kdd 2022 deadline kdd 2022 deadline

Papers must be between 4-8 pages in the AAAI submission format, with the eighth page containing only references. Spatio-temporal Event Forecasting Using Incremental Multi-source Feature Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), accepted. Finally, the workshop will welcome papers that describe the release of privacy-preserving benchmarks and data sets that can be used by the community to solve fundamental problems of interest, including in machine learning and optimization for health systems and urban networks, to mention but a few examples. Accepted papers will be published in the workshop proceedings. These challenges and issues call for robust artificial intelligence (AI) algorithms and systems to help. Innovation, Service, and Rising Star Awards. Typically, we receive around 40~60 submissions to each previous workshop. Shiyu Wang, Xiaojie Guo, Liang Zhao. PLOS ONE (impact factor: 3.534), vo. The trained models are intended to assign scores to novel utterances, assessing whether they are possible or likely utterances in the training language. The AAAI Workshop on Machine Learning for Operations Research (ML4OR) builds on the momentum that has been directed over the past 5 years, in both the OR and ML communities, towards establishing modern ML methods as a first-class citizen at all levels of the OR toolkit. a concise checklist by Prof. Eamonn Keogh (UC Riverside). Fine tuning a neural network is very time consuming and far from optimal. 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. ADMM for Efficient Deep Learning with Global Convergence. All submissions must be in PDF format and formatted according to the new Standard AAAI Conference Proceedings Template. We allow papers that are concurrently submitted to or currently under review at other conferences or venues. Babies learn their first language through listening, talking, and interacting with adults. Three specific roles are part of this format: session chairs, presenters and paper discussants. Any participant who experiences unacceptable behavior may contact any current member of the SIGMOD Executive Committee, the PODS Executive Committee, DBCares, or this year's D&I co-chairs Pnar Tzn (pito@itu.dk) and Renata Borovica-Gajic (renata.borovica@unimelb.edu.au). Liang Zhao, Olga Gkountouna, and Dieter Pfoser. robust and interpretable natural language processing for healthcare. Can AI achieve the same goal without much low-level supervision? Optimal transport-based analysis of structured data, such as networks, meshes, sequences, and so on; The applications of optimal transport in molecule analysis, network analysis, natural language processing, computer vision, and bioinformatics. and Simone Stumpf (Univ. We hope this will help bring the communities of data mining and visualization more closely connected. Submissions of technical papers can be up to 7 pages excluding references and appendices. Algorithms for secure and privacy-aware machine learning for AI. Additional information about formatting and style files is available here: : Full papers are limited to a total of 6 pages, including all content and references. Xiaojie Guo, Yuanqi Du, Liang Zhao. This workshop has no archival proceedings. These datasets can be leveraged to learn individuals behavioral patterns, identify individuals at risk of making sub-optimal or harmful choices, and target them with behavioral interventions to prevent harm or improve well-being. Previously published work (or under-review) is acceptable. 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/. The AAAI author kit can be downloaded from:https://www.aaai.org/Publications/Templates/AuthorKit22.zip. Topics of interest include but are not limited to: Acronyms, i.e., short forms of long phrases, are common in scientific writing. Winter. Poster session: One poster session of all accepted papers which leads for interaction and personal feedback to the research. Xuchao Zhang, Shuo Lei, Liang Zhao, Arnold Boedihardjo, Chang-Tien Lu, "Robust Regression via Heuristic Corruption Thresholding and Its Adaptive Estimation Variation", ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 1.98), accepted, 2019. Despite rapid recent progress, it has proven to be challenging for Artificial Intelligence (AI) algorithms to be integrated into real-world applications such as autonomous vehicles, industrial robotics, and healthcare. The workshop invites contribution to novel methods, innovations, applications, and broader implications of SSL for processing human-related data, including (but not limited to): In addition to the above, papers that consider the following are also invited: Manuscripts that fit only certain aspects of the workshop are also invited. . 10, pp. The impact of robustness assurance on other AI ethics principles: RAISA will also explore aspects related to ethical AI that overlap and interact with robustness concerns, including security, fairness, privacy, and explainability. SDU will also host a session for presenting the short research papers and the system reports of the shared tasks. In recent years, we have seen examples of general approaches that learn to play these games via self-play reinforcement learning (RL), as first demonstrated in Backgammon. Novel AI-enabled generative models for system design and manufacturing. In recent months/years, major global shifts have occurred across the globe triggered by the Covid pandemic. The main objective of the workshop is to bring researchers together to discuss ideas, preliminary results, and ongoing research in the field of reinforcement in games. 105, no. Apr 25th through Fri the 29th, 2022. . Dialog systems and related technologies, including natural language processing, audio and speech processing, and vision information processing. Attendance is expected to be 150-200 participants (estimated), including organizers and speakers. Characterization of fundamental limits of causal quantities using information theory. ACM, 2014. This cookie is set by GDPR Cookie Consent plugin. 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 invite paper submission on the following (and related) topics: The workshop will be a 1 day meeting comprising several invited talks from distinguished researchers in the field, spotlight lightning talks and a poster session where contributing paper presenters can discuss their work, and a concluding panel discussion focusing on future directions. The accelerated developments in the field of Artificial Intelligence (AI) hint at the need for considering Safety as a design principle rather than an option. After seventh highly successful events, the eighth Symposium on Visualization in Data Science (VDS) will be held at a new venue, ACM KDD 2022 as well as IEEE VIS 2022. Please email to Lingfei Wu: lwu@email.wm.edu for any query. 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. The reproducibility papers include a clarification phase: Deadlines refer to 23:59 (11:59pm) in the AoE (Anywhere on Earth) time zone. Submissions will be collected via the OpenReview platform; URL forthcoming on the Workshop website. Moreover, to tackle and overcome several issues in personalized healthcare, information technology will need to evolve to improve communication, collaboration, and teamwork among patients, their families, healthcare communities, and care teams involving practitioners from different fields and specialties. The extraction, representation, and sharing of health data, patient preference elicitation, personalization of generic therapy plans, adaptation to care environments and available health expertise, and making medical information accessible to patients are some of the relevant problems in need of AI-based solutions. 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. There is now a great deal of interest in finding better alternatives to this scheme. Deep Graph Learning for Circuit Deobfuscation. Xiaojie Guo, Liang Zhao, Cameron Nowzari, Setareh Rafatirad, Houman Homayoun, and Sai Dinakarrao. Recent years have witnessed growing efforts from the AI research community devoted to advancing our education and promising results have been obtained in solving various critical problems in education. chess, checkers). 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. ML-guided rare event modeling and system uncertainty quantification, Development of software, libraries, or benchmark datasets, and. 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). Algorithms and theories for trustworthy AI models. It is one of the key bottlenecks for financial services companies to improve their operating productivity. Thirty-First AAAI Conference on Artificial Intelligence, pp. The submission website ishttps://cmt3.research.microsoft.com/TAIH2022. Incomplete Label Multi-Task Ordinal Regression for Spatial Event Scale Forecasting. 1-39, November 2016. Microsoft Research CMT: https://cmt3.research.microsoft.com/DI2022, https://document-intelligence.github.io/DI-2022/ or https://aka.ms/di-2022, Workshop registration will be processed with the main KDD 2022 conference: https://kdd.org/kdd2022/, Standard ACM Conference Proceedings Template, Conflict of Interest Policy for ACM Publications, https://cmt3.research.microsoft.com/DI2022, https://document-intelligence.github.io/DI-2022/, Second Document Intelligence Workshop @ KDD 2021, First Document Intelligence Workshop @ NeurIPS 2019, Hamid Motahari, Nigel Duffy, Paul Bennett, and Tania Bedrax-Weiss. Deadline in . The accepted papers will be posted on the workshop website and will not appear in the AAAI proceedings. Trade-Off between Privacy-Preserving and Explainable Federated Learning Federated Learning Multi-Party Computation, Federated Learning Homomorphic Encryption, Federated Learning Personalization Techniques, Federated Learning Meets Mean-Field Game Theory, Federated Learning-based Corporate Social Responsibility. Liang Zhao, Junxiang Wang, and Xiaojie Guo. Autonomous vehicles can share their detected information (e.g., traffic signs, collision events, etc.) However, these real-world applications typically translate to problem domains where it is extremely challenging to even obtain raw data, let alone annotated data. The availability of massive amounts of data, coupled with high-performance cloud computing platforms, has driven significant progress in artificial intelligence and, in particular, machine learning and optimization. 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. Adverse event detection by integrating Twitter data and VAERS. P. 6205, succursale Centre-villeMontral, (Qubec) H3C 3T5Canada. "Online Spatial Event Forecasting in Microblogs. 1799-1808. In Proceedings of the 20th International Conference on Data Mining (ICDM 2020), (acceptance rate: 9.8%), November 17-20, 2020, Virtual Event, Sorrento, Italy, 10 pages. Hence, there is a need for research and practical solutions to ML security problems.With these in mind, this workshop solicits original contributions addressing problems and solutions related to dependability, quality assurance and security of ML systems. Jinliang Ding, Liang Zhao, Changxin Liu, and Tianyou Chai. Aug 11, 2022: Get early access for registration at L Street Bridge, Washington DC Convention Center, from 4-6 pm, Saturday, August 13. Adversarial attacking deep learning systems, Robust architectures against adversarial attacks, Hardware implementation and on-device deployment, Benchmark for evaluating model robustness, New methodologies and architectures for efficient and robust deep learning, December 3, 2021 Acceptance Notification, Applications of privacy-preserving AI systems, Differential privacy: theory and applications, Distributed privacy-preserving algorithms, Privacy preserving optimization and machine learning, Privacy preserving test cases and benchmarks. Registration Opens: Feb 02 '22 02:00 PM UTC: Registration Cancellation Refund Deadline: Apr 18 '22(Anywhere on Earth) Paper Submissions Abstract Submission Deadline: Sep 29 '21 12:00 AM UTC: Paper Submission deadline: Oct 06 '21 12:00 AM . In addition, several invited speakers with distinguished professional background will give talks related the frontier topics of GNN. If the admission deadline for international applicants is past, we suggest that you choose another session to begin your studies. December, 12-16, 2022. Submission Guidelines The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. Design, Automation and Test in Europe Conference (DATE 2020), long paper, (acceptance rate: 26%), accepted. information bottleneck principle). This workshop aims to bring together researchers from AI and diverse science/engineering communities to achieve the following goals: 1) Identify and understand the challenges in applying AI to specific science and engineering problems2) Develop, adapt, and refine AI tools for novel problem settings and challenges3) Community-building and education to encourage collaboration between AI researchers and domain area experts. Taseef Rahman, Yuanqi Du, Liang Zhao, Amarda Shehu. Yuyang Gao, Liang Zhao, Lingfei Wu, Yanfang Ye, Hui Xiong, Chaowei Yang. URL: https://sites.google.com/view/kdd22onlinemarketplaces Call For Papers (Submission deadline: June3, 2022) We will use double-blind reviewing. 2022. Online marketplaces exist in a diverse set of domains and industries, for example, rideshare (Lyft, DiDi, Uber), house rental (Airbnb), real estate (Beke), online retail (Amazon, Ebay), job search (LinkedIn, Indeed.com, CareerBuilder), and food ordering and delivery (Doordash, Meituan). The paper submissions must be in pdf format and use the AAAI official templates. Liang Zhao, Ting Hua, Chang-Tien Lu, and Ing-Ray Chen. Participants are welcomed to submit their system reports to be presented in the workshop. The workshop is organized by paper presentations.The length of the workshop: 1-day, 6-8 pages for full papers2-4 for poster/short/position papers, Submission URL:https://easychair.org/conferences/?conf=aaai-2022-workshop, Wenzhong Guo (Fuzhou University, fzugwz@163.com), Chin-Chen Chang (Feng Chia University, alan3c@gmail.com), Chi-Hua Chen (Fuzhou University, chihua0826@gmail.com), Haishuai Wang (Fairfield University & Harvard University, hwang@fairfield.edu), Feng-Jang Hwang (University of Technology Sydney), Cheng Shi (Xian University of Technology), Ching-Chun Chang (National Institute of Informatics, Japan). We will also select some of the best posters for spotlight talks (2 minutes each). "Pyramid: Machine Learning Framework to Estimate the Optimal Timing and Resource Usage of a High-Level Synthesis Design", 28th International Conference on Field Programmable Logic and Applications (FPL 2019), (acceptance rate: 18%), Barcelona, Spain, accepted. Identification of information-theoretic quantities relevant for causal inference and discovery. Deadline: FSE 2023. KDD 2022. To facilitate KDD related research, we create this repository with: *ICDM has two tracks (regular paper track and short paper track), but the exact statistic is not released, e.g., the split between these two tracks. Lingfei Wu, Ian En-Hsu Yen, Siyu Huo, Liang Zhao, Kun Xu, Liang Ma, Shouling Ji and Charu Aggarwal. Interesting challenges in this domain include the drastic increase of work from home or remote work, the imbalance between the demand and supply of the job market, the popularity of independent workers, the capability of helping job seekers on their whole job seeking journey and career development, the different objectives and behaviors of all major stakeholders in the ecosystem, e.g. The format is the standard double-column AAAI Proceedings Style. In this 2nd instance of GCLR (Graphs and more Complex structures for Learning and Reasoning) workshop, we will focus on various complex structures along with inference and learning algorithms for these structures. In some programs, spots may be available after the deadlines. What is the status of existing approaches in ensuring AI and Machine Learning (ML) safety, and what are the gaps? 2020. World Wide Web Conference (WWW 2018), (acceptance rate: 14.8%), Lyon, FR, Apr 2018, accepted. We will receive the paper on the CMT system. 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. Accepted papers will not be archived, and we explicitly allow papers that are concurrently submitted to, currently under review at, or recently accepted in other conferences / venues. The workshop will be a one-day meeting and will include a number of technical sessions, a virtual poster session where presenters can discuss their work, with the aim of further fostering collaborations, multiple invited speakers covering crucial challenges for the field of privacy-preserving AI applications, including policy and societal impacts, a tutorial talk, and will conclude with a panel discussion. Integration of Deep Learning and Relational Learning. The design and implementation of these AI techniques to meet financial business operations require a joint effort between academia researchers and industry practitioners. You may file an application just the same, but Universit de Montral cannot guarantee that it will respond quickly enough for you to be able to complete all the formalities required to study in Quebec. Ranking, acceptance rate, deadline, and publication tips. "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. However, you may visit "Cookie Settings" to provide a controlled consent. 8 pages), short (max. Papers must be in PDF format, in English, and formatted according to the AAAI template. Integration of declarative and procedural domain knowledge in learning. Check the deadlines for submitting your application. First, large data sources, both conventionally used in social sciences (EHRs, health claims, credit card use, college attendance records) and unconventional (social networks, fitness apps), are now available, and are increasingly used to personalize interventions. Deep learning has achieved significant success for artificial intelligence (AI) in multiple fields. Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), (Acceptance Rate: 15%), accepted. Checklist for Revising a SIGKDD Data Mining Paper: Deadline: Fri Jun 09 2023 04:59:00 GMT-0700 Yahoo! Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment. Deep Graph Transformation for Attributed, Directed, and Signed Networks. Transformations in many fields are enabled by rapid advances in our ability to acquire and generate data. We accept two types of submissions full research paper no longer than 8 pages (including references) and short/poster paper with 2-4 pages. CPM: A General Feature Dependency Pattern Mining Framework for Contrast Multivariate Time Series. 47, no. Options include pruning a trained network or training many networks automatically. We will end the workshop with a panel discussion by top researchers in the field. "Automatic Targeted-Domain Spatiotemporal Event Detection in Twitter." To provide proper alerts and timely response, public health officials and researchers systematically gather news and other reports about suspected disease outbreaks, bioterrorism, and other events of potential international public health concern, from a wide range of formal and informal sources. Data Mining and Knowledge Discovery (DMKD), (impact factor: 3.670), accepted. Deep Classifier Cascades for Open World Recognition. Mining from heterogeneous data sources, including text, semi-structured, spatio-temporal, streaming, graph, web, and multimedia data. A Systematic Survey on Deep Generative Models for Graph Generation. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), (Impact Factor: 14.255), accepted. Manuscripts must be submitted as PDF files viaEasyChair online submission system. Submissions tackling new problems or more than one of the aforementioned topics simultaneously are encouraged. This AAAI-22 workshop on AI for Decision Optimization (AI4DO) will explore how AI can be used to significantly simplify the creation of efficient production level optimization models, thereby enabling their much wider application and resulting business values.The desired outcome of this workshop is to drive forward research and seed collaborations in this area by bringing together machine learning and decision-making from the lens of both dynamic and static optimization models. To view them in conference website timezones, click on them. 17th International Workshop on Mining and Learning with Graphs. Are you sure you want to create this branch? Sathappan Muthiah, Patrick Butler, Rupinder Paul Khandpur, Parang Saraf, Nathan Self, Alla Rozovskaya, Liang Zhao, Jose Cadena et al. All extended abstracts and full papers are to be presented at the poster sessions. LOG 2022 LOG '22 . 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. In this workshop, we want to explore ways to bridge short-term with long-term issues, idealistic with pragmatic solutions, operational with policy issues, and industry with academia, to build, evaluate, deploy, operate and maintain AI-based systems that are demonstrably safe. Mitigating Cache-Based Side-Channel Attacks through Randomization: A Comprehensive System and Architecture Level Analysis. in Proceedings of the IEEE International Conference on Data Mining (ICDM 2015), regular paper (acceptance rate: 8.4%), Atlantic City, NJ, pp. Knowledge representation for business documents. The challenge requires participants to build competitive models for diverse downstream tasks with limited labeled data and trainable parameters, by reusing self-supervised pre-trained networks. Novel ML methods in the computational material and physical sciences. 2085-2094, Aug 2016. Rupinder Khandpur, Taoran Ji, Yue Ning, Liang Zhao, Chang-Tien Lu, Erik Smith, Christopher Adams and Naren Ramakrishnan. We expect 50~75 participants and potentially more according to our past experiences. Yuanqi Du*, Shiyu Wang* (co-first author), Xiaojie Guo, Hengning Cao, Shujie Hu, Junji Jiang, Aishwarya Varala, Abhinav Angirekula, Liang Zhao.