aims to study complex systems by using mathematical models, physical laws, inference and learning algorithms, etc. Attendance is open to all; at least one author of each accepted submission must be physically/virtually present at the workshop. The advances in web science and technology for data management, integration, mining, classification, filtering, and visualization has given rise to a variety of applications representing real-time data on epidemics. Apr 11-14, 2022. Please use vds@ieeevis.org to get in touch with us, or follow us on Twitter at @VisualDataSci. "EMBERS at 4 years:Experiences operating an Open Source Indicators Forecasting System." The audience of this workshop will be researchers and students from a wide array of disciplines including, but not limited to, statistics, computer science, economics, public policy, psychology, management, and decision science, who work at the intersection of causal inference, machine learning, and behavior science. 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. The submissions need to be anonymized. arXiv preprint arXiv:2212.03954 (2022). As for the Kraken, they made one trade a month ago to acquire a seventh defenceman, Jaycob Megna and did nothing else (from 'Kraken remain quiet as NHL trade deadline passes,' The Seattle . Submission site:https://easychair.org/conferences/?conf=kdf22, Chair:Xiaomo Liu (J.P. Morgan Chase AI Research, xiaomo.liu@jpmchase.com), Zhiqiang Ma (J.P. Morgan Chase AI Research), Armineh Nourbakhsh (J.P. Morgan Chase AI Research), Sameena Shah (J.P. Morgan Chase AI Research), Gerard de Melo (Hasso Plattner Institute), Le Song (Mohamed bin Zayed University of Artificial Intelligence), Workshop URL:https://aaai-kdf.github.io/kdf2022/. Conference Management Toolkit - Login Zirui Xu, Fuxun Xu, Liang Zhao, and Xiang Chen. For general inquiries about AI2ASE, please write to the lead organizer aryan.deshwal@wsu.edu or jana.doppa@wsu.edu. KDD: Knowledge Discovery and Data Mining 2024 2023 2022 - WikiCFP Call for Papers Document Intelligence Workshop @ KDD 2022 The main goal of the dialog system technology challenge (DSTC) workshop is to share the result of five main tracks of the tenth dialog system technology challenge (DSTC10). Rabat, Morocco . 10, pp. Deep Graph Learning for Circuit Deobfuscation. Wenbin Zhang, Liming Zhang, Dieter Pfoser, Liang Zhao. Integration of logical inference in training deep models. Linear Time Complexity Time Series Clustering with Symbolic Pattern Forest. Attendance is open to all, subject to any room occupancy constraints. [paper] Multi-objective Deep Data Generation with Correlated Property Control. Optimal transport-based machine learning paradigms; Trustworthy machine learning from the perspective of optimal transport. [Best Poster Runner-Up Award]. No supplement is allowed for extended abstracts. Big Data 2022 December 13-16, 2022. These approaches make it possible to use a tremendous amount of unlabeled data available on the web to train large networks and solve complicated tasks. Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, and Chang-TIen Lu. The workshop also welcomes participants of SUPERB and Zero Speech challenge to submit their results. We are excited to continue promoting innovation in self-supervision for the speech/audio processing fields and inspiring the fields to contribute to the general machine learning community. Some specific topics in the context of scientific discovery and engineering design include (but not limited to): This will be a one day workshop with a number of paper presentations and poster spotlights, a poster session, several invited talks, and a panel discussion. Yuanqi Du, Xiaojie Guo, Yinkai Wang, Amarda Shehu, Liang Zhao. These cookies track visitors across websites and collect information to provide customized ads. NOTE: Mandatory abstract deadline on Oct 13, 2022. The submissions must follow the formatting guidelines for AAAI-22. Data science draws from methodology developed in such fields as applied mathematics, statistics, machine learning, data mining, data management, visualization, and HCI. Deep Graph Transformation for Attributed, Directed, and Signed Networks. It highlights the importance of declarative languages that enable such integration for covering multiple formalisms at a high-level and points to the need for building a new generation of ML tools to help domain experts in designing complex models where they can declare their knowledge about the domain and use data-driven learning models based on various underlying formalisms. Multi-instance Domain Adaptation for Vaccine Adverse Event Detection.27th International However, the performance and efficiency of these techniques are big challenges for performing real-time applications. In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2020), (acceptance rate: 16.8%), August 23-27, 2020, Virtual Event, CA, USA. Necessary cookies are absolutely essential for the website to function properly. [Best Paper Award]. 40, no. Short or position papers of up to 4 pages are also welcome. How to Write and Publish Research Papers for the Premier Forums in Knowledge & Data Engineering: Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. Nonetheless, human-centric problems (such as activity recognition, pose estimation, affective computing, BCI, health analytics, and others) rely on information modalities with specific spatiotemporal properties. Yet, most of these efforts highlighted the challenges of model governance and compliance processes. While there have been extensive independent research threads on the subject of safety and reliability of specific sub-problems in autonomy, such as the problem of robust control, as well as recent considerations of robust AI-based perception, there has been considerably less research on investigating robustness and trust in end-to-end autonomy, where AI-based perception is integrated with planning and control in an open loop. This cookie is set by GDPR Cookie Consent plugin. ACM RecSys 2022 will be held in Seattle, USA, from September 18 - 23, 2022. The third AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI-22) builds on the success of previous years PPAI-20 and PPAI-21 to provide a platform for researchers, AI practitioners, and policymakers to discuss technical and societal issues and present solutions related to privacy in AI applications. Despite gratifying achievements that have demonstrated the great potential and bright development prospect of introducing AI in education, developing and applying AI technologies to educational practice is fraught with its unique challenges, including, but not limited to, extreme data sparsity, lack of labeled data, and privacy issues. ACM Transactions on Spatial Algorithms and Systems (TSAS), 5, 3, Article 19 (September 2019), 28 pages. Interpretable Molecular Graph Generation via Monotonic Constraints. Yuyang Gao, Tong Sun, Guangji Bai, Siyi Gu, Sungsoo Hong, and Liang Zhao. Online Flu Epidemiological Deep Modeling on Novel AI-based techniques to improve modeling of engineering systems. and Simone Stumpf (Univ. This topic also encompasses techniques that augment or alter the network as the network is trained. This workshop aims to provide a premier interdisciplinary forum for researchers in different communities to discuss the most recent trends, innovations, applications, and challenges of optimal transport and structured data modeling. This website uses cookies to improve your experience while you navigate through the website. STGEN: Deep Continuous-time Spatiotemporal Graph Generation. Yuyang Gao, Tong Sun, Sungsoo Hong, and Liang Zhao. Table identification and extraction from business documents. Interpreting and Evaluating Neural Network Robustness. Although textual data is prevalent in a large amount of finance-related business problems, we also encourage submissions of studies or applications pertinent to finance using other types of unstructured data such as financial transactions, sensors, mobile devices, satellites, social media, etc. System reports should also follow the AAAI 2022 formatting guidelines and have 4-6 pages including references. We hope this will help bring the communities of data mining and visualization more closely connected. Zero Speech challenge is to build language models only based on audio or audio-visual information, without using any textual input. in the proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), (acceptance rate: 26%), pp. How can we develop solid technical visions and new paradigms about AI Safety? Aryan Deshwal (Washington State University, aryan.deshwal@wsu.edu), Syrine Belakaria (Washington State University, syrine.belakaria@wsu.edu), Cory Simon (Oregon State University, cory.simon@oregonstate.edu), Jana Doppa (Washington State University, jana.doppa@wsu.edu), Yolanda Gil (University of Southern California, gil@isi.edu), Supplemental workshop site:https://ai-2-ase.github.io/. December, 09-12, 2022. Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, and Yanfang Ye. Introduction: SIGKDD aims to provide the premier forum for advancement and adoption of the "science" of knowledge discovery and data mining.SIGKDD will encourage: basic research in KDD (through annual research conferences, newsletter and other related activities . 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. An Invertible Graph Diffusion Model for Source Localization. Submit to:https://cmt3.research.microsoft.com/AIBSD2022, Kuan-Chuan Peng (Mitsubishi Electric Research Laboratories, kp388@cornell.edu), Ziyan Wu (UII America, Inc., wuzy.buaa@gmail.com), Supplemental workshop site:https://aibsdworkshop.github.io/2022/index.html. How to do good research, Get it published in SIGKDD and get it cited! What are the primary lessons learned from the model failures? Outcomes include outlining the main research challenges in this area, potential future directions, and cross-pollination between AI researchers and domain experts in agriculture and food systems. We will accept both original papers up to 8 pages in length (including references) as well as position papers and papers covering work in progress up to 4 pages in length (not including references).Submission will be through Easychair at the AAAI-22 Workshop AI4DO submission site, Professor Bistra Dilkina (dilkina@usc.edu), USC and Dr. Segev Wasserkrug, (segevw@il.ibm.com), IBM Research, Prof. Andrea Lodi (andrea.lodi@cornell.edu), Jacobs Technion-Cornell Institute IIT and Dr. Dharmashankar Subrmanian (dharmash@us.ibm.com), IBM Research. 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). Submissions tackling new problems or more than one of the aforementioned topics simultaneously are encouraged. For papers that rely heavily on empirical evaluations, the experimental methods and results should be clear, well executed, and repeatable. 963-971, Apr-May 2015. Please keep your paper format according to AAAI Formatting Instructions (two-column format). Notable examples include the information bottleneck (IB) approach on the explanation of the generalization behavior of DNNs and the information maximization principle in visual representation learning. Zhiqian Chen, Gaurav Kolhe, Setareh Rafatirad, Chang-Tien Lu, Sai Dinakarrao, Houman Homayoun, Liang Zhao. Papers must be between 4-8 pages with the AAAI submission format submitted to the track of regular paper, SUPERB or Zero Speech result paper. The ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2022 (ACM SIGSPATIAL 2022) (Acceptance Rate: 23.8%), full paper track, to appear, 2022. The submission website ishttps://cmt3.research.microsoft.com/PracticalDL2022. Cleansing and image enhancement techniques for scanned documents. Novel methods to learn from scarce/sparse, or heterogenous, or multimodal data. Published March 4, 2023 4:51 a.m. PST. 2, no. The robust development and assured deployment of AI systems: Participants will discuss how to leverage and update common software development paradigms, e.g., DevSecOps, to incorporate relevant aspects of system-level AI assurance. Continuous refinement of AI models using active/online learning. Paper Submission Deadline: 23:59 on Thursday. Journal of Biomedical Semantics, (impact factor: 1.845), 2018, accepted. RLG is a full-day workshop. "Spatiotemporal Event Forecasting from Incomplete Hyper-local Price Data" The 26th ACM International Conference on Information and Knowledge Management (CIKM 2017) , (acceptance rate: 21%), pp. Submissions may consist of up to 7 pages of technical content plus up to two additional pages solely for references. Transfer learning methods for business document reading and understanding. Social Media based Simulation Models for Understanding Disease Dynamics.