kdd 2022 deadline23 Apr kdd 2022 deadline
"Online and Distributed Robust Regressions under Adversarial Data Corruption", in Proceedings of the IEEE International Conference on Data Mining (ICDM 2017) , regular paper; (acceptance rate: 9.25%), pp. RAISAs systems-level perspective will be emphasized via three main thrusts: AI threat modeling, AI system robustness, explainable AI, system lifecycle attacks, system verification and validation, robustness benchmarks and standards, robustness to black-box and white-box adversarial attacks, defenses against training, operational and inversion attacks, AI system confidentiality, integrity, and availability, AI system fairness and bias. In other words, many existing FL solutions are still exposed to various security and privacy threats. As Artificial Intelligence (AI) begins to impact our everyday lives, industry, government, and society with tangible consequences, it becomes increasingly important for a user to understand the reasons and models underlying an AI-enabled systems decisions and recommendations. ", ACM Transactions on Spatial Algorithms and Systems (TSAS), (Acceptance Rate: 11%), Volume 2 Issue 4, Acticle No. Information-theoretic approaches provide a novel set of tools that can expand the scope of classical approaches to causal inference and discovery problems in a variety of applications. The accepted papers will be posted on the workshop website and will not appear in the AAAI proceedings. A fundamental problem in the use of artificial neural networks is that the first step is to guess the network architecture. Apr 25th through Fri the 29th, 2022. . The 11th International Conference on Learning Representations (ICLR 2023), accepted. Encore track papers that have been recently published, or accepted for publication in a conference or journal. An Invertible Graph Diffusion Model for Source Localization. Dr. Emotion: Disentangled Representation Learning for Emotion Analysis on Social Media to Improve Community Resilience in the COVID-19 Era and Beyond. A 2-day workshop to share knowledge and research on five tracks of DSTC-10 and general related technical track. "Bridging the gap between spatial and spectral domains: A survey on graph neural networks." What safety engineering considerations are required to develop safe human-machine interaction? 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. [materials][data]. 9, no. Submissions will go through a double-blind review process. The ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2022 (ACM SIGSPATIAL 2022), poster track, to appear, 2022. SIGKDD Explorations, Vol. 27, 2022: Please check out Speical Days at, Apr. Identification of key challenges and opportunities for future research. This workshop will follow a dual-track format. [paper] This workshop covers (but not limited to) the following topics: , It is a one day workshop and includes: invited talks, interactive discussions, paper presentations, shared task presentations, poster session etc. 2022. Submission site:https://cmt3.research.microsoft.com/AAAI2022HCSSL/Submission/Index, Ali Etemad (Queens University, ali.etemad@queensu.ca), Ali Etemad (Queens University, ali.etemad@queensu.ca), Ahmad Beirami (Facebook AI, ahmad.beirami@gmail.com), Akane Sano (Rice University, akane.sano@rice.edu), Aaqib Saeed (Philips Research & University of Cambridge, aqibsaeed@protonmail.com), Alireza Sepas-Moghaddam (Socure, alireza.sepasm@socure.com), Mathilde Caron (Inria & Facebook AI, mathilde@fb.com), Pritam Sarkar (Queens University & Vector Institute, pritam.sarkar@queensu.ca), Huiyuan Yang (Rice University, hy48@rice.edu), Supplemental website:https://hcssl.github.io/AAAI-22/. In addition, broad deployment of ML software in networked systems inevitably exposes ML software to attacks. We expect 50-65 people in the workshop. Welcome to the home of the 2023 ACM SIGMOD/PODS Conference, to be held in the Seattle metropolitan area, Washington, USA, on June 18 - June 23, 2023. 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. The submission website ishttps://cmt3.research.microsoft.com/OTSDM2022. Papers more suited for a poster, rather than a presentation, would be invited for a poster session. and deep learning techniques (e.g. We encourage authors to contact the organizers to discuss possible overlap. Call for Participation The 3rd KDD Workshop on Data-driven Humanitarian Mapping and Policymaking solicits research papers, case studies, vision papers, software demos, and extended abstracts. 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. Participation of researchers from a wide variety of areas is encouraged, including Data Science, Machine Learning, Symbolic AI, Mathematical programming, Constraint Optimization, Reinforcement Learning, Dynamic control and Operations Research. The KDD 2022 program promises to be the most robust and diverse to date, with keynote presentations, industry-led sessions, workshops, and tutorials spanning a wide range of topics - from data-driven humanitarian mapping and applied data science in healthcare to the uses of artificial intelligence (AI) for climate mitigation and decision . simulation, evaluation and experimentation. 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. KDD 2022 -ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. At least one author of each accepted submission must be present at the workshop. 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. Representation Learning on Spatial Networks. These abrupt changes impacted the environmental assumptions used by AI/ML systems and their corresponding input data patterns. Necessary cookies are absolutely essential for the website to function properly. The reproducibility papers include a clarification phase: Deadlines refer to 23:59 (11:59pm) in the AoE (Anywhere on Earth) time zone. Why did so many AI/ML models fail during the pandemic? 205-214, San Francisco, California, Aug 2016. In Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD 2014), industrial track, pp. 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). Pourya Hoseinip, Liang Zhao, and Amarda Shehu. The deep learning community must often confront serious time and hardware constraints from suboptimal architectural decisions. By the end of this century, the earths population is projected to increase by 45% with available arable land decreasing by 20% coupled with changes in what crops these arable lands can best support; this creates the urgent need to enhance agricultural productivity by 70% before 2050. Rabat, Morocco . Everyone in the Top-10 leaderboard submissions will have a guaranteed opportunity for an in-person oral/poster presentation. Note: Mandatory abstract deadline on May 16, 2022 Deadline: ISMIR 2022 ISMIR '22 ​ . ISBN: 978-981-16-6053-5. 2022. Integration of probabilistic inference in training deep models. Self-supervised learning approaches involving the interaction of speech/audio and other modalities. 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. Submit to: Papers are required to submit to:https://easychair.org/conferences/?conf=dlg22. The review process will be single blind. Innovation, Service, and Rising Star Awards. Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. 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/. Knowledge and Information Systems (KAIS), (Impact Factor: 2.531), to appear, 2022. Junxiang Wang and Liang Zhao. Interpretable Molecular Graph Generation via Monotonic Constraints. 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). 2022. While we are planning an in-person workshop to be held at AAAI-22, we aim to accommodate attendees who may not be able to travel to Vancouver by allowing participation via live virtual invited talks and virtual poster sessions. Please refer and submit through theLearning Network Architecture During Trainingworkshop website, which has more detailed information. By entering your email, you consent to receive communications from UdeM. FedAT: A High-Performance and Communication-Efficient Federated Learning System with Asynchronous Tiers. We expect ~60 attendees. Full (8 pages) and short (4 pages, work in progress) papers, AAAI style. "Controllable Data Generation by Deep Learning: A Review." Extended abstracts should not exceed 2 pages, excluding references. What AI safety considerations and experiences are relevant from industry? Both the research papers track and the applied data science papers track will take . These research trends inform the need to explore the intersection of AI with behavioral science and causal inference, and how they can come together for applications in the social and health sciences. VDS@KDD will be hybrid and VDS@VIS will be hybrid (both virtual and in-person) in 2022. The aim of this workshop is to focus on both original research and review articles on various disciplines of ITS applications, including particularly AI techniques for ITS time-series data analyses, ITS spatio-temporal data analyses, advanced traffic management systems, advanced traveler information systems, commercial vehicle operation systems, advanced vehicle control and safety systems, advanced public transportation services, advanced information management services, etc. 2022. Guangji Bai, Johnny Torres, Junxiang Wang, Liang Zhao, Carmen Vaca, Cristina Abad. "STED: semi-supervised targeted-interest event detectionin in twitter." Algorithms and theories for learning AI models under bias and scarcity. Merge remote-tracking branch 'origin/master', 2. While a variety of research has advanced the fundamentals of document understanding, the majority have focused on documents found on the web which fail to capture the complexity of analysis and types of understanding needed across business documents. CPM: A General Feature Dependency Pattern Mining Framework for Contrast Multivariate Time Series. There will be live Q&A sessions at the end of each talk and oral presentation. "Forecasting Significant Societal Events Using The Embers Streaming Predictive Analytics System." KDD 2022. ), Programs also suitable for students not fluent in French, Information and Communication Technologies, Graduate (master's, specialized graduate diploma (DESS), microprogram): February 1, Graduate (master's, specialized graduate diploma (DESS), microprogram): September 1. in the proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), (acceptance rate: 26%), pp. At the AAAI-22 Workshop on Scientific Document Understanding (SDU@AAAI-22), we aim to gather insights into the recent advances and remaining challenges on scientific document understanding. 20, 2022: We have announced Call for Nominations: , Jan. 25, 2022: Sponsorship Opportunities is available at, Jan. 6, 2022: Call for KDD Cup Proposals is available at, Dec. 26, 2021: Call for Workshop Proposals is available at, Dec. 26, 2021: Call for Tutorials is available at, Nov. 24, 2021: Those who are interested in serving as a PC, please feel free to fill in this, Nov. 12, 2021: Call for Research Track Papers is available at, Nov. 12, 2021: Call for Applied Data Science Track Papers is available at. If you are interested, please send a short email to rl4edorg@gmail.com and we can add you to the invitee list. The main interest of the proposed workshop is to look at a new perspective of system engineering where multiple disciplines such as AI and safety engineering are viewed as a larger whole, while considering ethical and legal issues, in order to build trustable intelligent autonomy. Novel approaches and works in progress are encouraged. Through invited talks and presentations by the participants, this workshop will bring together current advances in Network Science as well as Machine Learning, and set the stage for continuing interdisciplinary research discussions. KDD 2022 KDD . The submission website ishttps://cmt3.research.microsoft.com/PracticalDL2022. We solicit papers describing significant and innovative research and applications to the field of job marketplaces. 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. 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. search, ranking, recommendation, and personalization. While progress has been impressive, we believe we have just scratched the surface of what is capable, and much work remains to be done in order to truly understand the algorithms and learning processes within these environments. At least one author of each accepted submission must be present at the workshop. VDS will bring together domain scientists and methods researchers (including data mining, visualization, usability and HCI, data management, statistics, machine learning, and software engineering) to discuss common interests, talk about practical issues, and identify open research problems in visualization in data science. December 2020, July 21: Clarified that the workshop this year will be held, June 20: Paper notification is now extended to, Paper reviews are underway! [Best Paper Award]. Participants are welcomed to submit their system reports to be presented in the workshop. job seekers, employers, recruiters and job agents. Accepted papers will be published in the workshop proceedings. Jan 13, 2022: Notification. Short or position papers of up to 4 pages are also welcome. However, theoreticians and practitioners of AI and Safety are confronted with different levels of safety, different ethical standards and values, and different degrees of liability, that force them to examine a multitude of trade-offs and alternative solutions. Alan Yuille (Professor, Johns Hopkins University); Hao Su (Assistant Professor, UC San Diego); Rongrong Ji (Professor, Xiamen University); Xianglong Liu (Professor, Beihang University); Jishen Zhao (Associate Professor, UC San Diego); Tom Goldstein (Associate Professor, University of Maryland); Cihang Xie (Assistant Professor, UC Santa Cruz); Yisen Wang (Assistant Professor, Peking University); Bohan Zhuang (Assistant Professor, Monash University), Haotong Qin (Beihang University), Yingwei Li (Johns Hopkins University), Ruihao Gong (SenseTime Research), Xinyun Chen (UC Berkeley), Aishan Liu (Beihang University), Xin Dong (Harvard University), Jindong Guo (University of Munich), Yuhang Li (Yale University), Yiming Li (Tsinghua University), Yifu Ding (Beihang University), Mingyuan Zhang (Nanyang Technological University), Jiakai Wang (Beihang University), Jinyang Guo (University of Sydney), Renshuai Tao (Beihang University), Workshop site:https://practical-dl.github.io/. Are you sure you want to create this branch? Handwritten recognition in business documents. Application-specific designs for explainable AI, e.g., healthcare, autonomous driving, etc. 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. All papers must be submitted in PDF format, using the AAAI-21 author kit and anonymized. This date takes priority over those shown below and could be extended for some programs. Use Compass, the interactive checklist designed exclusively for the Universit de Montral, to carefully prepare your application and to avoid common pitfalls along the way. These challenges are widely studied in enterprise networks, but there are many gaps in research and practice as well as novel problems in other domains. While most work on XAI has focused on opaque learned models, this workshop also highlights the need for interactive AI-enabled agents to explain their decisions and models. Qingzhe Li, Jessica Lin, Liang Zhao and Huzefa Rangwala. Papers can be submitted here as an extended abstract (4 pages limit excluding references) or a short paper (6 pages limit excluding references). Data mining systems and platforms, and their efficiency, scalability, security and privacy. Kyoto . Send this CFP to us by mail: cfp@ourglocal.org. We invite a long research paper (8 pages) and a demo paper (4 pages) (including references). Positive applications of adversarial ML, i.e., adversarial for good. chess, checkers). All papers must be submitted in PDF format, using the AAAI-22 author kit. However, the performance and efficiency of these techniques are big challenges for performing real-time applications. All the submissions should be anonymous. sup-port vector machine (SVM), decision tree, random forest, etc.) The workshop will be co-located with the KDD 2022 conference at Washington DC Convention Center,Washington D.C., USA onAugust 17th, 2022 at1PM5PM (Eastern Standard Time).
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