Xiaojie Guo, Amir Alipour-Fanid, Lingfei Wu, Hemant Purohit, Xiang Chen, Kai Zeng and Liang Zhao. Novel ML methods in the computational material and physical sciences. You can optionally export all deadlines to Google Calendar or .ics . 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,
[email protected]), James Holt (Laboratory for Physical Sciences, USA,
[email protected]), Edward Raff (Booz Allen Hamilton, USA,
[email protected]), Ahmad Ridley (National Security Agency), Dennis Ross (MIT Lincoln Laboratory, USA,
[email protected]), Arunesh Sinha (Singapore Management University, Singapore,
[email protected]), Diane Staheli (MIT Lincoln Laboratory, USA,
[email protected]), William W. Streilein (MIT Lincoln Laboratory, USA,
[email protected]), Milind Tambe (Harvard University, USA,
[email protected]), Yevgeniy Vorobeychik (Washington University in Saint Louis, USA,
[email protected]) Allan Wollaber (MIT Lincoln Laboratory, USA,
[email protected]), Supplemental workshop site:http://aics.site/. Deep Generation of Heterogeneous Networks. Disentangled Spatiotemporal Graph Generative Model. Our topics of interest span over prediction, planning, and decision problems for online marketplaces, including but not limited to. Continuous refinement of AI models using active/online learning. 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. Full papers are allocated 20m presentation and 10m discussion. If the admission deadline for international applicants is past, we suggest that you choose another session to begin your studies. 20, 2022: We have announced Call for Nominations: , Jan. 25, 2022: Sponsorship Opportunities is available at, Jan. 6, 2022: Call for KDD Cup Proposals is available at, Dec. 26, 2021: Call for Workshop Proposals is available at, Dec. 26, 2021: Call for Tutorials is available at, Nov. 24, 2021: Those who are interested in serving as a PC, please feel free to fill in this, Nov. 12, 2021: Call for Research Track Papers is available at, Nov. 12, 2021: Call for Applied Data Science Track Papers is available at. We invite the submission of papers with 4-6 pages. As Artificial Intelligence (AI) begins to impact our everyday lives, industry, government, and society with tangible consequences, it becomes increasingly important for a user to understand the reasons and models underlying an AI-enabled systems decisions and recommendations.
KDD - ACM Conferences Shiyu Wang, Xiaojie Guo, Xuanyang Lin, Bo Pan, Yuanqi Du, Yinkai Wang, Yanfang Ye, Ashley Ann Petersen, Austin Leitgeb, Saleh AlKhalifa, Kevin Minbiole, Bill Wuest, Amarda Shehu, Liang Zhao. However, theoreticians and practitioners of AI and Safety are confronted with different levels of safety, different ethical standards and values, and different degrees of liability, that force them to examine a multitude of trade-offs and alternative solutions. How can we characterize or evaluate AI systems according to their potential risks and vulnerabilities? Novel AI-enabled generative models for system design and manufacturing. IEEE Computer (impact factor: 3.564), vo. 2022. Apr 11-14, 2022. Contrast Pattern Mining in Paired Multivariate Time Series of Controlled Driving Behavior Experiment. Qingzhe Li, Liang Zhao, Yi-Ching Lee, Avesta Sassan, and Jessica Lin. In addition to that, we propose a shared task on one of the challenging SDU tasks, i.e., acronym extraction and disambiguation in multiple languages text. [Bests of ICDM], Zheng Zhang and Liang Zhao. Workshop registration is available to AAAI-22 technical registrants at a discounted rate, or separately to workshop only registrants. We invite submission of papers describing innovative research on all aspects of knowledge discovery and data science, ranging from theoretical foundations to novel models and algorithms for data science problems in science, business, medicine, and engineering. The program of the workshop will include invited talks, paper presentations and a panel discussion. Attendance is open to all. "Spatiotemporal Event Forecasting in Social Media." In some programs, spots may be available after the deadlines. All papers must be submitted in PDF format, using the AAAI-22 author kit. Liang Zhao, Ting Hua, Chang-Tien Lu, and Ing-Ray Chen. Ting Hua, Feng Chen, Liang Zhao, Chang-Tien Lu, and Naren Ramakrishnan.
This workshop aims to bring together researchers and practitioners working on different facets of these problems, from diverse backgrounds to share challenges, new directions, recent research results, and lessons from applications. Current rates of progress are insufficient, making it impossible to meet this goal without a technological paradigm shift. The Thirty-Sixth AAAI Conference on Artificial IntelligenceFebruary 28 and March 1, 2022Vancouver Convention CentreVancouver, BC, Canada AAAI is pleased to present the AAAI-22 Workshop Program. Business documents are central to the operation of all organizations, and they come in all shapes and sizes: project reports, planning documents, technical specifications, financial statements, meeting minutes, legal agreements, contracts, resumes, purchase orders, invoices, and many more.
Sigcomm 2022! - Zhiqian Chen, Gaurav Kolhe, Setareh Rafatirad, Chang-Tien Lu, Sai Dinakarrao, Houman Homayoun, Liang Zhao. We also use third-party cookies that help us analyze and understand how you use this website. Fine tuning a neural network is very time consuming and far from optimal. BEAN: Interpretable and Efficient Learning with Biologically-Enhanced Artificial Neuronal Assembly. Information theory has demonstrated great potential to solve the above challenges. Previously published work (or under-review) is acceptable. Workshop Date: Sunday August 14, 2022 EDT. Yuanqi du, George Mason University, USA; Jian Pei, Simon Fraser University, Canada; Charu Aggarwal, IBM Research AI, USA; Philip S. Yu, University of Illinois at Chicago, USA; Xuemin Lin, University of New South Wales, Australia; Jiebo Luo, University of Rochester, USA; Lingfei Wu, JD.Com Silicon Valley Research Center, USA; Yinglong Xia, Facebook AI, USA; Jiliang Tang, Michigan State University, USA; Peng Cui, Tsinghua University, China; William L. Hamilton, McGill University, Canada; Thomas Kipf, University of Amsterdam, Netherlands, Workshop URL:https://deep-learning-graphs.bitbucket.io/dlg-aaai22/. We welcome attendance from individuals who do not have something theyd like to submit but who are interested in RL4ED research. Submissions will be assessed based on their novelty, technical quality, significance of impact, interest, clarity, relevance, and reproducibility. 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. The consideration and experience of adversarial ML from industry and policy making. There is a need for the research community to develop novel solutions for these practical issues. Pengtao Xie (main contact), Assistant Professor, University of California, San Diego,
[email protected] Engineer Ln, San Diego, CA 92161 (Tel)4123206230, Marinka Zitnik, Assistant Professor, Harvard University,
[email protected] 10 Shattuck Street, Boston, MA 02115 (Tel)6503086763, Byron Wallace, Assistant Professor, Northeastern University,
[email protected] 177 Huntington Ave, Boston, MA 02115 (Tel)4135120352, Eric P. Xing, Professor, Carnegie Mellon University,
[email protected] 5000 Forbes Ave, Pittsburgh, PA 15213 (Tel)4122682559, Ramtin Hosseini, PhD Student, University of California, San Diego,
[email protected] (Tel) 3104293825, Ethics and fairness in autonomous systems, Robust robotic design, particularly of autonomous drones and/or vehicles. Inspired by the question, there is a trend in the machine learning community to adopt self-supervised approaches to pre-train deep networks. Integration of non-differentiable optimization models in learning. 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. These datasets can be leveraged to learn individuals behavioral patterns, identify individuals at risk of making sub-optimal or harmful choices, and target them with behavioral interventions to prevent harm or improve well-being. The papers have to be submitted through EasyChair. And with particular focuses but not limited to these application domains: Our program consists of two sessions: academic session and industry session. 2022. In addition, any other work on dialog research is welcome to the general technical track. Template guidelines are here:https://www.acm.org/publications/proceedings-template. [materials][data]. anomaly detection, and ensemble learning. Xiaojie Guo, Yuanqi Du, Liang Zhao. Online Flu Epidemiological Deep Modeling on These approaches make it possible to use a tremendous amount of unlabeled data available on the web to train large networks and solve complicated tasks. 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.
ICDM: International Conference on Data Mining 2024 2023 2022 - WikiCFP KDD 2022 is a dual-track conference that provides distinct programming in research and applied data science. to protect data owner privacy in FL. Causality has received significant interest in ML in recent years in part due to its utility for generalization and robustness. We plan to invite 2-4 keynote speakers from prestigious universities and leading industrial companies. By registering, you agree to receive emails from UdeM. 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 (
[email protected]), USC and Dr. Segev Wasserkrug, (
[email protected]), IBM Research, Prof. Andrea Lodi (
[email protected]), Jacobs Technion-Cornell Institute IIT and Dr. Dharmashankar Subrmanian (
[email protected]), IBM Research. Submission Guidelines VDS@KDD will be hybrid and VDS@VIS will be hybrid (both virtual and in-person) in 2022. The biomedical space has seen a flurry of activity recently, and cyber criminals have amplified their efforts with health-related phishing attacks, spreading misinformation, and intruding into health infrastructure. 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. These challenges are widely studied in enterprise networks, but there are many gaps in research and practice as well as novel problems in other domains. Rabat, Morocco . 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. Abstracts of the following flavors will be sought: (1) research ideas, (2) case studies (or deployed projects), (3) review papers, (4) best practice papers, and (5) lessons learned. We also welcome submissions that are currently under consideration in such archival venues. In recent months/years, major global shifts have occurred across the globe triggered by the Covid pandemic. Supplemental Workshop site:https://rl4ed.org/aaai2022/index.html. 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. Combating fake news is one of the burning societal crises. Table identification and extraction from business documents. The cookies is used to store the user consent for the cookies in the category "Necessary". 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. text, images, and videos). Submissions will be collected via the OpenReview platform; URL forthcoming on the Workshop website. AAAI is pleased to present the AAAI-22 Workshop Program. We accept two types of submissions full research papers no longer than 8 pages (including references) and short/poster papers with 2-4 pages. If it turns out that the architecture is not appropriate for the task, the user must repeatedly adjust the architecture and retrain the network until an acceptable architecture has been obtained. August 14-18, 2022. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22), 2022. This workshop brings together researchers from diverse backgrounds with different perspectives to discuss languages, formalisms and representations that are appropriate for combining learning and reasoning. 4 pages), and position (max. AAAI, specifically, is a great venue for our workshop because its audience spans many ML and AI communities. Please refer and submit through theLearning Network Architecture During Trainingworkshop website, which has more detailed information. [Best Paper Candidate], Minxing Zhang, Dazhou Yu, Yun Li, Liang Zhao. 4701-4707, San Francisco, California, USA, Feb 2017. Papers will be submitted to OpenReview system: Waiting for approval,https://openreview.net/forum?id=6uMNTvU-akO, Workshop Chair:Parisa Kordjamshidi, +1-2174187004,
[email protected], Organizing Committee:Parisa Kordjamshidi (Michigan State University,
[email protected]), Behrouz Babaki (Mila/HEC Montreal,
[email protected]), Sebastijan Dumani (KU Leuven,
[email protected]), Alex Ratner (University of Washington,
[email protected]), Hossein Rajaby Faghihi (Michigan State University,
[email protected]), Hamid Karimian (Michigan State University,
[email protected]), Organizing Committee:Dan Roth (University of Pennsylvania,
[email protected]) and Guy Van Den Broeck (University of California Los Angeles,
[email protected]), Supplemental workshop site:https://clear-workshop.github.io. Adverse event detection by integrating Twitter data and VAERS. Necessary cookies are absolutely essential for the website to function properly. Integration of declarative and procedural domain knowledge in learning. Innovation, Service, and Rising Star Awards. An Invertible Graph Diffusion Model for Source Localization. Some good examples include recommender systems, clustering, graph mining, 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. All the submissions should be anonymous. Papers can be submitted here as an extended abstract (4 pages limit excluding references) or a short paper (6 pages limit excluding references). iCal Outlook robotics Online marketplace is a digital platform that connects buyers (demand) and sellers (supply) and provides exposure opportunities that individual participants would not otherwise have access to. Online. 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. Submissions will be peer reviewed, single-blinded. Deadline: FSE 2023. We have the following keynote speakers confirmed: Andreas Holzinger (Medical Univ. Interesting challenges in this domain include the drastic increase of work from home or remote work, the imbalance between the demand and supply of the job market, the popularity of independent workers, the capability of helping job seekers on their whole job seeking journey and career development, the different objectives and behaviors of all major stakeholders in the ecosystem, e.g. 963-971, Apr-May 2015. "Forecasting Significant Societal Events Using The Embers Streaming Predictive Analytics System." Zheng Chai, Yujing Chen, Ali Anwar, Liang Zhao, Yue Cheng, Huzefa Rangwala. The eligibility criteria for attending the workshop will be registration in the conference/workshop as per AAAI norms. ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 3.089), accepted. in Proceedings of the IEEE International Conference on Data Mining (ICDM 2018), short paper (acceptance rate: 19.9%), Singapore, Dec 2018, accepted. Submit to:https://cmt3.research.microsoft.com/AIBSD2022, Kuan-Chuan Peng (Mitsubishi Electric Research Laboratories,
[email protected]), Ziyan Wu (UII America, Inc.,
[email protected]), Supplemental workshop site:https://aibsdworkshop.github.io/2022/index.html. Algorithms and theories for trustworthy AI models. Document structure and layout learning and recognition. Amir A. Fanid, Monireh Dabaghchian, Ning Wang, Pu Wang, Liang Zhao, Kai Zeng. The positive/negative social impacts and ethical issues related to adversarial ML. Knowledge Discovery and Data Mining. This AAAI workshop aims to bring together researchers from core AI/ML, robotics, sensing, cyber physical systems, agriculture engineering, plant sciences, genetics, and bioinformatics communities to facilitate the increasingly synergistic intersection of AI/ML with agriculture and food systems. 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. Counter-intuitive behaviors of ML models will largely affect the public trust on AI techniques, while a revolution of machine learning/deep learning methods may be an urgent need. Junxiang Wang, Zheng Chai, Yue Cheng, and Liang Zhao. Liang Zhao, Junxiang Wang, and Xiaojie Guo. Jos Miguel Hernndez-Lobato, University of CambridgeProf. 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. Apr 25th through Fri the 29th, 2022. . As deep learning problems become increasingly complex, network sizes must increase and other architectural decisions become critical to success. The workshop will be a one-day meeting and will include a number of technical sessions, a virtual poster session where presenters can discuss their work, with the aim of further fostering collaborations, multiple invited speakers covering crucial challenges for the field of privacy-preserving AI applications, including policy and societal impacts, a tutorial talk, and will conclude with a panel discussion. The 19th International Conference on Data Mining (ICDM 2019), short paper, (acceptance rate: 18.05%), Beijing, China, accepted. Dataset(s) will be provided to hack-a-thon participants. The submission website ishttps://cmt3.research.microsoft.com/TAIH2022. Hua, Ting, Feng Chen, Liang Zhao, Chang-Tien Lu, and Naren Ramakrishnan. Liang Zhao, Jiangzhuo Chen, Feng Chen, Fang Jin, Wei Wang, Chang-Tien Lu, and Naren Ramakrishnan. We invite workshop participants to submit their original contributions following the AAAI format through EasyChair. For further information, please have a look at the call for contributions. in Proceedings of the 24st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018), research track (acceptance rate: 18.4%), London, United Kingdom, Aug 2018, accepted. The main interest of the proposed workshop is to look at a new perspective of system engineering where multiple disciplines such as AI and safety engineering are viewed as a larger whole, while considering ethical and legal issues, in order to build trustable intelligent autonomy. 25-50 attendees including invited speakers and accepted papers. Lyle Unga (University of Pennsylvania,
[email protected]), Rahul Ladhania* (University of Michigan,
[email protected], primary contact), Linnea Gandhi (University of Pennsylvania,
[email protected]), Michael Sobolev (Cornell Tech,
[email protected]), Supplemental workshop site:https://ai4bc.github.io/ai4bc22/, For any questions, please reach out to us at ai4behaviorchange at gmail dot com. Advances in IML promise to make AIs more accessible and controllable, more compatible with the values of their human partners and more trustworthy. Online . Other uncategorized cookies are those that are being analyzed and have not been classified into a category as yet. The AAAI-22 workshop program includes 39 workshops covering a [] References will not count towards the page limit. This workshop aims to bring together FL researchers and practitioners to address the additional security and privacy threats and challenges in FL to make its mass adoption and widespread acceptance in the community. Bioinformatics (Impact Factor: 6.937), accepted, 2022. What is the status of existing approaches in ensuring AI and Machine Learning (ML) safety, and what are the gaps?
The invited speakers, who are well-recognized experts of the field, will give a 30 minute talk. AI System Robustness: participants will consider techniques for detecting and mitigating vulnerabilities at each of the processing stages of an AI system, including: the input stage of sensing and measurement, the data conditioning stage, during training and application of machine learning algorithms, the human-machine teaming stage, and during operational use. "Multi-Task Learning for Spatio-Temporal Event Forecasting." Please refer tohttps://rl4ed.org/aaai2022/index.htmlfor additional information. We invite submissions from participants who can contribute to the theory and applications of modeling complex graph structures such as hypergraphs, multilayer networks, multi-relational graphs, heterogeneous information networks, multi-modal graphs, signed networks, bipartite networks, temporal/dynamic graphs, etc. All submissions will be peer-reviewed.
Invited speakers, panels, poster sessions, and presentations. Junxiang Wang, Fuxun Yu, Xiang Chen, and Liang Zhao. 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. The submission website ishttps://cmt3.research.microsoft.com/PPAI2022. To push forward the research on acronym understanding in scientific text, we propose two shared tasks on acronym extraction (i.e., recognizing acronyms and phrases in text) and disambiguation (i.e., finding the correct expansion for an ambiguous acronym). BERT and GPT in NLP and SimCLR and BYOL in CV are famous examples in this direction. Given the ever-increasing role of the World Wide Web as a source of information in many domains including healthcare, accessing, managing, and analyzing its content has brought new opportunities and challenges. "A Uniform Representation for Trajectory Learning Tasks", 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL 2017), short paper, DOI=10.1145/3139958.3140017, Redondo Beach, CA, USA, Nov 2017. 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. [Best Poster Runner-Up Award].
KDD 2022 : 28th ACM SIGKDD Conference on Knowledge Discovery - WikiCFP