Xuchao Zhang, Shuo Lei, Liang Zhao, Arnold Boedihardjo, Chang-Tien Lu, "Robust Regression via Heuristic Corruption Thresholding and Its Adaptive Estimation Variation", ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 1.98), accepted, 2019. Short or position papers of up to 4 pages are also welcome. Submission at:https://easychair.org/my/conference?conf=edsmls2022. DB transactions) to unstructured data (e.g. CFP - EasyChair ASPLOS 2023 will be moving to three submission deadlines. 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. Naftali Cohen (JP Morgan Chase & New York University), Eren Kurshan (Bank of America & Columbia University), Senthil Kumar (Capital One), Susan Tibbs (Financial Institutions Regulatory Authority, FINRA), Tucker Balch (JP Morgan Chase & Georgia Institute of Technology), and Kevin Compher (Securities Exchange Commission). Papers should be up to 4 pages in length (excluding references) formatted using the AAAI template. Submission URL:https://easychair.org/conferences/?conf=rl4edaaai22. AAAI-22 Workshop Program - AAAI In fact, the increasingly digitized education tools and the popularity of online learning have produced an unprecedented amount of data that provides us with invaluable opportunities for applying AI in education. Please keep your paper format according to AAAI Formatting Instructions (two-column format). This one-day workshop will consist of: (1) an ice-breaking session, (2) paper presentations, (3) a poster session, and (4) an ideation brainstorming session. We invite a long research paper (8 pages) and a demo paper (4 pages) (including references). Zhiqian Chen, Gaurav Kolhe, Setareh Rafatirad, Chang-Tien Lu, Sai Dinakarrao, Houman Homayoun, Liang Zhao. Extended abstracts should not exceed 2 pages, excluding references. The submissions need to be anonymized. We invite submissions on a wide range of topics, spanning both theoretical and practical research and applications. 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. Tanmoy Chowdhury, Chen Ling, Xuchao Zhang, Xujiang Zhao, Guangji Bai, Jian Pei, Haifeng Chen, Liang Zhao. 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. 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. Liang Zhao, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Please note that foreign students must allow for 3 to 6 months to complete all the formalities required to study in Canada. Technology has transformed over the last few years, turning from futuristic ideas into todays reality. Submissions should follow the AAAI 2022 formatting guidelines and the AAAI 2022 standards for double-blind review including anonymous submission. In this workshop we would like to focus on a contrasting approach, to learn the architecture during training. International Journal of Digital Earth, (impact factor: 3.097), 25 Aug 2020, https://doi.org/10.1080/17538947.2020.1809723. All papers must be submitted in PDF format using the AAAI-22 author kit. Liang Zhao, Feng Chen, and Yanfang Ye. ACM Transactions on Spatial Algorithms and Systems (TSAS), 5, 3, Article 19 (September 2019), 28 pages. Handwritten recognition in business documents. It leverages many emerging privacy-preserving technologies (SMC, Homomorphic Encryption, differential privacy, etc.) However, despite increasing interest from various subfields, AI/ML techniques are yet to fulfill their full promise in achieving these advances. Please note as per the KDD Call for Workshop Proposals: Note: Workshop papers will not be archived in the ACM Digital Library. CVPR 11 deadline . 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. 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. 5 (2014): 1447-1459. Manuscripts must be submitted as PDF files viaEasyChair online submission system. applications: ridesharing, online retail, food delivery, house rental, real estate, and more. [code] 205-214, San Francisco, California, Aug 2016. In the Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), (acceptance rate: 17.9%), accepted, Macao, China, Aug 2019. Welcome to PAKDD2022. Yuyang Gao, Tanmoy Chowdhury (co-first author), Lingfei Wu, Liang Zhao. [Best Paper Award]. One recommended setting for Latex file is:\documentclass[sigconf, review]{acmart}. In the Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), (acceptance rate: 17.9%), accepted, Macao, China, Aug 2019. Martin Michalowski, PhD, FAMIA (Co-chair), University of Minnesota; Arash Shaban-Nejad, PhD, MPH (Co-chair), The University of Tennessee Health Science Center Oak-Ridge National Lab (UTHSC-ORNL) Center for Biomedical Informatics; Simone Bianco, PhD (Co-chair), IBM Almaden Research Center; Szymon Wilk, PhD, Poznan University of Technology; David L. Buckeridge, MD, PhD, McGill University; John S. Brownstein, PhD, Boston Childrens Hospital, Workshop URL:http://w3phiai2022.w3phi.com/. The workshop page ishttps://sites.google.com/view/aaaiwfs2022, and it will include the most up-to-date information, including the exact schedule. Options include pruning a trained network or training many networks automatically. Submissions are due by 12 November 2021. Optimal transport-based machine learning paradigms; Trustworthy machine learning from the perspective of optimal transport. At least three research trends are informing insights in this field. 22, Issue 2. The review process will be single blind. Submission instructions will be available at the workshop web page. Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), (Acceptance Rate: 15%), accepted. Qingzhe Li, Jessica Lin, Liang Zhao and Huzefa Rangwala. 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. 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. We have invited several distinguished speakers with their research interests spanning from the theoretical to experimental aspects of complex networks. SIGMOD 2022 adheres to the ACM Policy Against Harassment. AAAI, specifically, is a great venue for our workshop because its audience spans many ML and AI communities. 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/. Full (8 pages) and short (4 pages, work in progress) papers, AAAI style. Liang Zhao, Jieping Ye, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan. Large-scale Cost-aware Classification Using Feature Computational Dependency Graph. Jinliang Ding, Liang Zhao, Changxin Liu, and Tianyou Chai. Liang Zhao, Junxiang Wang, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan. All submissions must be original contributions and will be peer reviewed, single-blinded. Data mining systems and platforms, and their efficiency, scalability, security and privacy. Qingzhe Li, Liang Zhao, Yi-Ching Lee, Yanfang Ye, Jessica Lin, and Lingfei Wu. Please refer to the KDD 2022 website for the policies of Conflict of Interest, Violations of Originality, and Dual Submission: A Best Paper Award will be presented to the best full paper as voted by the reviewers. We invite submissions of full papers, as well as works-in-progress, position papers, and papers describing open problems and challenges. Attendance is open to all. Held in conjunction with KDD'22 Aug 15, 2022 - Washington DC, USA. IEEE Transactions on Knowledge and Data Engineerings (TKDE), (impact factor: 6.977), accepted. In addition, any other work on dialog research is welcome to the general technical track. 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 will also have a panel discussion on the current and future of GNNs on both research and industry. ), 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. 1503-1512, Aug 2015. Submissions will undergo double blind review. In addition, authors can provide an optional one page supplement at the end of their submitted paper (it needs to be in the same PDF file) focused on reproducibility. This is especially the case for non-traditional online resources such as social networks, blogs, news feed, twitter posts, and online communities with the sheer size and ever-increasing growth and change rate of their data. I recommend highly motivated students to reach out to me way earlier than the admission deadline, and figure out a research project project with me, with the goal of a publication. Submit to:https://cmt3.research.microsoft.com/AIBSD2022, Kuan-Chuan Peng (Mitsubishi Electric Research Laboratories, kp388@cornell.edu), Ziyan Wu (UII America, Inc., wuzy.buaa@gmail.com), Supplemental workshop site:https://aibsdworkshop.github.io/2022/index.html. KDD 2022 | Washington DC, U.S. SIGKDD CONFERENCE Latest News Aug 12, 2022: Please check out the proceedings access information. 10, pp. We invite thought-provoking submissions on a range of topics in fields including, but not limited to, the following areas: The full-day workshop will start with a keynote talk, followed by an invited talk and contributed paper presentations in the morning. Papers more suited for a poster, rather than a presentation, would be invited for a poster session. Data-driven Humanitarian Mapping and Policymaking Research The 48th International Conference on Parallel Processing (ICPP 2019), (acceptance rate: 20%), accepted, Kyoto, Japan. 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. Outcomes include outlining the main research challenges in this area, potential future directions, and cross-pollination between AI researchers and domain experts in agriculture and food systems. For authors who do not wish their papers to be posted online, please mention this in the workshop submission. Natural language reasoning and inference. Topics of interest include, but are not limited to: One day, comprising keynote, paper presentations and panel sessions. Despite the great success of deep neural networks (DNNs) in many artificial intelligence (AI) tasks, they still suffer from limitations, such as poor generalization behavior for out-of-distribution (OOD) data, vulnerability to adversarial examples, and the black-box nature of DNNs. A new and comprehensive view of AI Safety must cover a wide range of AI paradigms, including systems that are application-specific as well as those that are more general, considering potentially unanticipated risks. "Spatiotemporal Event Forecasting in Social Media." The fundamental mechanism of an online marketplace is to match supply and demand to generate transactions, with objectives considering service quality, participants experience, financial and operational efficiency. Question answering on business documents. Yujie Fan, Yanfang (Fanny) Ye, Qian Peng, Jianfei Zhang, Yiming Zhang, Xusheng Xiao, Chuan Shi, Qi Xiong, Fudong Shao, and Liang Zhao. The Thirty-Sixth Annual Conference on Neural Information Processing Systems (NeurIPS 2022), (Acceptance Rate: 25.6%), to appear, 2022. 1923-1935, 1 Oct. 2020, doi: 10.1109/TKDE.2019.2912187. Registration Opens: Feb 02 '22 02:00 PM UTC: Registration Cancellation Refund Deadline: Apr 18 '22(Anywhere on Earth) Paper Submissions Abstract Submission Deadline: Sep 29 '21 12:00 AM UTC: Paper Submission deadline: Oct 06 '21 12:00 AM . The 35th Conference on Neural Information Processing Systems (NeurIPS 2021), (Acceptance Rate: 26%), accepted. 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. Some specific topics in the context of scientific discovery and engineering design include (but not limited to): This will be a one day workshop with a number of paper presentations and poster spotlights, a poster session, several invited talks, and a panel discussion. The academic session will focus on most recent research developments on GNNs in various application domains. ACM, 2014. Negar Etemadyrad, Yuyang Gao, Qingzhe Li, Xiaojie Guo, Frank Krueger, Qixiang Lin, Deqiang Qiu, and Liang Zhao. Graph Neural Networks: Foundations, Frontiers, and Applications. Multi-instance Domain Adaptation for Vaccine Adverse Event Detection.27th International 2022. 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. Unsupervised Deep Subgraph Anomaly Detection. Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, and Yanfang Ye. Interpretable Molecular Graph Generation via Monotonic Constraints. 8 pages), short (max. Ourprevious workshop at AAAI-21generated significant interest from the community. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. Submissions will be assessed based on their novelty, technical quality, significance of impact, interest, clarity, relevance, and reproducibility. The goal of this workshop is to bring together the optimal transport, artificial intelligence, and structured data modeling, gathering insights from each of these fields to facilitate collaboration and interactions. Information theory has demonstrated great potential to solve the above challenges. Integration of Deep learning and Constraint programming. All deadlines are at 11:59 PM anytime in the world. San Francisco, USA . Researchers from related fields are invited to submit papers on the recent advances, resources, tools, and upcoming challenges for SDU. 4, Roosevelt Rd., Taipei, TaiwanAffiliation: National Taiwan UniversityPhone: +1-412-465-0130Email: yvchen@csie.ntu.edu.tw, Paul CrookAddress: 1 Hacker Way, Menlo Park, CA, USAAffiliation: FacebookPhone: +1-650-885-0094Email: pacrook@fb.com, DSTC 10 home:https://dstc10.dstc.community/homeDSTC 10 CFPs:https://dstc10.dstc.community/calls_1/call-for-workshop-papers. Eliminating the need to guess the right topology in advance of training is a prominent benefit of learning network architecture during training. iCal Outlook robotics Key obstacles include lack of high-quality data, difficulty in embedding complex scientific and engineering knowledge in learning, and the need for high-dimensional design space exploration under constrained budgets. 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. 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. Submissions will be peer reviewed, single-blinded. Optimal transport-based analysis of structured data, such as networks, meshes, sequences, and so on; The applications of optimal transport in molecule analysis, network analysis, natural language processing, computer vision, and bioinformatics. These cookies will be stored in your browser only with your consent. We especially welcome research from fields including but not limited to AI, human-computer interaction, human-robot interaction, cognitive science, human factors, and philosophy. The post-lunch session will feature one long talk, two short talks, and a poster session. There were two workshops on similar topics hosted at ICML 2020 and NeurIPS 2020, and both workshops observed positive feedback and overwhelming participation. Linear Time Complexity Time Series Clustering with Symbolic Pattern Forest. In the Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), (acceptance rate: 17.9%), accepted, Macao, China, Aug 2019. convolutional neural network (CNN), recurrent neural network (RNN), etc.) Award for Artificial Intelligence for the Benefit of Humanity, Patrick Henry Winston Outstanding Educator Award, A Report to ARPA on Twenty-First Century Intelligent Systems, The Role of Intelligent Systems in the National Information Infrastructure, Code of Conduct for Conferences and Events, Request to Reproduce Copyrighted Materials, AAAI Conference on Artificial Intelligence, W1: Adversarial Machine Learning and Beyond, W2: AI for Agriculture and Food Systems (AIAFS), W6: AI in Financial Services: Adaptiveness, Resilience & Governance, W7: AI to Accelerate Science and Engineering (AI2ASE), W8: AI-Based Design and Manufacturing (ADAM) (Half-Day), W9: Artificial Intelligence for Cyber Security (AICS)(2-Day), W10: Artificial Intelligence for Education (AI4EDU), W11: Artificial Intelligence Safety (SafeAI 2022)(1.5-Day), W12: Artificial Intelligence with Biased or Scarce Data, W13: Combining Learning and Reasoning: Programming Languages, Formalisms, and Representations (CLeaR), W14: Deep Learning on Graphs: Methods and Applications (DLG-AAAI22), W15: DE-FACTIFY :Multi-Modal Fake News and Hate-Speech Detection, W16: Dialog System Technology Challenge (DSTC10), W17: Engineering Dependable and Secure Machine Learning Systems (EDSMLS 2022) (Half-Day), W18: Explainable Agency in Artificial Intelligence, W19: Graphs and More Complex Structures for Learning and Reasoning (GCLR), W21: Human-Centric Self-Supervised Learning (HC-SSL), W22: Information-Theoretic Methods for Causal Inference and Discovery (ITCI22), W23: Information Theory for Deep Learning (IT4DL), W25: Knowledge Discovery from Unstructured Data in Financial Services (Half-Day), W26: Learning Network Architecture during Training, W27: Machine Learning for Operations Research (ML4OR) (Half-Day), W28: Optimal Transport and Structured Data Modeling (OTSDM), W29: Practical Deep Learning in the Wild (PracticalDL2022), W30: Privacy-Preserving Artificial Intelligence, W31: Reinforcement Learning for Education: Opportunities and Challenges, W32: Reinforcement Learning in Games (RLG), W33: Robust Artificial Intelligence System Assurance (RAISA) (Half-Day), W34: Scientific Document Understanding (SDU) (Half-Day), W35: Self-Supervised Learning for Audio and Speech Processing, W36: Trustable, Verifiable and Auditable Federated Learning, W38: Trustworthy Autonomous Systems Engineering (TRASE-22), W39: Video Transcript Understanding (Half-Day), https://openreview.net/group?id=AAAI.org/2022/Workshop/AdvML, https://openreview.net/group?id=AAAI.org/2022/Workshop/AIAFS, https://easychair.org/conferences/?conf=aaai-2022-workshop, https://rail.fzu.edu.cn/info/1014/1064.htm, https://aaai.org/Conferences/AAAI-22/aaai22call/, https://sites.google.com/view/aaaiwfs2022, https://www.aaai.org/Publications/Templates/AuthorKit22.zip, https://openreview.net/group?id=AAAI.org/2022/Workshop/ADAM, https://easychair.org/conferences/?conf=aics22, https://cmt3.research.microsoft.com/AIBSD2022, https://aibsdworkshop.github.io/2022/index.html, https://openreview.net/forum?id=6uMNTvU-akO, https://easychair.org/conferences/?conf=dlg22, https://deep-learning-graphs.bitbucket.io/dlg-aaai22/, https://cmt3.research.microsoft.com/DSTC102022, https://dstc10.dstc.community/calls_1/call-for-workshop-papers, https://easychair.org/my/conference?conf=edsmls2022, https://sites.google.com/view/edsmls-2022/home, https://sites.google.com/view/eaai-ws-2022/call, https://sites.google.com/view/eaai-ws-2022/topic, https://sites.google.com/view/gclr2022/submissions, https://cmt3.research.microsoft.com/AAAI2022HCSSL/Submission/Index, https://cmt3.research.microsoft.com/ITCI2022, https://easychair.org/conferences/?conf=it4dl, https://easychair.org/conferences/?conf=imlaaai22, https://sites.google.com/view/aaai22-imlw, https://easychair.org/conferences/?conf=kdf22, Learning Network Architecture During Training, https://cmt3.research.microsoft.com/OTSDM2022, https://cmt3.research.microsoft.com/PracticalDL2022, https://cmt3.research.microsoft.com/PPAI2022, https://easychair.org/conferences/?conf=rl4edaaai22, https://sites.google.com/view/raisa-2022/, https://sites.google.com/view/sdu-aaai22/home, https://cmt3.research.microsoft.com/SAS2022, https://easychair.org/conferences/?conf=fl-aaai-22, http://federated-learning.org/fl-aaai-2022/, https://cmt3.research.microsoft.com/TAIH2022, https://easychair.org/conferences/?conf=trase2022, https://easychair.org/my/conference?conf=vtuaaai2022, Symposium on Educational Advances in Artificial Intelligence (EAAI-22), Conference on Innovative Applications of Artificial Intelligence (IAAI-22). The Institute for Operations Research and the Management Sciences, [Submission deadline extended, June 3] KDD 2022 Workshop on Decision Intelligence and Analytics for Online Marketplaces: Jobs, Ridesharing, Retail, and Beyond, We are excited to announce our upcoming workshop at. The financial services industry relies heavily on AI and Machine Learning solutions across all business functions and services. Junxiang Wang, Fuxun Yu, Xiang Chen, and Liang Zhao. Different from machine learning, Knowledge Discovery and Data Mining (KDD) is considered to be more practical and more related with real-world applications. Papers will be peer-reviewed and selected for spotlight and/or poster presentation. Self-Paced Robust Learning for Leveraging Clean Labels in Noisy Data. MLG 2022 - 17th International Workshop on Mining and Learning with Graphs Knowledge discovery from various data sources has gained the attention of many practitioners in recent decades. RecSys 2022 - Important Dates - RecSys Social Media based Simulation Models for Understanding Disease Dynamics. Junxiang Wang, Hongyi Li, Liang Zhao. Functional Connectivity Prediction with Deep Learning for Graph Transformation. IEEE Computer (impact factor: 3.564), vo. 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. Factorized Deep Generative Models for End-to-End Trajectory Generation with Spatiotemporal Validity Constraints. in Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015), research track, (acceptance rate: 19.4%), Sydney, Australia, pp. What safety engineering considerations are required to develop safe human-machine interaction? These choices can only be analyzed holistically if the technological and ethical perspectives are integrated into the engineering problem, while considering both the theoretical and practical challenges of AI safety. 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. 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 . Submissions including full papers (6-8 pages) and short papers (2-4 pages) should be anonymized and follow the AAAI-22 Formatting Instructions (two-column format) at https://www.aaai.org/Publications/Templates/AuthorKit22.zip.
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