While progress has been impressive, we believe we have just scratched the surface of what is capable, and much work remains to be done in order to truly understand the algorithms and learning processes within these environments. Conference stats are visualized below for a straightforward comparison. Neil T. Heffernan, Worcester Polytechnic Institute (Worcester, MA, USA), Andrew S. Lan, University of Massachusetts Amherst (Amherst, MA, USA), Anna N. Rafferty, Carleton College (Northfield, MN, USA), Adish Singla, Max Planck Institute for Software Systems (Saarbrucken, Germany). We invite the submission of original and high-quality research papers in the topics related to biased or scarce data. applications: ridesharing, online retail, food delivery, house rental, real estate, and more. 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. Negar Etemadyrad, Qingzhe Li, Liang Zhao. In Proceedings of the IEEE International Conference on Big Data (BigData 2014), pp. Online . This topic also encompasses techniques that augment or alter the network as the network is trained. 2022. AAAI is pleased to present the AAAI-22 Workshop Program. We invite thought-provoking submissions and talks on a range of topics in these fields. "Multi-resolution Spatial Event Forecasting in Social Media." Big data Journal (impact factor: 1.489), vo. We are interested in a broad range of topics, both foundational and applied. Big Data 2022 December 13-16, 2022. 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. Deep learning has achieved significant success for artificial intelligence (AI) in multiple fields. ACM, 2014. Authors are strongly encouraged to make data and code publicly available whenever possible. As a result, many AI/ML systems faced serious performance challenges and failures. Liang Zhao, Feng Chen, and Yanfang Ye. Scientific documents such as research papers, patents, books, or technical reports are one of the most valuable resources of human knowledge. ICLR 2022 Meeting Dates The Tenth annual conference is held Mon. Event Prediction in the Big Data Era: A Systematic Survey. Andy Doyle, Graham Katz, Kristen Summers, Chris Ackermann, Ilya Zavorin, Zunsik Lim, Sathappan Muthiah, Liang Zhao, Chang-Tien Lu, Patrick Butler, Rupinder Paul Khandpur. Springer, Singapore. The IEEE International Conference on Data Mining (ICDM 2022), full paper, (Acceptance Rate: 20%=174/870), short paper, to appear, 2022. 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. The Conference. 3434-3440, Melbourne, Australia, Aug 2017. The 35th Conference on Neural Information Processing Systems (NeurIPS 2021), (Acceptance Rate: 26%), accepted. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2021), (acceptance rate: 15.4%), accepted. In addition, several invited speakers with distinguished professional background will give talks related the frontier topics of GNN. Submissions will undergo double blind review. For instance, advanced driver assistance systems and autonomous cars have been developed based on AI techniques to perform forward collision warning, blind spot monitoring, lane departure warning systems, traffic sign recognition, traffic safety, infrastructure management and congestion, and so on. To provide proper alerts and timely response, public health officials and researchers systematically gather news and other reports about suspected disease outbreaks, bioterrorism, and other events of potential international public health concern, from a wide range of formal and informal sources. All questions about submissions should be emailed to nurendra@vt.edu, AmazonKDDCup2022: KDD Cup 2022 Workshop: ESCI Challenge for Improving Product Search, Washington DC, DC, United States, August 17, 2022, https://easychair.org/conferences/?conf=amazonkddcup2022, https://www.acm.org/publications/proceedings-template. Shiyu Wang, Xiaojie Guo, Liang Zhao. Comparison or integration of self-supervised learning methods and other semi-supervised and transfer learning methods in speech and audio processing tasks. All deadlines are at 11:59 PM anytime in the world. Integration of probabilistic inference in training deep models. Cesa Salaam (Howard University, USA), Hwanhee Lee (Seoul National University, South Korea), Jaemin Cho (University of North Carolina at Chapel Hill, USA), Jielin Qiu (Carnegie Mellon University, USA), Joseph Barrow (University of Maryland, US), Mengnan Du (Texas A&M University, USA), Minh Van Nguyen (University of Oregon, USA), Nicole Meister (Princeton University, USA), Sajad Sotudeh Gharebagh (Georgetown University, USA), Sampreeth Chebolu (University of Houston, USA), Sarthak Jain (Northeastern University, USA),Shufan Wang (University of Massachusetts Amherst, USA), Supplemental Workshop site:https://vtuworkshop.github.io/2022/, https://research.ibm.com/haifa/Workshops/AAAI-22-AI4DO/. 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/. Papers should be up to 4 pages in length (excluding references) formatted using the AAAI template. "Spatiotemporal Event Forecasting in Social Media." We have invited several distinguished speakers with their research interests spanning from the theoretical to experimental aspects of complex networks. RL4ED is intended to facilitate tighter connections between researchers and practitioners interested in the broad areas of reinforcement learning (RL) and education (ED). Some of the key questions to be explored include: The workshop will take place in person and will span over one day. Short or position papers of up to 4 pages are also welcome. 5, pp. Causal inference is one of the main areas of focus in artificial intelligence (AI) and machine learning (ML) communities. NOTE: Mandatory abstract deadline: 2022-08-08 Deadline: AAAI 157. 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.) How can we make AI-based systems more ethically aligned? These cookies will be stored in your browser only with your consent. We welcome the submissions in the following two formats: The submissions should adhere to theAAAI paper guidelines. anomaly detection, and ensemble learning. Using a social media account will simply make the application process easier: none of your activities on this site will be posted to your profile. The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) (Acceptance Rate: 14.99%), accepted, 2022. In addition, any other work on dialog research is welcome to the general technical track. Consequently, standard notions of software quality and reliability such as deterministic functional correctness, black box testing, code coverage, and traditional software debugging become practically irrelevant for ML systems. 2022. Incomplete Label Multi-task Deep Learning for Spatio-temporal Event Subtype Forecasting.Thirty-third AAAI Conference on Artificial Intelligence (AAAI 2019), (acceptance rate: 16.2%), Hawaii, USA, Feb 2019, accepted. 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. Note: This is the inaugural event of a conference dedicated to Graph Machine Learning. Thank you for all your contributions, our, Paper submission deadline is now extended to. We expect 50~75 participants and potentially more according to our past experiences. The workshop plans to invite about 50-75 participants. Schematic Memory Persistence and Transience for Efficient and Robust Continual Learning. Novel algorithmic solutions to causal inference or discovery problems using information-theoretic tools or assumptions. We accept two types of submissions full research paper no longer than 8 pages (including references) and short/poster paper with 2-4 pages. IEEE Transactions on Information Forensics and Security (TIFS), (impact factor: 7.178), accepted. Liang Zhao, Qian Sun, Jieping Ye, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Papers will be peer-reviewed and selected for oral and/or poster presentations at the workshop. How can we engineer trustable AI software architectures? The aim of this workshop is to focus on both original research and review articles on various disciplines of ITS applications, including particularly AI techniques for ITS time-series data analyses, ITS spatio-temporal data analyses, advanced traffic management systems, advanced traveler information systems, commercial vehicle operation systems, advanced vehicle control and safety systems, advanced public transportation services, advanced information management services, etc. Submissions are limited to 4 pages, not including references. The industry session will emphasize practical industrial product developments using GNNs. Theoretical understanding of adversarial ML and its connection to other areas. ML-guided rare event modeling and system uncertainty quantification, Development of software, libraries, or benchmark datasets, and. Novel methods to learn from scarce/sparse, or heterogenous, or multimodal data. The final schedule will be available in November. Ourprevious workshop at AAAI-21generated significant interest from the community. of London). Template guidelines are here:https://www.acm.org/publications/proceedings-template. Please email to Lingfei Wu: lwu@email.wm.edu for any query. Association for the Advancement of Artificial Intelligence, The Thirty-Sixth AAAI Conference on Artificial IntelligenceFebruary 28 and March 1, 2022Vancouver Convention CentreVancouver, BC, Canada. We send a public call and we assume the workshop will be of interest to many AAAI main conference audiences; we expect 50 participants. A Systematic Survey on Deep Generative Models for Graph Generation. The program of the workshop will include invited talks, paper presentations and a panel discussion. have been popularly applied into image recognition and time-series inferences for intelligent transportation systems (ITS). 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. 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). Yuyang Gao, Tong Sun, Rishab Bhatt, Dazhou Yu, Sungsoo Hong, and Liang Zhao. These abrupt changes impacted the environmental assumptions used by AI/ML systems and their corresponding input data patterns. Incomplete Label Uncertainty Estimation for Petition Victory Prediction with Dynamic Features. However, the quality of audio and video content shared online and the nature of speech and video transcripts pose many challenges to the existing natural language processing. 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. We invite a long research paper (8 pages) and a demo paper (4 pages) (including references). Poster session: One poster session of all accepted papers which leads for interaction and personal feedback to the research. These cookies track visitors across websites and collect information to provide customized ads. In our workshop, we specifically focus on the trustworthy issues in AI for healthcare, aiming to make clinical AI methods more reliable in real clinical settings and be willingly used by physicians. PLOS ONE (impact factor: 3.534), vo. GeoInformatica (impact factor: 2.392), 24, 443475 (2020). Xiaojie Guo, Yuanqi Du, Liang Zhao. 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. We will use double-blind reviewing. 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. 40 attendees including: invited speakers, authors of accepted papers and shared task participants. ECoST: Energy-Efficient Co-Locating and Self-Tuning MapReduce Applications. Submission site:https://cmt3.research.microsoft.com/DSTC102022, Koichiro Yoshino,Address: 2-2-2, Seika, Sohraku, Kyoto, 6190288, JapanAffiliation: RIKENPhone: +81-774-95-1360Email: koichiro.yoshino@riken.jp, Yun-Nung (Vivian) ChenAddress: No. Linguistic analysis of business documents. information bottleneck principle). 105, no. Paper Submission:November 12, 2021, 11:59 pm (anywhere on earth) Author Notification: December 3, 2021Full conference:February 22 March 1, 2022Workshop:February 28 March 1, 2022. 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. Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), (Acceptance Rate: 15%), accepted. Benchmarks to reliably evaluate attacks/defenses and measure the real progress of the field. Papers must be in PDF format, in English, and formatted according to the AAAI template. We hope this will help bring the communities of data mining and visualization more closely connected. Papers must be between 4-8 pages in the AAAI submission format, with the eighth page containing only references. [Best Paper Award]. How do metrics of capability and generality, and the trade-offs with performance affect safety? Please use ACM Conference templates (two column format). upon methodologies and applications for extracting useful knowledge from data [1]. The workshop on Robust Artificial Intelligence System Assurance (RAISA) will focus on research, development and application of robust artificial intelligence (AI) and machine learning (ML) systems. Typically, we receive around 40~60 submissions to each previous workshop. The submissions need to be anonymized. Industry-wide reports highlight large-scale remediation efforts to fix the failures and performance issues. Topics of interest include but are not limited to: Acronyms, i.e., short forms of long phrases, are common in scientific writing. 2022. ), 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. Factorized Deep Generative Models for End-to-End Trajectory Generation with Spatiotemporal Validity Constraints. Use Compass, the interactive checklist designed exclusively for the Universit de Montral, to carefully prepare your application and to avoid common pitfalls along the way. Microsoft Research CMT: https://cmt3.research.microsoft.com/DI2022, https://document-intelligence.github.io/DI-2022/ or https://aka.ms/di-2022, Workshop registration will be processed with the main KDD 2022 conference: https://kdd.org/kdd2022/, Standard ACM Conference Proceedings Template, Conflict of Interest Policy for ACM Publications, https://cmt3.research.microsoft.com/DI2022, https://document-intelligence.github.io/DI-2022/, Second Document Intelligence Workshop @ KDD 2021, First Document Intelligence Workshop @ NeurIPS 2019, Hamid Motahari, Nigel Duffy, Paul Bennett, and Tania Bedrax-Weiss. 17th International Workshop on Mining and Learning with Graphs. Novel ML methods in the computational material and physical sciences. Papers will be peer-reviewed by the Program Committee (2-3 reviewers per paper). We expect ~60 attendees. The last few years have seen the rapid development of mathematical methods for modeling structured data coming from biology, chemistry, network science, natural language processing, and computer vision applications. Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Liang Zhao. 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. Nowadays, machine learning solutions are widely deployed. Long talks (50 mins):Gabriel Peyr, (Mathematics, CNRS Senior Researcher);Yusu Wang, (Mathematics, Professor in CSE, UCSD);Caroline Uhler, (Statistics and CS, Associate Professor in EECS and IDSS, MIT); Short talks (25mins):Titouan Vayer, (Mathematics, Postdoctoral Researcher at ENS Lyon);Tam Le, (Computer Science, Research Scientist at RIKEN);Dixin Luo, (Computer Science, Assistant Professor in CS, Beijing Institute of Technology). This workshop aims to discuss important topics about adversarial ML to deepen our understanding of ML models in adversarial environments and build reliable ML systems in the real world. Submitting a short or long paper to VDS will give authors a chance to present at VDS events at both ACM KDD 2022(hybrid) and IEEE VIS 2022( hybrid). The invited speakers, who are well-recognized experts of the field, will give a 30 minute talk. The final schedule will be available in November. Papers will be submitted to OpenReview system: Waiting for approval,https://openreview.net/forum?id=6uMNTvU-akO, Workshop Chair:Parisa Kordjamshidi, +1-2174187004, kordjams@msu.edu, Organizing Committee:Parisa Kordjamshidi (Michigan State University, kordjams@msu.edu), Behrouz Babaki (Mila/HEC Montreal, behrouz.babaki@mila.quebec), Sebastijan Dumani (KU Leuven, sebastijan.dumancic@cs.kuleuven.be), Alex Ratner (University of Washington, ajratner@cs.washington.edu), Hossein Rajaby Faghihi (Michigan State University, rajabyfa@msu.edu), Hamid Karimian (Michigan State University, karimian@msu.edu), Organizing Committee:Dan Roth (University of Pennsylvania, danroth@seas.upenn.edu) and Guy Van Den Broeck (University of California Los Angeles, guyvdb@cs.ucla.edu), Supplemental workshop site:https://clear-workshop.github.io. Yevgeniy Vorobeychik (Washington University in St. Louis), Bruno Sinopoli (Washington University in St. Louis), Jinghan Yang (Washington University in St. Louis), Bo Li (UIUC), Atul Prakash (University of Michigan), Supplemental Workshop site:https://jinghany.github.io/trase2022/. We accept two types of submissions full research papers no longer than 8 pages (including references) and short/poster papers with 2-4 pages. Kyoto . With this in mind, we welcome relevant contributions on the following (and related) topic areas: The submissions must be in PDF format, written in English, and formatted according to the AAAI camera-ready style. Please note that the KDD Cup workshop will have no proceedings and the authors retain full rights to submit or post the paper at any other venue. Yuyang Gao, Liang Zhao, Lingfei Wu, Yanfang Ye, Hui Xiong, Chaowei Yang. Submissions will go through a double-blind review process. Topics include, but our not limited to: learning optimization models from data, constraint and objective learning, AutoAI, especially if combined with decision optimization models or environments, AutoRL, incorporating the inaccuracy of the automatically learnt models in the decision making process, and using machine learning to efficiently solve combinatorial optimization models. P. 6205, succursale Centre-villeMontral, (Qubec) H3C 3T5Canada. VDS@VIS Submission Deadline:Thur., July 14th, 2022, 5:00 pm PDT, VDS@VIS Author Notification:Thur., August 25th, 2022, 5:00 pm PDT, VDS@KDD Submission Deadline:Thur., May 26th June 2nd, 2022, 5:00 pm PDT, VDS@KDD Author Notification:Mon., June 20th, 2022, 5:00 pm PDT. We invite submission of papers describing innovative research and applications around the following topics. 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. It provides an international forum . 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. 2022. Attendance is open to any interested participants at AAAI-22. Call for Participation The 3rd KDD Workshop on Data-driven Humanitarian Mapping and Policymaking solicits research papers, case studies, vision papers, software demos, and extended abstracts. Submissions introducing interesting experimental phenomena and open problems of optimal transport and structured data modeling are welcome as well. 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. How to do good research, Get it published in SIGKDD and get it cited! Our topics of interest span over prediction, planning, and decision problems for online marketplaces, including but not limited to. 9, no. Papers will be submitted electronically using Easychair. Objectives of ADAM include outlining the main research challenges in this area, cross-pollinating collaborations between AI researchers and domain experts in engineering design and manufacturing, and sketching open problems of common interest. Invited speakers, panels, poster sessions, and presentations. Yiming Zhang, Yujie Fan, Wei Song, Shifu Hou, Yanfang Ye, Xin Li, Liang Zhao, Chuan Shi, Jiabin Wang, Qi Xiong. Papers will be peer-reviewed and selected for oral and/or poster presentation at the workshop. Washington DC, USA. Xiaosheng Li, Jessica Lin, Liang Zhao. a concise checklist by Prof. Eamonn Keogh (UC Riverside). All extended abstracts and full papers are to be presented at the poster sessions. Junxiang Wang, Yuyang Gao, Andreas Zufle, Jingyuan Yang, and Liang Zhao. The goal of this workshop is to offer an opportunity to appreciate the diversity in applications, to draw connections to inform decision optimization across different industries, and to discover new problems that are fundamental to marketplaces of different domains. The eligibility criteria for attending the workshop will be registration in the conference/workshop as per AAAI norms. The workshop welcomes the submission of work on, but not limited to, the following research directions. Chen Ling, Junji Jiang, Junxiang Wang, Liang Zhao. 205-214, San Francisco, California, Aug 2016. The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) (Acceptance Rate: 14.99%), accepted, 2022. For research track papers and applied data science track papers. Andrew White, University of RochesterDr. This workshop wants to emphasize on the importance of integrative paradigms for solving the new wave of AI applications. ), 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). After the submission deadline, the names and order of authors cannot be changed. Finally, the workshop will welcome papers that describe the release of privacy-preserving benchmarks and data sets that can be used by the community to solve fundamental problems of interest, including in machine learning and optimization for health systems and urban networks, to mention but a few examples. simulation, evaluation and experimentation. Representation learning, distributed representations learning and encoding in natural language processing for financial documents; Synthetic or genuine financial datasets and benchmarking baseline models; Transfer learning application on financial data, knowledge distillation as a method for compression of pre-trained models or adaptation to financial datasets; Search and question answering systems designed for financial corpora; Named-entity disambiguation, recognition, relationship discovery, ontology learning and extraction in financial documents; Knowledge alignment and integration from heterogeneous data; Using multi-modal data in knowledge discovery for financial applications; Data acquisition, augmentation, feature engineering, and analysis for investment and risk management; Automatic data extraction from financial fillings and quality verification; Event discovery from alternative data and impact on organization equity price; AI systems for relationship extraction and risk assessment from legal documents; Accounting for Black-Swan events in knowledge discovery methods. RES: A Robust Framework for Guiding Visual Explanation. We invite novel contributions following the AAAI-22 formatting guidelines, camera-ready style. SL-VAE: Variational Autoencoder for Source Localization in Graph Information Diffusion. Self-supervised learning utilizes proxy supervised learning tasks, for example, distinguishing parts of the input signal from distractors, or generating masked input segments conditioned on the unmasked ones, to obtain training data from unlabeled corpora. 25, 2022: We have announced Call for Nominations: , Mar. [Bests of ICDM]. Why did so many AI/ML models fail during the pandemic? 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. We will accept the extended abstracts of the relevant and recently published work too. Scott E. Fahlman, School of Computer Science, Carnegie Mellon University (sef@cs.cmu.edu), Edouard Oyallon, Sorbonne Universit LIP6 (Edouard.oyallon@lip6.fr), Dean Alderucci, School of Computer Science, Carnegie Mellon University, (dalderuc@cs.cmu.edu). Pourya Hoseinip, Liang Zhao, and Amarda Shehu. ReForm: Static and Dynamic Resource-Aware DNN Reconfiguration Framework for Mobile Devices. The workshop aims at bridging formalisms for learning and reasoning such as neural and symbolic approaches, probabilistic programming, differentiable programming, Statistical Relation Learning and using non-differentiable optimization in deep models. This workshop has no archival proceedings. The 33rd European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databasesg (ECML-PKDD 2022) (Acceptance Rate: 26%), accepted, 2022. Panel discussion: Interactive Q&A session with a panel of leading researchers. Second, psychological experiments in laboratories and in the field, in partnership with technology companies (e.g., using apps), to measure behavioral outcomes are being increasingly used for informing intervention design. FedAT: A High-Performance and Communication-Efficient Federated Learning System with Asynchronous Tiers. 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. 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. Attendance is expected to be 150-200 participants (estimated), including organizers and speakers. Submission at:https://easychair.org/my/conference?conf=edsmls2022.