Each paper will be reviewed by three reviewers in double-blind. We are interested in a broad range of topics, both foundational and applied. This topic also encompasses techniques that augment or alter the network as the network is trained. Naren Ramakrishnan, Patrick Butler, Sathappan Muthiah, Nathan Self, Rupinder Khandpur, Parang Saraf, Wei Wang, Jose Cadena, Anil Vullikanti, Gizem Korkmaz, Chris Kuhlman, Achla Marathe, Liang Zhao, Ting Hua, Feng Chen, et al.. "'Beating the news' with EMBERS:forecasting civil unrest using open source indicators." Novel AI-enabled generative models for system design and manufacturing. "A Topic-focused Trust Model for Twitter." The eligibility criteria for attending the workshop will be registration in the conference/workshop as per AAAI norms. 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. Papers more suited for a poster, rather than a presentation, would be invited for a poster session. All deadlines are at 11:59 PM anytime in the world. Zirui Xu, Fuxun Xu, Liang Zhao, and Xiang Chen. Continuous refinement of AI models using active/online learning. Xiaojie Guo, Yuanqi Du, Liang Zhao. Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors. 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. This workshop aims to bring together researchers and practitioners working on different facets of these problems, from diverse backgrounds to share challenges, new directions, recent research results, and lessons from applications. Mining from heterogeneous data sources, including text, semi-structured, spatio-temporal, streaming, graph, web, and multimedia data. [Best Paper Award]. NOTE: Mandatory abstract deadline on Oct 13, 2022. Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. However, workshop organizers may set up any archived publication mechanism that best suits their workshop. Liang Zhao, Jiangzhuo Chen, Feng Chen, Fang Jin, Wei Wang, Chang-Tien Lu, and Naren Ramakrishnan. Long papers (up to 6 pages + references) and extended abstracts (2 pages + references) are welcome, including resubmissions of already accepted papers, work-in-progress, and position papers. At least three research trends are informing insights in this field. to protect data owner privacy in FL. Extracting knowledge or insights from this abundance of data lies at the heart of 21st century discovery, which can be used to inform decisions, coordinate activities, optimize processes, improve products and services, as well as enhance productivity and innovation across a wide range of business and scientific problems. Options include pruning a trained network or training many networks automatically. An increasing world population, coupled with finite arable land, changing diets, and the growing expense of agricultural inputs, is poised to stretch our agricultural systems to their limits. Liang Zhao, Ting Hua, Chang-Tien Lu, and Ing-Ray Chen. November 11-17, 2023. arXiv preprint arXiv:2302.02093 (2023). 17th International Workshop on Mining and Learning with Graphs. Robust Regression via Online Feature Selection under Adversarial Data Corruption. Make sure your desired study programs are open for admission in the session when you would like to start your studies. 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. The submission website ishttps://cmt3.research.microsoft.com/PracticalDL2022. This calls for novel methods and new methodologies and tools to address quality and reliability challenges of ML systems. AI for infrastructure management and congestion. The objective of this workshop is to discuss the winning submissions of the Submissions to the Amazon KDD Cup 2022 issingle-blind (author names and affiliations should be listed). In nearly all applications, reliability, safety, and security of such systems is a critical consideration. At least one author of each accepted submission must be present at the workshop. Junxiang Wang, Junji Jiang, Liang Zhao. IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), vol. 27, 2022: Please check out Speical Days at, Apr. Question answering on business documents. ACM, 2014. Generative Adversarial Learning of Protein Tertiary Structures. Full papers are allocated 20m presentation and 10m discussion. The deadline for the submissions is July 31st, 2022 11.59 PM (Anywhere on Earth time). Modern surveillance systems employ tools and techniques from artificial intelligence and machine learning to monitor direct and indirect signals and indicators of disease activities for early, automatic detection of emerging outbreaks and other health-relevant patterns. Oct 14, 2021: Abstract Deadline. a concise checklist by Prof. Eamonn Keogh (UC Riverside). 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. KDD 2022. FedAT: A High-Performance and Communication-Efficient Federated Learning System with Asynchronous Tiers. 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. There is a need for the research community to develop novel solutions for these practical issues. Examples of the datasets which may be considered are the DBTex Radiology Mammogram dataset and the Johns Hopkins COVID-19 case reports. Specific topics of interest for the workshop include (but are not limited to) foundational and translational AI activities related to: The workshop will be a one day meeting comprising invited talks from researchers in the field, spotlight lightning talks and a poster session where contributing paper presenters can discuss their work. 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. Deadline in your local America/New_York timezone: Deadline in timezone from conference website: DASFAA 2022. To adapt SSL frameworks to build effective human-centric deep learning solutions for human-centric data, a number of key challenges and opportunities need to be explored. CVPR 11 deadline . These models can also generate instant feedback to instructors and help them to improve their teaching effectiveness. Causal inference is one of the main areas of focus in artificial intelligence (AI) and machine learning (ML) communities. KDD is the premier Data Science conference. SDU will be a one-day workshop. Online . Ferdinando Fioretto (Syracuse University), Emma Frejinger (Universit de Montral), Elias B. Khalil (University of Toronto), Pashootan Vaezipoor (University of Toronto). In addition, authors can provide an optional two (2) page supplement at the end of their submitted paper (it needs to be in the same PDF file) focused on reproducibility. The accepted papers will be allocated either a contributed talk or a poster presentation. 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. 2022. References will not count towards the page limit. 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. Mitigating Cache-Based Side-Channel Attacks through Randomization: A Comprehensive System and Architecture Level Analysis. Participants will be given access to publicly available datasets and will be asked to use tools from AI and ML to generate insight from the data. 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. We will include a panel discussion to close the workshop, in which the audience can ask follow up questions and to identify the key AI challenges to push the frontiers in Chemistry. "How events unfold: spatiotemporal mining in social media." In the financial services industry particularly, a large amount of financial analysts work requires knowledge discovery and extraction from different data sources, such as SEC filings and industry reports, etc., before they can conduct any analysis. Molecules, (impact factor: 4.411), accepted. GeoInformatica (impact factor: 2.392), 24, 443475 (2020). IEEE Transactions on Information Forensics and Security (TIFS), (impact factor: 7.178), accepted. Knowledge and Information Systems (KAIS), (Impact Factor: 2.531), to appear, 2022. 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. We welcome attendance from individuals who do not have something theyd like to submit but who are interested in RL4ED research. This half day workshop will focus on research into the use of AI techniques to extract knowledge from unstructured data in financial services. Submit to: Submissions should be made via EasyChair athttps://easychair.org/conferences/?conf=it4dl, Jose C. Principe (University of Florida, principe@cnel.ufl.edu), Robert Jenssen (UiT The Arctic University of Norway, robert.jenssen@uit.no), Badong Chen (Xian Jiaotong University, chenbd@mail.xjtu.edu.cn), Shujian Yu (UiT The Arctic University of Norway, yusj9011@gmail.com), Supplemental workshop site:https://www.it4dl.org/. Linguistic analysis of business documents. The workshop organizers invite paper submissions on the following (and related) topics: This workshop will be a one-day workshop, featuring invited speakers, poster presentations, and short oral presentations of selected accepted papers. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. We cordially welcome researchers, practitioners, and students from academia and industry who are interested in understanding and discussing how data scarcity and bias can be addressed in AI to participate. in Proceedings of the IEEE International Conference on Data Mining (ICDM 2016), regular paper, (acceptance rate: 8.5%), pp. For previous workshops held physically, each workshop attracts around 150~300 participants. and deep learning techniques (e.g. We consider submissions that havent been published in any peer-reviewed venue (except those under review). 22, Issue 2. ACM, New York, NY, USA, 10 pages. Unsupervised Deep Subgraph Anomaly Detection. 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. Deadline: Fri Jun 09 2023 04:59:00 GMT-0700 Yahoo! IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), accepted. Integration of logical inference in training deep models. Check the deadlines for submitting your application. Please note as per the KDD Call for Workshop Proposals: Note: Workshop papers will not be archived in the ACM Digital Library. Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM Framework. Papers must be in PDF format, in English, and formatted according to the AAAI template. 4 (2014): 185-195. The first achievements in playing these games at super-human level were attained with methods that relied on and exploited domain expertise that was designed manually (e.g. Bioinformatics (Impact Factor: 6.937), accepted, 2022. Liang Zhao, Feng Chen, Jing Dai, Ting Hua, Chang-Tien Lu, and Naren Ramakrishnan. This workshop on Trustworthy Autonomous Systems Engineering (TRASE) offers an opportunity to highlight state of the art research in trustworthy autonomous systems, as well as provide a vision for future foundational and applied advances in this critical area at the intersection of AI and Cyber-Physical Systems. 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 . STGEN: Deep Continuous-time Spatiotemporal Graph Generation. The workshop welcomes the submission of work on, but not limited to, the following research directions. P. 6205, succursale Centre-villeMontral, (Qubec) H3C 3T5Canada. 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. Integration of Deep Learning and Relational Learning. 12 (2014): 90-94. Dialog systems and related technologies, including natural language processing, audio and speech processing, and vision information processing. Han Wang, Hossein Sayadi, Avesta Sasan, Houman Homayoun, Liang Zhao, Tinoosh Mohsenin, Setareh Rafatirad. Consult the list of programs available in the next session. Yuyang Gao and Liang Zhao. The financial services industry relies heavily on AI and Machine Learning solutions across all business functions and services. You also have the option to opt-out of these cookies. We especially welcome research from fields including but not limited to AI, human-computer interaction, human-robot interaction, cognitive science, human factors, and philosophy. Yiming Zhang, Yujie Fan, Yanfang Ye, Liang Zhao, Jiabin Wang, and Qi Xiong. KDD 2022 KDD . Although machine learning (ML) approaches have demonstrated impressive performance on various applications and made significant progress for AI, the potential vulnerabilities of ML models to malicious attacks (e.g., adversarial/poisoning attacks) have raised severe concerns in safety-critical applications. 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. The 21st IEEE International Conference on Data Mining (ICDM 2021), (Acceptance Rate: 9.9%), accepted. The accepted papers are allowed to be submitted to other conference venues. In some programs, spots may be available after the deadlines. Knowledge and Information Systems (KAIS), (impact factor: 2.936), accepted. Necessary cookies are absolutely essential for the website to function properly. (Depending on the volume of submissions, we may be able to accommodate only a subset of them.). 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. Generative Deep Learning for Macromolecular Structure and Dynamics, Current Opinion in Structural Biology, (impact factor: 7.108), Section on Theory and Simulation/Computational Methods 67: 170-177, 2021 accepted. 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. robust and interpretable natural language processing for healthcare. Self-supervised learning approaches involving the interaction of speech/audio and other modalities. Natural language reasoning and inference. "Unsupervised Spatial Event Detection in Targeted Domains with Applications to Civil Unrest Modeling." The 21st IEEE International Conference on Data Mining (ICDM 2021), (Acceptance Rate: 9.9%), accepted. Winter. Yet, most of these efforts highlighted the challenges of model governance and compliance processes. Linear Time Complexity Time Series Clustering with Symbolic Pattern Forest. Submissions are due by 12 November 2021. Online Flu Epidemiological Deep Modeling on By entering your email, you consent to receive communications from UdeM. Three categories of contributions are sought: full-research papers up to 8 pages; short papers up to 4 pages; and posters and demos up to 2 pages. Knowledge discovery from various data sources has gained the attention of many practitioners in recent decades. 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. For example, AI tools are built to ease the workload for teachers. Given the ever-increasing role of the World Wide Web as a source of information in many domains including healthcare, accessing, managing, and analyzing its content has brought new opportunities and challenges. We hope this will help bring the communities of data mining and visualization more closely connected. 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. [code] 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. All submissions must be anonymous and conform to AAAI standard for double-blind review. Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Information theoretic quantities (entropy, mutual information, divergence) estimation, Information theoretic methods for out-of-domain generalization and relevant problems (such as robust transfer learning and lifelong learning), Information theoretic methods for learning from limited labelled data, such as few-shot learning, zero-shot learning, self-supervised learning, and unsupervised learning, Information theoretic methods for the robustness of DNNs in AI systems, The explanation of deep learning models (in AI systems) with information-theoretic methods, Information theoretic methods in different AI applications (e.g., NLP, healthcare, robotics, finance).