Jos Miguel Hernndez-Lobato, University of CambridgeProf. Finally, there is an increasing interest in AI in moving beyond traditional supervised learning approaches towards learning causal models, which can support the identification of targeted behavioral interventions. Big data Journal (impact factor: 1.489), vo. The 19th International Conference on Data Mining (ICDM 2019), short paper, (acceptance rate: 18.05%), Beijing, China, accepted. Xuchao Zhang, Liang Zhao, Arnold Boedihardjo, and Chang-Tien Lu. 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. 205-214, San Francisco, California, Aug 2016. Submissions introducing interesting experimental phenomena and open problems of optimal transport and structured data modeling are welcome as well. Submissions of technical papers can be up to 7 pages excluding references and appendices. Web applications along with text processing programs are increasingly being used to harness online data and information to discover meaningful patterns identifying emerging health threats. We invite submission of papers describing innovative research on all aspects of knowledge discovery and data science, ranging from theoretical foundations to novel models and algorithms for data science problems in science, business, medicine, and engineering. Integration of neuro and symbolic approaches. System reports should also follow the AAAI 2022 formatting guidelines and have 4-6 pages including references. 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. Submissions are due by 12 November 2021. Junxiang Wang, Fuxun Yu, Xiang Chen, and Liang Zhao. "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. Workshops will be held Monday and Tuesday, February 28 and March 1, 2022. Submit to:https://easychair.org/conferences/?conf=imlaaai22, Elizabeth DalyAddress: IBM Dublin Technology Campus, Dublin 15, IrelandEmail: elizabeth.daly@ie.ibm.com, Elizabeth Daly, IBM Research, Ireland (elizabeth.daly@ie.ibm.com), znur Alkan, IBM Research, Ireland (oalkan2@ie.ibm.com), Stefano Teso, University of Trento, Italy (stefano.teso@unitn.it), Wolfgang Stammer, TU Darmstadt, Germany (wolfgang.stammer@cs.tu-darmstadt.de), Workshop URL:https://sites.google.com/view/aaai22-imlw. iDev: Enhancing Social Coding Security by Cross-platform User Identification Between GitHub and Stack Overflow. STGEN: Deep Continuous-time Spatiotemporal Graph Generation. The workshop also welcomes participants of SUPERB and Zero Speech challenge to submit their results. This topic encompasses forms of Neural Architecture Search (NAS) in which the performance properties of each architecture, after some training, are used to guide the selection of the next architecture to be tried. Liyan Xu, Xuchao Zhang, Zong Bo, Yanchi Liu, Wei Cheng, Jingchao Ni, Haifeng Chen, Liang Zhao, Jinho Choi. 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. Data science is the practice of deriving insights from data, enabled by statistical modeling, computational methods, interactive visual analysis, and domain-driven problem solving. Deep Graph Translation. The workshop follows a single-blind reviewing process. The trained models are intended to assign scores to novel utterances, assessing whether they are possible or likely utterances in the training language. with other vehicles via vehicular communication systems (e.g., dedicated short range communication (DSRC), vehicular ad hoc networks (VANETs), long term evolution (LTE), and 5G/6G mobile networks) for cooperation. Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, and Chang-TIen Lu. sup-port vector machine (SVM), decision tree, random forest, etc.) These challenges and issues call for robust artificial intelligence (AI) algorithms and systems to help. and Simone Stumpf (Univ. Social Media based Simulation Models for Understanding Disease Dynamics. Estimating the Circuit Deobfuscating Runtime based on Graph Deep Learning. The annual ACM SIGMOD/PODS Conference is a leading international forum for database researchers, practitioners, developers, and users to explore cutting-edge ideas and results, and . Please use ACM Conference templates (two column format). Lastly, learning joint modalities is of interest to both Natural Language Processing (NLP) and Computer Vision (CV) forums. Previous healthcare-related workshops focus on how to develop AI methods to improve the accuracy and efficiency of clinical decision-making, including diagnosis, treatment, triage. Papers will be peer-reviewed and selected for oral and/or poster presentation at the workshop. The industry session will emphasize practical industrial product developments using GNNs. Note: This is the inaugural event of a conference dedicated to Graph Machine Learning. "A Uniform Representation for Trajectory Learning Tasks", 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL 2017), short paper, DOI=10.1145/3139958.3140017, Redondo Beach, CA, USA, Nov 2017. Deep Graph Learning for Circuit Deobfuscation. After the submission deadline, the names and order of authors cannot be changed. Thank you for all your contributions, our, Paper submission deadline is now extended to. How to do good research, Get it published in SIGKDD and get it cited! References will not count towards the page limit. [Bests of ICDM]. KDD is the premier Data Science conference. Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, and Yanfang Ye. December, 12-16, 2022. This workshop will encourage researchers from interdisciplinary domains working on multi-modality and/or fact-checking to come together and work on multimodal (images, memes, videos etc.) Motif-guided Heterogeneous Graph Deep Generation. Continuous refinement of AI models using active/online learning. Three specific roles are part of this format: session chairs, presenters and paper discussants. Yuanqi Du*, Shiyu Wang* (co-first author), Xiaojie Guo, Hengning Cao, Shujie Hu, Junji Jiang, Aishwarya Varala, Abhinav Angirekula, Liang Zhao. References will not count towards the page limit. Andy Doyle, Graham Katz, Kristen Summers, Chris Ackermann, Ilya Zavorin, Zunsik Lim, Sathappan Muthiah, Liang Zhao, Chang-Tien Lu, Patrick Butler, Rupinder Paul Khandpur. We will accept the extended abstracts of the relevant and recently published work too. The 35th Conference on Neural Information Processing Systems (NeurIPS 2021), (Acceptance Rate: 26%), accepted. Authors are invited to send a contribution in the AAAI-22 proceedings format. Deep Generation of Heterogeneous Networks. This calls for novel methods and new methodologies and tools to address quality and reliability challenges of ML systems. IEEE Computer (impact factor: 3.564), vo. 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. Submissions must be formatted in the AAAI submission format (https://www.aaai.org/Publications/Templates/AuthorKit22.zip) All submissions should be done electronically via EasyChair. There is increasing evidence that enabling AI technology has the potential to aid in the aforementioned paradigm shift. The submissions must be in PDF format, written in English, and formatted according to the AAAI camera-ready style. 2022. IEEE Transactions on Pattern Analysis and Machine Intelligence (Impact Factor: 24.31), accepted. Guangji Bai, Chen Ling, Liang Zhao. The goal of this workshop is to connect researchers in self-supervision inside and outside the speech and audio fields to discuss cutting-edge technology, inspire ideas and collaborations, and drive the research frontier. Saliency-regularized Deep Multi-task Learning. Knowledge and Information Systems (KAIS), (impact factor: 2.936), accepted. We are in a conversation with some publishers once they confirm, we will announce accordingly. AI is one of these transformative technologies that is now achieving great successes in various real-world applications and making our life more convenient and safer. The submitted contributions will be peer-reviewed by the Program Committee, and preference will be given to high-quality original and relevant work to the Document Intelligence topics. Poster session: One poster session of all accepted papers which leads for interaction and personal feedback to the research. Half day event featuring a panel, invited and keynote speakers and presentations selected through a CFP. Guangji Bai and Liang Zhao. Deadline in . This cookie is set by GDPR Cookie Consent plugin. We solicit papers describing significant and innovative research and applications to the field of job marketplaces. The workshop will include several technical sessions, a virtual poster session where presenters can discuss their work, to further foster collaborations, multiple invited speakers covering crucial aspects for the practical deep learning in the wild, especially the efficient and robust deep learning, some tutorial talks, the challenge for efficient deep learning and solution presentations, and will conclude with a panel discussion. We received 38 paper submissions and accepted 23 of them. There will be live Q&A sessions at the end of each talk and oral presentation. in Proceedings of the SIAM International Conference on Data Mining (SDM 2015), (acceptance rate: 22%), Vancouver, BC, pp. It is anticipated that this will be an in-person workshop, subject to changing travel restrictions and health measures. Counter-intuitive behaviors of ML models will largely affect the public trust on AI techniques, while a revolution of machine learning/deep learning methods may be an urgent need. Contrast Feature Dependency Pattern Mining for Controlled Experiments with Application to Driving Behavior. Submissions should follow the AAAI 2022 formatting guidelines and the AAAI 2022 standards for double-blind review including anonymous submission. Data Mining and Knowledge Discovery (DMKD), (impact factor: 3.670), accepted. CPM: A General Feature Dependency Pattern Mining Framework for Contrast Multivariate Time Series. Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs. How can we make AI-based systems more ethically aligned? Make sure your desired study programs are open for admission in the session when you would like to start your studies. Continuous V&V and predictability of AI safety properties, Runtime monitoring and (self-)adaptation of AI safety, Accountability, responsibility and liability of AI-based systems, Avoiding negative side effects in AI-based systems, Role and effectiveness of oversight: corrigibility and interruptibility, Loss of values and the catastrophic forgetting problem, Confidence, self-esteem and the distributional shift problem, Safety of AGI systems and the role of generality, Self-explanation, self-criticism and the transparency problem, Regulating AI-based systems: safety standards and certification, Human-in-the-loop and the scalable oversight problem, Experiences in AI-based safety-critical systems, including industrial processes, health, automotive systems, robotics, critical infrastructures, among others. Inspired by the question, there is a trend in the machine learning community to adopt self-supervised approaches to pre-train deep networks. ), 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. 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. Zhiqian Chen, Lei Zhang, Gaurav Kolhe, Hadi Mardani Kamali, Setareh Rafatirad, Sai Manoj Pudukotai Dinakarrao, Houman Homayoun, Chang-Tien Lu, Liang Zhao. . The 33rd European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databasesg (ECML-PKDD 2022) (Acceptance Rate: 26%), accepted, 2022.
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kdd 2022 deadline
