Regarding efficiency, it is impractical to train a neural network containing billions of parameters and then deploy it to an edge device in practice. KDD 2022 : 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining Conference Series : Knowledge Discovery and Data Mining Link: https://kdd.org/kdd2022/ Call For Papers [Empty] Related Resources KDD 2023 29TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING Liang Zhao, Jiangzhuo Chen, Feng Chen, Fang Jin, Wei Wang, Chang-Tien Lu, and Naren Ramakrishnan. The submissions must be in PDF format, written in English, and formatted according to the AAAI camera-ready style. 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. Qingzhe Li, Liang Zhao, Yi-Ching Lee, Avesta Sassan, and Jessica Lin. These complex demands have brought profound implications and an explosion of interest for research into the topic of this workshop, namely building practical AI with efficient and robust deep learning models. Such systems are better modeled by complex graph structures such as edge and vertex labeled graphs (e.g., knowledge graphs), attributed graphs, multilayer graphs, hypergraphs, temporal/dynamic graphs, etc. Spatiotemporal Innovation Center Team. Interpreting and Evaluating Neural Network Robustness. 2022. As a result, many AI/ML systems faced serious performance challenges and failures. Multilingual document understanding methods and frameworks. Attendance is open to all; at least one author of each accepted submission must be physically/virtually present at the workshop. [Submission deadline extended, June 3] KDD 2022 Workshop on - INFORMS Lyle Unga (University of Pennsylvania, ungar@cis.upenn.edu), Rahul Ladhania* (University of Michigan, ladhania@umich.edu, primary contact), Linnea Gandhi (University of Pennsylvania, lgandhi@wharton.upenn.edu), Michael Sobolev (Cornell Tech, michael.sobolev@cornell.edu), Supplemental workshop site:https://ai4bc.github.io/ai4bc22/, For any questions, please reach out to us at ai4behaviorchange at gmail dot com. The ability to read, understand and interpret these documents, referred to here as Document Intelligence (DI), is challenging due to their complex formats and structures, internal and external cross references deployed, quality of scans and OCR performed, and many domains of knowledge involved. Continuous refinement of AI models using active/online learning. Eliminating the need to guess the right topology in advance of training is a prominent benefit of learning network architecture during training. Our topics of interest span over prediction, planning, and decision problems for online marketplaces, including but not limited to. Incomplete Label Uncertainty Estimation for Petition Victory Prediction with Dynamic Features. July 22: The workshop Programis up! 2022. 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. The 19th International Conference on Data Mining (ICDM 2019), long paper, (acceptance rate: 9.08%), Beijing, China. 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. It is important to learn how to use AI effectively in these areas in order to be able to motivate and help people to take actions that maximize their welfare. August 14-18, 2022. NOTE: Mandatory abstract deadline: 2022-08-08 Deadline: AAAI 157. This workshop has no archival proceedings. Frontiers in Neurorobotics, (impact factor: 2.574), accepted. Some of the key questions to be explored include: The workshop will take place in person and will span over one day. Workshop Date: Sunday August 14, 2022 EDT. 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. KDD 2023 August 06-10, 2023. Paper Submission Deadline: 23:59 on Thursday. Novel mechanisms for eliciting and consuming user feedback, recommender, structured and generative models, concept acquisition, data processing, optimization; HCI and visualization challenges; Analysis of human factors/cognition and user modelling; Design, testing and assessment of IML systems; Studies on risks of interaction mechanisms, e.g., information leakage and bias; Business use cases and applications. Deep Classifier Cascades for Open World Recognition. Guangji Bai, Chen Ling, Yuyang Gao, Liang Zhao. Check the CFP for details Deadline: ICDM 2020 . Zheng Zhang and Liang Zhao. The bottleneck to discovery is now our ability to analyze and make sense of heterogeneous, noisy, streaming, and often massive datasets. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc. 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. Note: This is the inaugural event of a conference dedicated to Graph Machine Learning. ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 3.089), accepted. ACM, 2013. Liang Zhao. 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. Publication in HC-SSL does not prohibit authors from publishing their papers in archival venues such as NeurIPS/ICLR/ICML or IEEE/ACM Conferences and Journals. 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. For general inquiries about AI2ASE, please write to the lead organizer aryan.deshwal@wsu.edu or jana.doppa@wsu.edu. The current research in this area is focused on extending existing ML algorithms as well as network science measures to these complex structures. 625-634, New Orleans, US, Dec 2017. We will accept the extended abstracts of the relevant and recently published work too. The theme of the hack-a-thon will be decided before submission is closed and will be focused around finding creative solutions to novel problems in health. Welcome to the 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2022), which will be held in Chengdu, China on May 16-19, 2022. The Thirty-Sixth AAAI Conference on Artificial IntelligenceFebruary 28 and March 1, 2022Vancouver Convention CentreVancouver, BC, Canada AAAI is pleased to present the AAAI-22 Workshop Program. 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. It has profoundly impacted several areas, including computer vision, natural language processing, and transportation. Position papers are welcome. At least one author of each accepted submission must present the paper at the workshop. Xiaojie Guo and Liang Zhao. 2999-3006, New Orleans, US, Feb 2018. Neurocomputing (Impact Factor: 5.719), accepted. Ting Hua, Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Feng Chen, Baojian Zhou, Adil Alim, Liang Zhao. IEEE Computer (impact factor: 3.564), vo. 1059-1072, May 1 2017. ICDM: International Conference on Data Mining 2024 2023 2022 - WikiCFP Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment. Nonetheless, human-centric problems (such as activity recognition, pose estimation, affective computing, BCI, health analytics, and others) rely on information modalities with specific spatiotemporal properties. 1799-1808. 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. All these changes require novel solutions, and the AI community is well-positioned to provide both theoretical- and application-based methods and frameworks. Attendance is expected to be 150-200 participants (estimated), including organizers and speakers. 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. In recent years, machine learning techniques (e.g. Wenbin Zhang, Liming Zhang, Dieter Pfoser, Liang Zhao. In the coronavirus era, requiring many schools to move to online learning, the ability to give feedback at scale could provide needed support to teachers. 76, pp. Xiaojie Guo, Liang Zhao, Cameron Nowzari, Setareh Rafatirad, Houman Homayoun, and Sai Dinakarrao. The accepted papers will be posted on the workshop website and will not appear in the AAAI proceedings. Advances in complex engineering systems such as manufacturing and materials synthesis increasingly seek artificial intelligence/machine learning (AI/ML) solutions to enhance their design, development, and production processes. The cookie is used to store the user consent for the cookies in the category "Performance". IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), vol. We expect 50~75 participants and potentially more according to our past experiences. 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. Would you like to mark this message as the new best answer? Babies learn their first language through listening, talking, and interacting with adults. Integration of logical inference in training deep models. Yuyang Gao, Tong Sun, Rishab Bhatt, Dazhou Yu, Sungsoo Hong, and Liang Zhao. The IEEE International Conference on Data Mining (ICDM 2022), full paper, (Acceptance Rate: 20%=174/870), short paper, to appear, 2022. Yuyang Gao, Lingfei Wu, Houman Homayoun, and Liang Zhao. Self-supervised learning approaches involving the interaction of speech/audio and other modalities. 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. Submissions are limited to a maximum of four (4) pages, including all content and references, and must be in PDF format. Papers that are under review at another conference or journal are acceptable for submission at this workshop, but we will not accept papers that have already been accepted or published at a venue with formal proceedings (including KDD 2022). Bioinformatics (Impact Factor: 6.937), accepted, 2022. Make sure your desired study programs are open for admission in the session when you would like to start your studies. Jos Miguel Hernndez-Lobato, University of CambridgeProf. We are interested in a broad range of topics, both foundational and applied. Table identification and extraction from business documents. Adaptive Kernel Graph Neural Network. KDD 2022. Topics of interest include but are not limited to: (1) Survey papers summarizing recent advances in RL with applicability to ED; (2) Developing toolkits and datasets for applying RL methods to ED; (3) Using RL for online evaluation and A/B testing of different intervention strategies in ED; (4) Novel applications of RL for ED problem settings; (5) Using pedagogical theories to narrow the policy space of RL methods; (6) Using RL methodology as a computational model of students in open-ended domains; (7) Developing novel offline RL methods that can efficiently leverage historical student data; (8) Combining statistical power of RL with symbolic reasoning to ensure the robustness for ED. Data Mining Conferences - GitHub Introduction: SIGKDD aims to provide the premier forum for advancement and adoption of the "science" of knowledge discovery and data mining.SIGKDD will encourage: basic research in KDD (through annual research conferences, newsletter and other related activities .

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