RLG is a full-day workshop. 1, 2022: Call For Paper: The Undergraduate Consortium at SIGKDD 2022 is available at, Mar. Integration of Deep learning and Constraint programming. We invite submission of papers describing innovative research and applications around the following topics. Poster session: One poster session of all accepted papers which leads for interaction and personal feedback to the research. Inspired by the question, there is a trend in the machine learning community to adopt self-supervised approaches to pre-train deep networks. 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. 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. Yuyang Gao and Liang Zhao. It is anticipated that this will be an in-person workshop, subject to changing travel restrictions and health measures. The program consists of poster sessions for accepted papers, and invited and spotlight talks. We expect 50-65 people in the workshop. Transformations in many fields are enabled by rapid advances in our ability to acquire and generate data. The cookie is used to store the user consent for the cookies in the category "Performance". There is a need for the research community to develop novel solutions for these practical issues. Submissions will undergo double blind review. Multilingual document understanding methods and frameworks. Causality has received significant interest in ML in recent years in part due to its utility for generalization and robustness. We have invited several distinguished speakers with their research interests spanning from the theoretical to experimental aspects of complex networks. The positive/negative social impacts and ethical issues related to adversarial ML. "A Generic Framework for Interesting Subspace Cluster Detection in Multi-attributed Networks", in Proceedings of the IEEE International Conference on Data Mining (ICDM 2017) , regular paper; (acceptance rate: 9.25%), pp. We propose a full day workshop with the following sessions: The workshop solicits paper submissions from participants (26 pages). Meta-learning models from various existing task-specific AI models. [materials][data]. Towards Quantized Model Parallelism for Graph-Augmented MLPs Based on Gradient-Free ADMM Framework. Geoinformatica, (impact factor: 2.392), Volume 20, Issue 4, pp 765-795, Oct 2016. ETA (expected time-of-arrival) prediction. These models can also generate instant feedback to instructors and help them to improve their teaching effectiveness. Application-specific designs for explainable AI, e.g., healthcare, autonomous driving, etc. IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), vol. This cookie is set by GDPR Cookie Consent plugin. A primary reason for this is the inherent long-tailed nature of our world, and the need for algorithms to be trained with large amounts of data that includes as many rare events as possible. KDD - ACM Conferences 29, no. The 19th International Conference on Data Mining (ICDM 2019), short paper, (acceptance rate: 18.05%), Beijing, China, accepted. Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs. The Conference. 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). Pourya Hoseinip, Liang Zhao, and Amarda Shehu. 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. ICONF 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/. Ferdinando Fioretto (Syracuse University), Aleksandra Korolova (University of Southern California), Pascal Van Hentenryck (Georgia Institute of Technology), Supplemental Workshop site:https://aaai-ppai22.github.io/. In nearly all applications, reliability, safety, and security of such systems is a critical consideration. Poster/short/position papers submission deadline: Nov 5, 2021Full paper submission deadline: Nov 5, 2021Paper notification: Dec 3, 2021. "TITAN: A Spatiotemporal Feature Learning Framework for Traffic Incident Duration Prediction", the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2019 (SIGSPATIAL 2019), long paper, (acceptance rate: 21.7%), Chicago, Illinois, USA, accepted. ), The workshop will be organized as half-day event with 2 invited speakers, follow by presentation from accepted papers (both ordinary papers, and shared task paper). It is valuable to bring together researchers and practitioners from different application domains to discuss their experiences, challenges, and opportunities to leverage cross-domain knowledge. We hope this will help bring the communities of data mining and visualization more closely connected. These submissions would benefit from additional exposure and discussion that can shape a better future publication. 2022. This proposed workshop will build upon successes and learnings from last years successful AI for Behavior Change workshop, and will focus on on advances in AI and ML that aim to (1) design and target optimal interventions; (2) explore bias and equity in the context of decision-making and (3) exploit datasets in domains spanning mobile health, social media use, electronic health records, college attendance records, fitness apps, etc. Liang Zhao, Olga Gkountouna, and Dieter Pfoser. We will also organize 3 shared tasks in this workshop: punctuation restoration, domain adaptation for punctuation restoration, and chitchat detection. Submissions may consist of up to 4 pages plus one additional page solely for references. 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. Interactive Machine Learning (IML) is concerned with the development of algorithms for enabling machines to cooperate with human agents. 205-214, San Francisco, California, Aug 2016. 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. 40, no. Note: This is the inaugural event of a conference dedicated to Graph Machine Learning. Analytical cookies are used to understand how visitors interact with the website. "SimNest: Social Media Nested Epidemic Simulation via Online Semi-supervised Deep Learning." Our intent is to facilitate new AI/ML advances for core engineering design, simulation, and manufacturing. Template guidelines are here:https://www.acm.org/publications/proceedings-template. SIAM International Conference on Data Mining (SDM 2023) (Acceptance Rate: 27.4%), accepted. the 56th Design Automation Conference (DAC 2019), accepted, (acceptance rate: 20%), Las Vegas, US, 2019. KDD 2022 | Washington DC, U.S. SIGKDD CONFERENCE Latest News Aug 12, 2022: Please check out the proceedings access information. Thirty-First AAAI Conference on Artificial Intelligence, pp. 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. 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. CVPR 11 deadline . Chen Ling, Carl Yang, and Liang Zhao. 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. It is also central for tackling decision-making problems such as reinforcement learning, policy or experimental design. Submissions can be original research contributions, or abstracts of papers previously submitted to top-tier venues, but not currently under review in other venues and not yet published. ITCI22 will be a one-day workshop. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), (Impact Factor: 14.255), accepted. Interpretable Molecular Graph Generation via Monotonic Constraints. A striking feature of much of this recent work is the application of new theoretical and computational techniques for comparing probability distributions defined on spaces with complex structures, such as graphs, Riemannian manifolds and more general metric spaces. All papers must be submitted in PDF format, using the AAAI-22 author kit. Dazhou Yu, Guangji Bai, Yun Li, and Liang Zhao. 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. Accepted papers will be published in the workshop proceedings. KDD: Knowledge Discovery and Data Mining 2024 2023 2022 - WikiCFP The topics for AIBSD 2022 include, but are not limited to: This one-day workshop will include invited talks from keynote speakers, and oral/spotlight presentations of the accepted papers. Even in cases where one is able to collect data, there are inherently many kinds of biases in this process, leading to biased models. Data science draws from methodology developed in such fields as applied mathematics, statistics, machine learning, data mining, data management, visualization, and HCI. 2020. Question answering on business documents. of Graz), Cynthia Rudin (Duke Univ.) 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. Temporal Domain Generalization with Drift-Aware Dynamic Neural Network. Liang Zhao's Homepage - Emory University Hence, AI methods are required to understand and protect the cyber domain. The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC 2021), (acceptance rate: 23.6%), accepted. There is increasing evidence that enabling AI technology has the potential to aid in the aforementioned paradigm shift. Declarative languages and differentiable programming. 47, no. The official dates for submitting an application are detailed below, but see the exact deadline posted on the Description Page for the program of study. An Invertible Graph Diffusion Model for Source Localization. Our topics of interest span over prediction, planning, and decision problems for online marketplaces, including but not limited to. Whats more, various AI based models are trained on massive student behavioral and exercise data to have the ability to take note of a students strengths and weaknesses, identifying where they may be struggling. The main research questions and topics of interest include, but are not limited to: This will be a one day workshop, including four invited speakers, one panel session, a number of oral presentations of the accepted long papers and two poster sessions for all accepted papers including short and long. Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao. But opting out of some of these cookies may affect your browsing experience. . Registration information will be mailed directly to all invited participants in December. Submissions tackling new problems or more than one of the aforementioned topics simultaneously are encouraged. Yuyang Gao, Tong Sun, Rishab Bhatt, Dazhou Yu, Sungsoo Hong, and Liang Zhao. 12 (2014): 90-94. The acceptance decisions will take in account novelty, technical depth and quality, insightfulness, depth, elegance, practical or theoretical impact, reproducibility and presentation. Xiaosheng Li, Jessica Lin, Liang Zhao. Oilers Outperform Division Rivals at 2023 Trade Deadline Topics of interest include, but are not limited to: One day, comprising keynote, paper presentations and panel sessions. How do metrics of capability and generality, and the trade-offs with performance affect safety? DB transactions) to unstructured data (e.g. 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 papers have to be submitted through EasyChair. Technology has transformed over the last few years, turning from futuristic ideas into todays reality. Hierarchical Incomplete Multisource Feature Learning for Spatiotemporal Event Forecasting. in Proceedings of the 22st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2016), research track (acceptance rate: 18.2%), San Francisco, California, pp. Ting Hua, Chandan Reddy, Lijing Wang, Liang Zhao, Lei Zhang, Chang-Tien Lu, and Naren Ramakrishnan. Novel AI-based techniques to improve modeling of engineering systems. AD Conference Deadlines Disentangled Spatiotemporal Graph Generative Model. 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 . 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. 2022. Integration of probabilistic inference in training deep models. Xiaojie Guo, Liang Zhao, Houman Homayoun, Sai Manoj Pudukotai Dinakarrao. Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Eliminating the need to guess the right topology in advance of training is a prominent benefit of learning network architecture during training. Submissions should be formatted using the AAAI-2022 Author Kit. 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. Welcome to PAKDD2022. We will also select some of the best posters for spotlight talks (2 minutes each). Xuchao Zhang, Liang Zhao, Zhiqian Chen, and Chang-Tien Lu. The cookie is used to store the user consent for the cookies in the category "Other. Linear Time Complexity Time Series Clustering with Symbolic Pattern Forest. Liang Zhao. job seekers, employers, recruiters and job agents. These cookies ensure basic functionalities and security features of the website, anonymously. 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. ), 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. CoRL 2023 97 days 17h 29m 15s November 06-09, 2023. Accepted papers are likely to be archived. 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. [Best Paper Award]. What is the status of existing approaches in ensuring AI and Machine Learning (ML) safety, and what are the gaps? in Proceedings of the 24st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018), research track (acceptance rate: 18.4%), London, United Kingdom, Aug 2018, accepted. Yiming Zhang, Yujie Fan, Yanfang Ye, Liang Zhao, Jiabin Wang, and Qi Xiong. July 21: Clarified that the workshop this year will be held in-person. Thank you for all your contributions, our, Paper submission deadline is now extended to. Deadline in . For program deadlines, click on the Admissions and Regulations tab on the specific page of study. Submissions will be accepted via the Easychair submission website. Submissions that do not meet the formatting requirements will be rejected without review. Distributed Self-Paced Learning in Alternating Direction Method of Multipliers. The deadline for the submissions is July 31st, 2022 11.59 PM (Anywhere on Earth time). Published March 4, 2023 4:51 a.m. PST. Deep Spatial Domain Generalization. This 1-day workshop will include a mixture of invited speakers, panels (including discussion with the audience), and presentations from authors of accepted submissions. ), responsible development of human-centric SSL (e.g., safety, limitations, societal impacts, and unintended consequences), ethical and legal implications of using SSL on human-centric data, implications of SSL on robustness and fairness, implications of SSL on privacy and security, interpretability and explainability of human-centric SSL frameworks, if your work broadly addresses the use of unlabeled human-centric data with unsupervised or semi-supervised learning, if your work focuses on architectures and frameworks for SSL for sensory data beyond CV and NLP (but not necessarily human-centric data). Some examples of the success of information theory in causal inference are: the use of directed information, minimum entropy couplings and common entropy for bivariate causal discovery; the use of the information bottleneck principle with applications in the generalization of machine learning models; analyzing causal structures of deep neural networks with information theory; among others. Distant-supervision of heterogeneous multitask learning for social event forecasting with multilingual indicators. ), Learning with algebraic or combinatorial structure, Link analysis/prediction, node classification, graph classification, clustering for complex graph structures, Theoretical analysis of graph algorithms or models, Optimization methods for graphs/manifolds, Probabilistic and graphical models for structured data, Unsupervised graph/manifold embedding methods. 19-25, 2016. 507-516, Singapore, Nov 2017. At least one author of each accepted submission must register and present their paper at the workshop. Yuyang Gao, Siyi Gu, Junji Jiang, Sungsoo Ray Hong, Dazhou Yu, and Liang Zhao. Deep Classifier Cascades for Open World Recognition. Researchers from related domains are invited to submit papers on recent advanced technologies, resources, tools and challenges for VTU. search, ranking, recommendation, and personalization. The workshop follows a single-blind reviewing process. 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." It is well-known that deep learning techniques that were disruptive for Euclidean data such as images or sequence data such as text are not immediately applicable to graph-structured data. NOTE: Mandatory abstract deadline on Oct 13, 2022. 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. Topics of interest include, but are not limited to: Paper submissions will be in two formats: full paper (8 pages) and position paper (4 pages): The submission website ishttps://easychair.org/conferences/?conf=trase2022. We will receive the paper on the CMT system. 10 (2014): e110206. The 9th International Conference on Learning Representations (ICLR 2021), (acceptance rate: 28.7%), accepted. About 7-8 invited speakers who are distinguished professional in Deep learning on graph will present the frontier research topics. Furthermore, leveraging AI to connect disparate social networks amongst teachers \\cite{karimi2020towards}, we may be able to provide greater resources for their planning, which have been shown to significantly affect students achievement. Cleansing and image enhancement techniques for scanned documents. The official dates for submitting an application are detailed below, but see the exact deadline posted on the Description Page for the program of study. The post-lunch session will feature a second keynote talk, two invited talks. Optimal transport theory, including statistical and geometric aspects; Gromov-Wasserstein distance and its variants; Bayesian inference for/with optimal transport; Gromovization of machine learning methods; Optimal transport-based generative modeling. CS Conference Deadlines - Yanlin 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. 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. Spatio-temporal Event Forecasting Using Incremental Multi-source Feature Learning. We will end the workshop with a panel discussion by top researchers in the field. Lastly, learning joint modalities is of interest to both Natural Language Processing (NLP) and Computer Vision (CV) forums. The research contributions may discuss technical challenges of reading and interpreting business documents and present research results. The deep learning community must often confront serious time and hardware constraints from suboptimal architectural decisions. The 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Datasets and Benchmarks Track, accepted. Complex systems are often characterized by several components that interact in multiple ways among each other. This AAAI workshop aims to bring together researchers from core AI/ML, robotics, sensing, cyber physical systems, agriculture engineering, plant sciences, genetics, and bioinformatics communities to facilitate the increasingly synergistic intersection of AI/ML with agriculture and food systems. 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. Onn Shehory, Bar Ilan University (onn.shehory@biu.ac.il), Eitan Farchi, IBM Research Haifa (farchi@il.ibm.com), Guy Barash, Western Digital (Guy.Barash@wdc.com), Supplemental workshop site:https://sites.google.com/view/edsmls-2022/home. 2022. "A Topic-focused Trust Model for Twitter." RL4ED is intended to facilitate tighter connections between researchers and practitioners interested in the broad areas of reinforcement learning (RL) and education (ED). Pengtao Xie (main contact), Assistant Professor, University of California, San Diego, pengtaoxie2008@gmail.com Engineer Ln, San Diego, CA 92161 (Tel)4123206230, Marinka Zitnik, Assistant Professor, Harvard University, marinka@hms.harvard.edu 10 Shattuck Street, Boston, MA 02115 (Tel)6503086763, Byron Wallace, Assistant Professor, Northeastern University, byron@ccs.neu.edu 177 Huntington Ave, Boston, MA 02115 (Tel)4135120352, Eric P. Xing, Professor, Carnegie Mellon University, epxing@cs.cmu.edu 5000 Forbes Ave, Pittsburgh, PA 15213 (Tel)4122682559, Ramtin Hosseini, PhD Student, University of California, San Diego, rhossein@eng.ucsd.edu (Tel) 3104293825, Ethics and fairness in autonomous systems, Robust robotic design, particularly of autonomous drones and/or vehicles. 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. 2020. We are soliciting submissions of short papers in PDF format and formatted according to the Standard ACM Conference Proceedings Template.