The role of adjacent fields of study (e.g, computational social science) in mitigating issues of bias and trust in AI. We hope to build upon that success. Well also host a competition on adversarial ML along with this workshop. Information-theoretic approaches provide a novel set of tools that can expand the scope of classical approaches to causal inference and discovery problems in a variety of applications. Guangji Bai, Chen Ling, Yuyang Gao, Liang Zhao. Everyone in the Top-10 leaderboard submissions will have a guaranteed opportunity for an in-person oral/poster presentation. in Proceedings of the IEEE International Conference on Data Mining (ICDM 2016), regular paper, (acceptance rate: 8.5%), pp. ), 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. The review process is double-blind, and we follow the Conflict of Interest Policy for ACM Publications. December, 09-12, 2022. [materials][data]. Complex systems are often characterized by several components that interact in multiple ways among each other. Liang Zhao, Feng Chen, and Yanfang Ye. November 11-17, 2023. arXiv preprint arXiv:2207.09542 (2022). You signed in with another tab or window. 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. This proposed workshop will build upon successes and learnings from last years successful AI for Behavior Change workshop, and will focus on on advances in AI and ML that aim to (1) design and target optimal interventions; (2) explore bias and equity in the context of decision-making and (3) exploit datasets in domains spanning mobile health, social media use, electronic health records, college attendance records, fitness apps, etc. algorithms applied to the above topics: deep learning, reinforcement learning, multi-armed bandits, causal inference, mathematical programming, and stochastic optimization. The positive/negative social impacts and ethical issues related to adversarial ML. Papers will be peer-reviewed and selected for spotlight and/or poster presentation at the workshop. Invited speakers, committee members, authors of the research paper, and the participants of the shared task are invited to attend. 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. Submissions will undergo double blind review. July 21: Clarified that the workshop this year will be held in-person. This workshop aims to bring together researchers from industry and academia and from different disciplines in AI and surrounding areas to explore challenges and innovations in IML. We expect 50-65 people in the workshop. Recently developed tools and cutting-edge methodologies coming from the theory of optimal transport have proved to be particularly successful for these tasks. Winter. 5, pp. Please refer and submit through theLearning Network Architecture During Trainingworkshop website, which has more detailed information. This workshop has no archival proceedings. KDD 2022 KDD . Junxiang Wang, Hongyi Li, Zheng Chai, Yongchao Wang, Yue Cheng, 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. Negar Etemadyrad, Qingzhe Li, Liang Zhao. Please note as per the KDD Call for Workshop Proposals: Note: Workshop papers will not be archived in the ACM Digital Library. How to Write and Publish Research Papers for the Premier Forums in Knowledge & Data Engineering: While the research community is converging on robust solutions for individual AI models in specific scenarios, the problem of evaluating and assuring the robustness of an AI system across its entire life cycle is much more complex. Guangji Bai and Liang Zhao. The desired LENGTH of the workshop: Full-day (~8 hours). "Multi-resolution Spatial Event Forecasting in Social Media." 11-13. Information extraction from text and semi-structured documents. 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. Junxiang Wang, Liang Zhao, Yanfang Ye, and Yuji Zhang. Disentangled Dynamic Graph Deep Generation, SIAM International Conference on Data Mining (SDM 2021), (acceptance rate: 21.3%), accepted. Furthermore, leveraging AI to connect disparate social networks amongst teachers \\cite{karimi2020towards}, we may be able to provide greater resources for their planning, which have been shown to significantly affect students achievement. This AAAI-22 workshop on AI for Decision Optimization (AI4DO) will explore how AI can be used to significantly simplify the creation of efficient production level optimization models, thereby enabling their much wider application and resulting business values.The desired outcome of this workshop is to drive forward research and seed collaborations in this area by bringing together machine learning and decision-making from the lens of both dynamic and static optimization models. The workshop will include original contributions on theory, methods, systems, and applications of data mining, machine learning, databases, network theory, natural language processing, knowledge representation, artificial intelligence, semantic web, and big data analytics in web-based healthcare applications, with a focus on applications in population and personalized health. Jos Miguel Hernndez-Lobato, University of CambridgeProf. Yuyang Gao, Tong Sun, Rishab Bhatt, Dazhou Yu, Sungsoo Hong, and Liang Zhao. 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. Please specify the length of the workshop (1-day, 1.5-day, 2-day, or half-day. As deep learning problems become increasingly complex, network sizes must increase and other architectural decisions become critical to success. Submitted technical papers can be up to 4 pages long (excluding references and appendices). 2022. . IEEE Transactions on Neural Networks and Learning Systems (TNNLS), (Impact Factor: 14.255), accepted. Xuchao Zhang, Liang Zhao, Arnold Boedihardjo, Chang-Tien Lu, and Naren Ramakrishnan. What techniques and approaches can be used to detect and effectively manage similar scenarios in the future? Rabat, Morocco . ICONF "How events unfold: spatiotemporal mining in social media." Xiaojie Guo and Liang Zhao. 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. The topics of interest include but are not limited to: Theoretical and Computational Optimal Transport: Optimal Transport-Driven Machine Learning: Optimal Transport-Based Structured Data Modeling: The full-day workshop will start with two long talks and one short talk in the morning. Spatio-temporal Event Forecasting Using Incremental Multi-source Feature Learning. 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. ACM Transactions on Spatial Algorithms and Systems (TSAS), accepted. Linear Time Complexity Time Series Clustering with Symbolic Pattern Forest. 11, 2022: We have posted the list of accepted Workshops at, Apr. IEEE Transactions on Information Forensics and Security (TIFS), (impact factor: 7.178), accepted. The industry session will emphasize practical industrial product developments using GNNs. SIGMOD 2022 adheres to the ACM Policy Against Harassment. Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs. A final tribute was paid on Saturday to former Coalition Avenir Qubec (CAQ) minister Nadine Girault, who died of lung cancer last month at age 63 . Respect official deadlines - Universit de Montral This manual extraction process is usually inefficient, error-prone, and inconsistent. Attendance is open to all, subject to any room occupancy constraints. Notable examples include the information bottleneck (IB) approach on the explanation of the generalization behavior of DNNs and the information maximization principle in visual representation learning. In Proceedings of the 20th International Conference on Data Mining (ICDM 2020), (acceptance rate: 9.8%), November 17-20, 2020, Virtual Event, Sorrento, Italy, 10 pages. Ranking, acceptance rate, deadline, and publication tips. SIAM International Conference on Data Mining (SDM 2023) (Acceptance Rate: 27.4%), accepted. The following paper categories are welcome: Submission site:https://sites.google.com/view/eaai-ws-2022/call, Silvia Tulli (Dept. Jan 13, 2022: Notification. It is one of the key bottlenecks for financial services companies to improve their operating productivity. Shuo Lei, Xuchao Zhang, Liang Zhao, Arnold P. Boedihardjo, Chang-Tien Lu. in Proceedings of the IEEE International Conference on Data Mining (ICDM 2015), regular paper (acceptance rate: 8.4%), Atlantic City, NJ, pp. 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. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2021), (acceptance rate: 15.4%), accepted. ; (2) Deep Learning (DL) approaches that can exploit large datasets, particularly Graph Neural Networks (GNNs) and Deep Reinforcement Learning (DRL); (3) End-to-end learning methodologies that mend the gap between ML model training and downstream optimization problems that use ML predictions as inputs; (4) Datasets and benchmark libraries that enable ML approaches for a particular OR application or challenging combinatorial problems. The workshop attracted about 100 attendees. Integration of AI-based approaches with engineering prototyping and manufacturing. Ourprevious workshop at AAAI-21generated significant interest from the community. In this workshop, we want to explore ways to bridge short-term with long-term issues, idealistic with pragmatic solutions, operational with policy issues, and industry with academia, to build, evaluate, deploy, operate and maintain AI-based systems that are demonstrably safe. 2022. Zheng Zhang and Liang Zhao. The cookie is used to store the user consent for the cookies in the category "Analytics". The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022) (Acceptance Rate: 14.99%), accepted, 2022. TG-GAN: Continuous-time Temporal Graph Deep Generative Models with Time-Validity Constraints. Shi, Y., Deng, M., Yang, X., Liu, Q., Zhao, L., & Lu, C. T. "A Framework for Discovering Evolving Domain Related Spatio-Temporal Patterns in Twitter." KDD 2022. Prediction-time Efficient Classification Using Feature Computational Dependencies. The growing popularity of NAS methods demonstrates the communitys hunger for better ways of choosing or evolving network architectures that are well-matched to the problem at hand. This workshop will follow a dual-track format. "Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning." The program of the workshop will include invited talks, paper presentations and a panel discussion. Information extraction and information retrieval for scientific documents; Question answering and question generation for scholarly documents; Word sense disambiguation, acronym identification and expansion, and definition extraction; Document summarization, text mining, document topic classification, and machine reading comprehension for scientific documents; Graph analysis applications including knowledge graph construction and representation, graph reasoning and query knowledge graphs; Biomedical image processing, scientific image plagiarism detection, and data visualization; Code/Pseudo-code generation from text and im-age/diagram captioning, New language understanding resources such as new syn-tactic/semantic parsers, language models or techniques to encode scholarly text; Survey or analysis papers on scientific document under-standing and new tasks and challenges related to each scientific domain; Factuality, data verification, and anti-science detection. SIGSPATIAL Special (invited paper), vo. text, images, and videos). This thread already has a best answer. Junxiang Wang, Junji Jiang, Liang Zhao. Analytical cookies are used to understand how visitors interact with the website. Full papers are allocated 20m presentation and 10m discussion. 4. Theoretical or empirical studies focusing on understanding why self-supervision methods work for speech and audio. Xiaojie Guo, Liang Zhao, Cameron Nowzari, Setareh Rafatirad, Houman Homayoun, and Sai Dinakarrao. Pattern Recognition, (impact factor: 7.196),112 (2021): 107711. Submissions will be assessed based on their novelty, technical quality, significance of impact, interest, clarity, relevance, and reproducibility. The 19th International Conference on Data Mining (ICDM 2019), short paper, (acceptance rate: 18.05%), Beijing, China, accepted. SIGKDD Explorations, Vol. Integration of neuro and symbolic approaches. Ting Hua, Feng Chen, Liang Zhao, Chang-Tien Lu, and Naren Ramakrishnan. Rupinder Khandpur, Taoran Ji, Yue Ning, Liang Zhao, Chang-Tien Lu, Erik Smith, Christopher Adams and Naren Ramakrishnan. Continuous refinement of AI models using active/online learning. Workshop registration is available to AAAI-22 technical registrants at a discounted rate, or separately to workshop only registrants. Liming Zhang, Liang Zhao, Dieter Pfoser, Shan Qin and Chen Ling. All papers must be submitted in PDF format, using the AAAI-22 author kit. Amitava Das (Wipro AI Labs; amitava.santu@gmail.com), Workshop Chairs: Amitava Das (Wipro AI Labs) [India], Amit Sheth (University of South Carolina) [USA], Tanmoy Chakraborty (IIIT Delhi) [India], Asif Ekbal (IIT Patna) [India], Chaitanya Ahuja (CMU) [USA], Parth Patwa (UCLA) [USA], Parul Chopra (CMU) [USA], Amrit Bhaskar (ASU) [USA], Nethra Gunti (IIIT Sri City) [USA], Sathyanarayanan R. (IIIT Sri City) [India], Shreyash Mishra (IIIT Sri City) [India], S. Suryavardan (IIIT Sri City) [India], Vishal Pallagani (University of South Carolina), Supplemental workshop site:https://aiisc.ai/defactify/. In the Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), (acceptance rate: 17.9%), accepted, Macao, China, Aug 2019. Expected attendance is 40-50 people. Hosein Mohammadi Makrani, Farnoud Farahmand, Hossein Sayadi, Sara Bondi, Sai Manoj Pudukotai Dinakarrao, Liang Zhao, Avesta Sasan, Houman Homayoun, and Setareh Rafatirad,. All the submissions must follow the AAAI-22 formatting guidelines, camera-ready style. This topic also encompasses techniques that augment or alter the network as the network is trained. BEAN: Interpretable and Efficient Learning with Biologically-Enhanced Artificial Neuronal Assembly. in Proceedings of the IEEE International Conference on Data Mining (ICDM 2018), regular paper (acceptance rate: 8.9%), Singapore, Dec 2018, accepted. The adversarial ML could also result in potential data privacy and ethical issues when deploying ML techniques in real-world applications. Recent years have witnessed growing interest in human and AI systems with the increasing realisation that machines can indeed meet objectives specified but the real question becomes have they been given the right objectives. Thirty-fourth AAAI Conference on Artificial Intelligence (AAAI 2021), (acceptance rate: 21.0%), accepted. We hope this will help bring the communities of data mining and visualization more closely connected. Handwritten recognition in business documents. 25, 2022: We have announced Call for Nominations: , Mar. AI Conference Deadlines These cookies ensure basic functionalities and security features of the website, anonymously. Deep Classifier Cascades for Open World Recognition. Oral Paper (Top 5% among the accepted papers). We allow papers that are concurrently submitted to or currently under review at other conferences or venues. Detailed information could be found on the website of the workshop. Taking the pulse of COVID-19: a spatiotemporal perspective. We invite submissions of technical papers up to 7 pages excluding references and appendices. Papers will be peer-reviewed and selected for oral and/or poster presentation at the workshop. We expect ~60 attendees. 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. "Forecasting Significant Societal Events Using The Embers Streaming Predictive Analytics System." Each accepted paper presentation will be allocated between 15 and 20 minutes. 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. Yuanqi Du, Xiaojie Guo, Amarda Shehu, Liang Zhao. These abrupt changes impacted the environmental assumptions used by AI/ML systems and their corresponding input data patterns. CoRL 2023 97 days 17h 29m 15s November 06-09, 2023. Property Controllable Variational Autoencoder via Invertible Mutual Dependence. 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. ITCI22 will be a one-day workshop. Attendance is open to all registered participants. CFP - EasyChair Liang Zhao, Feng Chen, Jing Dai, Ting Hua, Chang-Tien Lu, and Naren Ramakrishnan. Topics of interest include, but are not limited to: One day, comprising keynote, paper presentations and panel sessions. 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. What AI safety considerations and experiences are relevant from industry? GeoInformatica (impact factor: 2.392), 24, 443475 (2020). Babies learn their first language through listening, talking, and interacting with adults. The workshop also welcomes participants of SUPERB and Zero Speech challenge to submit their results. 9, no. The 35th Conference on Neural Information Processing Systems (NeurIPS 2021), Datasets and Benchmarks Track, accepted. 2022. Can AI achieve the same goal without much low-level supervision? Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. 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. At AAAI 2021, we successfully organized this workshop (https://taih20.github.io/). Each paper will be reviewed by three reviewers in double-blind. a concise checklist by Prof. Eamonn Keogh (UC Riverside). Securing personal information, genomics, and intellectual property, Adversarial attacks and defenses on biomedical datasets, Detecting and preventing spread of misinformation, Usable security and privacy for digital health information, Phishing and other attacks using health information, Novel use of biometrics to enhance security, Machine learning (including RL) security and resiliency, Automation of data labeling and ML techniques, Operational and commercial applications of AI, Explanations of security decisions and vulnerability of explanations. "GA-based principal component selection for production performance estimation in mineral processing." In recent years, various information theoretic principles have also been applied to different deep learning related AI applications in fruitful and unorthodox ways. We invite workshop participants to submit their original contributions following the AAAI format through EasyChair. Feature Constrained Multi-Task Learnings for Event Forecasting in Social Media." Accepted papers will not be archived, and we explicitly allow papers that are concurrently submitted to, currently under review at, or recently accepted in other conferences / venues. 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.