In addition, authors can provide an optional two (2) page supplement at the end of their submitted paper (it needs to be in the same PDF file) focused on reproducibility. Submit to: Papers are required to submit to:https://easychair.org/conferences/?conf=dlg22. The 30th International World Wide Web Conference, the Web Conference (WWW 2021), (acceptance rate: 20.6%), accepted. Tips for Doing Good DM Research & Get it Published! This half day workshop will focus on research into the use of AI techniques to extract knowledge from unstructured data in financial services. Junxiang Wang, Zheng Chai, Yue Cheng, and Liang Zhao. 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. TG-GAN: Continuous-time Temporal Graph Deep Generative Models with Time-Validity Constraints. We expect 60-70 participants. We welcome attendance from individuals who do not have something theyd like to submit but who are interested in RL4ED research. Dialog systems and related technologies, including natural language processing, audio and speech processing, and vision information processing. The aim of the hack-a-thon is not only to foster innovation and potentially provide answers to outstanding research problems, but rather to engage the community and create new collaborations. 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. Track 2 focuses on the state of the art advances in the computational jobs marketplace. Poster/short/position papers: We encourage participants to submit preliminary but interesting ideas that have not been published before as short papers. 2020. Precision agriculture and farm management, Development of open-source software, libraries, annotation tools, or benchmark datasets, Bias/equity in algorithmic decision-making, AI for ITS time-series and spatio-temporal data analyses, AI for the applications of transportation, Applications and techniques in image recognition based on AI techniques for ITS, Applications and techniques in autonomous cars and ships based on AI techniques. A challenge is how to integrate people into the learning loop in a way that is transparent, efficient, and beneficial to the human-AI team as a whole, supporting different requirements and users with different levels of expertise. Rather than studying robustness with respect to particular ML algorithms, our approach will be to explore robustness assurance at the system architecture level, during both development and deployment, and within the human-machine teaming context. 40 attendees including: invited speakers, authors of accepted papers and shared task participants. "Misinformation Propagation in the Age of Twitter." Adversarial attacking deep learning systems, Robust architectures against adversarial attacks, Hardware implementation and on-device deployment, Benchmark for evaluating model robustness, New methodologies and architectures for efficient and robust deep learning, December 3, 2021 Acceptance Notification, Applications of privacy-preserving AI systems, Differential privacy: theory and applications, Distributed privacy-preserving algorithms, Privacy preserving optimization and machine learning, Privacy preserving test cases and benchmarks. Full (8 pages) and short (4 pages, work in progress) papers, AAAI style. Algorithms and theories for learning AI models under bias and scarcity. Information theory has demonstrated great potential to solve the above challenges. 2022. Functional Connectivity Prediction with Deep Learning for Graph Transformation. Half day event featuring a panel, invited and keynote speakers and presentations selected through a CFP. Liang Zhao, Jiangzhuo Chen, Feng Chen, Fang Jin, Wei Wang, Chang-Tien Lu, and Naren Ramakrishnan. SDU accepts both long (8 pages including references) and short (4 pages including references) papers. Computers & Electrical Engineering (impact factor: 2.189), vo. 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. Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), (Acceptance Rate: 15%), accepted. 1145/3394486.3403221. Options include pruning a trained network or training many networks automatically. iDev: Enhancing Social Coding Security by Cross-platform User Identification Between GitHub and Stack Overflow. Participants will be given access to publicly available datasets and will be asked to use tools from AI and ML to generate insight from the data. 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-launch session includes the invited talks, shared task winners presentations, and a panel discussion on the resources, findings, and upcoming challenges. It has profoundly impacted several areas, including computer vision, natural language processing, and transportation. In nearly all applications, reliability, safety, and security of such systems is a critical consideration. What is the status of existing approaches in ensuring AI and Machine Learning (ML) safety, and what are the gaps? "Spatiotemporal Event Forecasting from Incomplete Hyper-local Price Data" The 26th ACM International Conference on Information and Knowledge Management (CIKM 2017) , (acceptance rate: 21%), pp. in Proceedings of the IEEE International Conference on Data Mining (ICDM 2015), regular paper (acceptance rate: 8.4%), Atlantic City, NJ, pp. Papers will be submitted electronically using Easychair. Application-specific designs for explainable AI, e.g., healthcare, autonomous driving, etc. Submissions will go through a double-blind review process. IEEE, 2014. Deep Classifier Cascades for Open World Recognition. We will accept both original papers up to 8 pages in length (including references) as well as position papers and papers covering work in progress up to 4 pages in length (not including references).Submission will be through Easychair at the AAAI-22 Workshop AI4DO submission site, Professor Bistra Dilkina (dilkina@usc.edu), USC and Dr. Segev Wasserkrug, (segevw@il.ibm.com), IBM Research, Prof. Andrea Lodi (andrea.lodi@cornell.edu), Jacobs Technion-Cornell Institute IIT and Dr. Dharmashankar Subrmanian (dharmash@us.ibm.com), IBM Research. It does not store any personal data. Information extraction from text and semi-structured documents. The adversarial ML could also result in potential data privacy and ethical issues when deploying ML techniques in real-world applications. SIAM International Conference on Data Mining (SDM 2023) (Acceptance Rate: 27.4%), accepted. Accepted contributions will be made publicly available as non-archival reports, allowing future submissions to archival conferences or journals. Chen Ling, Tanmoy Chowdhury, Junji Jiang, Junxiang Wang, Xuchao Zhang, Haifeng Chen, and Liang Zhao. Toward Model Parallelism for Deep Neural Network based on Gradient-free ADMM Framework. The current research in this area is focused on extending existing ML algorithms as well as network science measures to these complex structures. 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/. San Francisco, USA . The review process will be single blind. 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. Position papers are welcome. This workshop wants to emphasize on the importance of integrative paradigms for solving the new wave of AI applications. . Zitao Liu (main contact) , TAL Education Group, liuzitao@tal.com, http://www.zitaoliu.com, Jiliang Tang (Michigan State University, tangjili@msu.edu, https://www.cse.msu.edu/~tangjili/), Lihan Zhao (TAL Education Group, zhaolihan@tal.com), and Xiao Zhai (TAL Education Group, zhaixiao@tal.com), Workshop URL:http://ai4ed.cc/workshops/aaai2022. It is expected that one of the authors of accepted contributions will register and attend the workshop to present the work in video in-person in the workshops Paper Sessions. Machine Learning-Based Delay-Aware UAV Detection and Operation Mode Identification over Encrypted Wi-Fi Traffic. Check the deadlines for submitting your application. AAAI is pleased to present the AAAI-22 Workshop Program. It further combines academia and industry in a quest for well-founded practical solutions. Pourya Hoseinip, Liang Zhao, and Amarda Shehu. Some good examples include recommender systems, clustering, graph mining, 2022. These abrupt changes impacted the environmental assumptions used by AI/ML systems and their corresponding input data patterns. We welcome submissions of long (max. We also use third-party cookies that help us analyze and understand how you use this website. Attendance is open to all, subject to any room occupancy constraints. Short or position papers of up to 4 pages are also welcome. At least one author of each accepted submission must register and present their paper at the workshop. Balaraman Ravindran (Indian Institute of Technology Madras, India ravi@cse.iitm.ac.in), Balaraman Ravindran (Indian Institute of Technology Madras, India Primary contact (ravi@cse.iitm.ac.in), Kristian Kersting (TU Darmstadt, Germany, kersting@cs.tu-darmstadt.de), Sriraam Natarajan (Univ of Texas Dallas, USA, Sriraam.Natarajan@utdallas.edu), Ginestra Bianconi (Queen Mary University of London, UK, ginestra.bianconi@gmail.com), Philip S. Chodrow (University of California, Los Angeles, USA, phil@math.ucla.edu) Tarun Kumar (Indian Institute of Technology Madras, India, tkumar@cse.iitm.ac.in), Deepak Maurya (Purdue University, India, maurya@cse.iitm.ac.in), Shreya Goyal (Indian Institute of Technology Madras, India, Goyal.3@iitj.ac.in), Workshop URL:https://sites.google.com/view/gclr2022/. 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. Paper Submission Deadline: 23:59 on Thursday. Paper Final Version Due: Monday August 1, 2022. Government day with NSF, NIH, DARPA, NIST, and IARPA, Local industries in the DC Metro Area, including the Amazons second headquarter, New initiatives at KDD 2022: undergraduate research and poster session, Early career research day with postdoctoral scholars and assistant professors in a mentoring workshop and panel, Workshops and hands-on tutorials on emerging topics. All submissions must be in PDF format and formatted according to the new Standard AAAI Conference Proceedings Template. By entering your email, you consent to receive communications from UdeM. However, FL also faces multiple challenges that may potentially limit its applications in real-world use scenarios. The accepted papers will be posted on the workshop website and will not appear in the AAAI proceedings. 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. The Thirty-Sixth Annual Conference on Neural Information Processing Systems (NeurIPS 2022), (Acceptance Rate: 25.6%), to appear, 2022. Submissions of technical papers can be up to 7 pages excluding references and appendices. Efficient Learning with Exponentially-Many Conjunctive Precursors for Interpretable Spatial Event Forecasting. Although machine learning (ML) approaches have demonstrated impressive performance on various applications and made significant progress for AI, the potential vulnerabilities of ML models to malicious attacks (e.g., adversarial/poisoning attacks) have raised severe concerns in safety-critical applications. Eliminating the need to guess the right topology in advance of training is a prominent benefit of learning network architecture during training. 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. The 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), long paper, (acceptance rate: 19.4%), Beijing, China, accepted. ACM Transactions on Spatial Algorithms and Systems (TSAS), accepted. Aug 14-18. Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022), (Acceptance Rate: 15%), accepted. By registering, you agree to receive emails from UdeM. 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. Well also host a competition on adversarial ML along with this workshop. arXiv preprint arXiv:2207.09542 (2022). Topics of interest in the biomedical space include: Topics of general interest to cyber-security include: Submission site:https://easychair.org/conferences/?conf=aics22, Tamara Broderick (MIT CSAIL, tamarab@mit.edu), James Holt (Laboratory for Physical Sciences, USA, holt@lps.umd.edu), Edward Raff (Booz Allen Hamilton, USA, Raff_Edward@bah.com), Ahmad Ridley (National Security Agency), Dennis Ross (MIT Lincoln Laboratory, USA, dennis.ross@ll.mit.edu), Arunesh Sinha (Singapore Management University, Singapore, aruneshs@smu.edu.sg), Diane Staheli (MIT Lincoln Laboratory, USA, diane.staheli@ll.mit.edu), William W. Streilein (MIT Lincoln Laboratory, USA, wws@ll.mit.edu), Milind Tambe (Harvard University, USA, milind_tambe@harvard.edu), Yevgeniy Vorobeychik (Washington University in Saint Louis, USA, eug.vorobey@gmail.com) Allan Wollaber (MIT Lincoln Laboratory, USA, Allan.Wollaber@ll.mit.edu), Supplemental workshop site:http://aics.site/. Multi-objective Deep Data Generation with Correlated Property Control. Spatial Auto-regressive Dependency Interpretable Learning Based on Spatial Topological Constraints. All papers will be peer-reviewed, single-blinded (i.e., please include author names/affiliations/email addresses on your first page). 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. System reports will be presented during poster sessions. Advances in AI technology, particularly perception and planning, have enabled unprecedented advances in autonomy, with autonomous systems playing an increasingly important role in day-to-day lives, with applications including IoT, drones, and autonomous vehicles. Sathappan Muthiah, Patrick Butler, Rupinder Paul Khandpur, Parang Saraf, Nathan Self, Alla Rozovskaya, Liang Zhao, Jose Cadena et al. Qingzhe Li, Liang Zhao, Yi-Ching Lee, Yanfang Ye, Jessica Lin, and Lingfei Wu. The workshop will focus on two thrusts: 1) Exploring how we can leverage recent advances in RL methods to improve state-of-the-art technology for ED; 2) Identifying unique challenges in ED that can help nurture technical innovations and next breakthroughs in RL. SDU is expected to host 50-60 attendees. Dazhou Yu, Guangji Bai, Yun Li, and Liang Zhao. December 2020, July 21: Clarified that the workshop this year will be held, June 20: Paper notification is now extended to, Paper reviews are underway! Workshop URL:https://rail.fzu.edu.cn/info/1014/1064.htm, Prof. Chi-Hua ChenEmail: chihua0826@gmail.comPostal address: No.2, Xueyuan Rd., Fuzhou, Fujian, ChinaTelephone: +86-18359183858. Submissions are limited to a maximum of four (4) pages, including all content and references, and must be in PDF format. Property Controllable Variational Autoencoder via Invertible Mutual Dependence. Disease Contact Network. Knowledge Discovery and Data Mining. Robust Regression via Online Feature Selection under Adversarial Data Corruption. Participants are welcomed to submit their system reports to be presented in the workshop. However, these real-world applications typically translate to problem domains where it is extremely challenging to even obtain raw data, let alone annotated data. FedAT: A High-Performance and Communication-Efficient Federated Learning System with Asynchronous Tiers. Novel AI-enabled generative models for system design and manufacturing. Positive applications of adversarial ML, i.e., adversarial for good. 22, Issue 2. The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) (Acceptance Rate: 14.99%), accepted, 2022. 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. Hua, Ting, Feng Chen, Liang Zhao, Chang-Tien Lu, and Naren Ramakrishnan. References will not count towards the page limit. 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. applications: ridesharing, online retail, food delivery, house rental, real estate, and more. Estimate of the audience size: 400-500 attendees (based on the number of attendees in previous DLG workshops in KDD19, AAAI20, KDD20 and AAAI21). 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. 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. Identification of information-theoretic quantities relevant for causal inference and discovery. Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors. How can we make AI-based systems more ethically aligned? You also have the option to opt-out of these cookies. Nowadays, machine learning solutions are widely deployed. Attendance is open to all; at least one author of each accepted paper must be virtually present at the workshop. 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. This one-day workshop will bring concentrated discussions on self-supervision for the field of speech/audio processing via keynote speech, invited talks, contributed talks and posters based on community-submitted high-quality papers, and the result representation of SUPERB and Zero Speech challenge. We will also have a video component for remote participation. Yuyang Gao, Liang Zhao, Lingfei Wu, Yanfang Ye, Hui Xiong, Chaowei Yang. 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. Games provide an abstract and formal model of environments in which multiple agents interact: each player has a well-defined goal and rules to describe the effects of interactions among the players. Typically, we receive around 40~60 submissions to each previous workshop. Distributed Self-Paced Learning in Alternating Direction Method of Multipliers. Liming Zhang, Dieter Pfoser, Liang Zhao. 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. Attendance is open to all; at least one author of each accepted submission must be physically/virtually present at the workshop. Frontiers in Big Data, accepted, 2021. Submissions may consist of up to 7 pages of technical content plus up to two additional pages solely for references. The review process is double-blind, and we follow the Conflict of Interest Policy for ACM Publications. IEEE Transactions on Knowledge and Data Engineering (TKDE), (impact factor: 6.977), accepted. Meta-learning models from various existing task-specific AI models. Characterization of fundamental limits of causal quantities using information theory. LOG 2022 LOG '22 . "Knowledge-enhanced Neural Machine Reasoning: A Review." Cyber systems generate large volumes of data, utilizing this effectively is beyond human capabilities. in the proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), (acceptance rate: 26%), pp. 5, pp. [paper] 4498-4505, New Orleans, US, Feb 2018. 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 aim to bring together researchers in AI, healthcare, medicine, NLP, social science, etc. Submission URL:https://easychair.org/conferences/?conf=rl4edaaai22. "Multi-resolution Spatial Event Forecasting in Social Media." 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. In the Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), (acceptance rate: 17.9%), accepted, Macao, China, Aug 2019. Other submissions will be evaluated by a committee based on their novelty and insights. We allow both short (2-4 pages) and long papers (6-8 pages) papers. RAISAs systems-level perspective will be emphasized via three main thrusts: AI threat modeling, AI system robustness, explainable AI, system lifecycle attacks, system verification and validation, robustness benchmarks and standards, robustness to black-box and white-box adversarial attacks, defenses against training, operational and inversion attacks, AI system confidentiality, integrity, and availability, AI system fairness and bias. References will not count towards the page limit. Xuchao Zhang, Liang Zhao, Zhiqian Chen, and Chang-Tien Lu. Knowledge discovery from various data sources has gained the attention of many practitioners in recent decades. Prof. Max Welling, University of Amsterdam and Microsoft ResearchProf. Benchmarks to reliably evaluate attacks/defenses and measure the real progress of the field. URL: https://sites.google.com/view/kdd22onlinemarketplaces Call For Papers (Submission deadline: June3, 2022) Theoretical or empirical studies focusing on understanding why self-supervision methods work for speech and audio. Please note as per the KDD Call for Workshop Proposals: Note: Workshop papers will not be archived in the ACM Digital Library. One recommended setting for Latex file is:\documentclass[sigconf, review]{acmart}. Submit to:https://openreview.net/group?id=AAAI.org/2022/Workshop/AdvML, Yinpeng Dong (dyp17@mails.tsinghua.edu.cn, 30 Shuangqing Road, Haidian District, Tsinghua University, Beijing, China, 100084, Phone: +86 18603303421), Yinpeng Dong (Tsinghua University, dyp17@mail.tsinghua.edu.cn), Tianyu Pang (Tsinghua University, pty17@mails.tsinghua.edu.cn), Xiao Yang (Tsinghua University, yangxiao19@mails.tsinghua.edu.cn), Eric Wong (MIT, wongeric@mit.edu), Zico Kolter (CMU, zkolter@cs.cmu.edu), Yuan He (Alibaba, heyuan.hy@alibaba-inc.com ).