The deep learning community must often confront serious time and hardware constraints from suboptimal architectural decisions. GeoInformatica (impact factor: 2.392), 24, 443475 (2020). ISBN: 978-981-16-6053-5. The ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2022 (ACM SIGSPATIAL 2022), poster track, to appear, 2022.
Liang Zhao, Olga Gkountouna, and Dieter Pfoser. SIAM International Conference on Data Mining (SDM 2023) (Acceptance Rate: 27.4%), accepted. Accepted submissions will be notified latest by August 7th, 2022. [Best Paper Award]. DeepGAR: Deep Graph Learning for Analogical Reasoning. There is now a great deal of interest in finding better alternatives to this scheme. 2022. Please note that the KDD Cup workshop will haveno proceedingsand the authors retainfull rightsto submit or post the paper at any other venue. Novel AI-enabled generative models for system design and manufacturing. Novel algorithmic solutions to causal inference or discovery problems using information-theoretic tools or assumptions. 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. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2021), (acceptance rate: 15.4%), accepted. Junxiang Wang and Liang Zhao. Examples of the datasets which may be considered are the DBTex Radiology Mammogram dataset and the Johns Hopkins COVID-19 case reports. Autonomous vehicles can share their detected information (e.g., traffic signs, collision events, etc.) PDF suitable for ArXiv repository (4 to 8 pages). Zhiqian Chen, Gaurav Kolhe, Setareh Rafatirad, Chang-Tien Lu, Sai Dinakarrao, Houman Homayoun, Liang Zhao. For each accepted paper, at least one author must attend the workshop and present the paper. Submissions are limited to a total of 5 pages for initial submission (up to 6 pages for final camera-ready submission), excluding references or supplementary materials, and authors should only rely on the supplementary material to include minor details that do not fit in the 5 pages. 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. : Papers are submitted through the CMT portal for this workshop: Please select the track for your submission in Primary Subject Area and indicate if your submission is a full paper or an extended abstract in Secondary Subject Area. Big Data 2022 December 13-16, 2022. iDev: Enhancing Social Coding Security by Cross-platform User Identification Between GitHub and Stack Overflow. Yujie Fan, Yiming Zhang, Shifu Hou, Lingwei Chen, Yanfang Ye, Chuan Shi, Liang Zhao, Shouhuai Xu. Papers must be between 4-8 pages in the AAAI submission format, with the eighth page containing only references. 5, pp. This cookie is set by GDPR Cookie Consent plugin. The paper submissions must be in pdf format and use the AAAI official templates. Inspired by the question, there is a trend in the machine learning community to adopt self-supervised approaches to pre-train deep networks. Fang Jin, Wei Wang, Liang Zhao, Edward Dougherty, Yang Cao, Chang-Tien Lu, and Naren Ramakrishnan. Workshops will be held Monday and Tuesday, February 28 and March 1, 2022. 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. Proceedings of the IEEE (impact factor: 9.237), vol. and deep learning techniques (e.g. The post-lunch session will feature a second keynote talk, two invited talks. 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. Topics of interest include, but are not limited to: Paper submissions will be in two formats: full paper (8 pages) and position paper (4 pages): The submission website ishttps://easychair.org/conferences/?conf=trase2022. Rabat, Morocco . Technology has transformed over the last few years, turning from futuristic ideas into todays reality. Attendance is open to all; at least one author of each accepted submission must be physically/virtually present at the workshop. Application-specific designs for explainable AI, e.g., healthcare, autonomous driving, etc. We collaborate with Saudi Aramco to use machine learning for simulating oil and water flows, . Reasons include: (1) a lack of certification of AI for security, (2) a lack of formal study of the implications of practical constraints (e.g., power, memory, storage) for AI systems in the cyber domain, (3) known vulnerabilities such as evasion, poisoning attacks, (4) lack of meaningful explanations for security analysts, and (5) lack of analyst trust in AI solutions. This website uses cookies to improve your experience while you navigate through the website. The 21st IEEE International Conference on Data Mining (ICDM 2021), (Acceptance Rate: 9.9%), accepted. 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. 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. FedAT: A High-Performance and Communication-Efficient Federated Learning System with Asynchronous Tiers. SIGKDD Explorations, Vol. Sathappan Muthiah, Patrick Butler, Rupinder Paul Khandpur, Parang Saraf, Nathan Self, Alla Rozovskaya, Liang Zhao, Jose Cadena et al.
Prediction-time Efficient Classification Using Feature Computational Dependencies. Different from machine learning, Knowledge Discovery and Data Mining (KDD) is considered to be more practical and more related with real-world applications. 2022. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. 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. KDD 2022 | Washington DC, U.S. SIGKDD CONFERENCE Latest News Aug 12, 2022: Please check out the proceedings access information.
KDD 2022 | Washington DC, U.S. The submitted papers written in English must be in PDF format according to the AAAI camera ready style. Martin Michalowski, PhD, FAMIA (Co-chair), University of Minnesota; Arash Shaban-Nejad, PhD, MPH (Co-chair), The University of Tennessee Health Science Center Oak-Ridge National Lab (UTHSC-ORNL) Center for Biomedical Informatics; Simone Bianco, PhD (Co-chair), IBM Almaden Research Center; Szymon Wilk, PhD, Poznan University of Technology; David L. Buckeridge, MD, PhD, McGill University; John S. Brownstein, PhD, Boston Childrens Hospital, Workshop URL:http://w3phiai2022.w3phi.com/. After the submission deadline, the names and order of authors cannot be changed. Papers will be submitted electronically using Easychair. 2085-2094, Aug 2016. Small Molecule Generation via Disentangled Representation Learning. Share. Thank you for all your contributions, our, Paper submission deadline is now extended to. Chen Ling, Carl Yang, Liang Zhao. 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. The eligibility criteria for attending the workshop will be registration in the conference/workshop as per AAAI norms. Short papers 10m presentation and 5m discussion. algorithms applied to the above topics: deep learning, reinforcement learning, multi-armed bandits, causal inference, mathematical programming, and stochastic optimization. 4 pages) papers describing research at the intersection of AI and science/engineering domains including chemistry, physics, power systems, materials, catalysis, health sciences, computing systems design and optimization, epidemiology, agriculture, transportation, earth and environmental sciences, genomics and bioinformatics, civil and mechanical engineering etc. Semantic understanding of business documents. Industry-wide reports highlight large-scale remediation efforts to fix the failures and performance issues. Continuous V&V and predictability of AI safety properties, Runtime monitoring and (self-)adaptation of AI safety, Accountability, responsibility and liability of AI-based systems, Avoiding negative side effects in AI-based systems, Role and effectiveness of oversight: corrigibility and interruptibility, Loss of values and the catastrophic forgetting problem, Confidence, self-esteem and the distributional shift problem, Safety of AGI systems and the role of generality, Self-explanation, self-criticism and the transparency problem, Regulating AI-based systems: safety standards and certification, Human-in-the-loop and the scalable oversight problem, Experiences in AI-based safety-critical systems, including industrial processes, health, automotive systems, robotics, critical infrastructures, among others. SDU is expected to host 50-60 attendees. 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. 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. Nowadays, machine learning solutions are widely deployed. Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment. Xuchao Zhang, Liang Zhao, Arnold Boedihardjo, Chang-Tien Lu. Prof. Max Welling, University of Amsterdam and Microsoft ResearchProf. What is the status of existing approaches in ensuring AI and Machine Learning (ML) safety, and what are the gaps? 19-25, 2016. At least one author of each accepted submission must register and present the paper at the workshop. 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). ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 3.089), accepted. KDD 2023 KDD '23 ​ ​ ​ August 6-10, 2023. We hope this will help bring the communities of data mining and visualization more closely connected. We invite a long research paper (8 pages) and a demo paper (4 pages) (including references). 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. In the coronavirus era, requiring many schools to move to online learning, the ability to give feedback at scale could provide needed support to teachers. The reproducibility papers include a clarification phase: Deadlines refer to 23:59 (11:59pm) in the AoE (Anywhere on Earth) time zone. Xuchao Zhang, Shuo Lei, Liang Zhao, Arnold Boedihardjo, Chang-Tien Lu, "Robust Regression via Heuristic Corruption Thresholding and Its Adaptive Estimation Variation", ACM Transactions on Knowledge Discovery from Data (TKDD), (impact factor: 1.98), accepted, 2019. 1-39, November 2016. LOG 2022 LOG '22 . 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. URL: https://sites.google.com/view/kdd22onlinemarketplaces Call For Papers (Submission deadline: June3, 2022) This workshop on Trustworthy Autonomous Systems Engineering (TRASE) offers an opportunity to highlight state of the art research in trustworthy autonomous systems, as well as provide a vision for future foundational and applied advances in this critical area at the intersection of AI and Cyber-Physical Systems. Poster/short/position papers: We encourage participants to submit preliminary but interesting ideas that have not been published before as short papers. 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. All the submissions must follow the AAAI-22 formatting guidelines, camera-ready style. ACM Transactions on Spatial Algorithms and Systems (TSAS), 5, 3, Article 19 (September 2019), 28 pages. It does not store any personal data. Qingzhe Li, Jessica Lin, Liang Zhao and Huzefa Rangwala. Integration of neuro and symbolic approaches. Apr 25th through Fri the 29th, 2022. . As far as we know, we are the first workshop to focus on practical deep learning in the wild for AI, which is of great significance. Deep Classifier Cascades for Open World Recognition. The advances in web science and technology for data management, integration, mining, classification, filtering, and visualization has given rise to a variety of applications representing real-time data on epidemics. Topics of interest include but are not limited to: Acronyms, i.e., short forms of long phrases, are common in scientific writing. 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.
MLG 2022 - 17th International Workshop on Mining and Learning with Graphs We invite researchers to submit either full-length research papers (8 pages) or extended abstracts (2 pages) describing novel contributions and preliminary results, respectively, to the topics above; a more extensive list of topics is available on the Workshop website. The Thirty-Sixth Annual Conference on Neural Information Processing Systems (NeurIPS 2022), (Acceptance Rate: 25.6%), to appear, 2022. 40, no. 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. This date takes priority over those shown below and could be extended for some programs. the 56th Design Automation Conference (DAC 2019), accepted, (acceptance rate: 20%), Las Vegas, US, 2019. At AAAI 2021, we successfully organized this workshop (https://taih20.github.io/). 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. Integration of non-differentiable optimization models in learning. The format is the standard double-column AAAI Proceedings Style. Theoretical or empirical studies focusing on understanding why self-supervision methods work for speech and audio. Submission link:https://easychair.org/cfp/raisa-2022, William Streilein, MIT Lincoln Laboratory, 244 Wood St., Lexington, MA, 02420, (781) 981-7200, wws@ll.mit.edu, Olivia Brown (MIT Lincoln Laboratory, Olivia.Brown@ll.mit.edu), Rajmonda Caceres (MIT Lincoln Laboratory, Rajmonda.Caceres@ll.mit.edu), Tina Eliassi-Rad (Northeastern University, teliassirad@northeastern.edu), David Martinez (MIT Lincoln Laboratory, dmartinez@ll.mit.edu), Sanjeev Mohindra (MIT Lincoln Laboratory, smohindra@ll.mit.edu), Elham Tabassi (National Institute of Standards and Technology, elham.tabassi@nist.gov), Workshop URL:https://sites.google.com/view/raisa-2022/. It highlights the importance of declarative languages that enable such integration for covering multiple formalisms at a high-level and points to the need for building a new generation of ML tools to help domain experts in designing complex models where they can declare their knowledge about the domain and use data-driven learning models based on various underlying formalisms. "Automatic Targeted-Domain Spatiotemporal Event Detection in Twitter." 689-698, Barcelona, Spain, Dec 2016. The AAAI template https://aaai.org/Conferences/AAAI-22/aaai22call/ should be used for all submissions. 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). We invite submission of papers describing innovative research and applications around the following topics. Event Prediction in the Big Data Era: A Systematic Survey. arXiv preprint arXiv:2002.11867 (2021), Lingfei Wu, Peng Cui, Jian Pei, Liang Zhao. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22), 2022. Universit de MontralOffice of Admissions and RecruitmentC. Virtual . Yuyang Gao, Tong Sun, Guangji Bai, Siyi Gu, Sungsoo Hong, and Liang Zhao. We invite the submission of papers with 4-6 pages. 1, Sec. In addition, broad deployment of ML software in networked systems inevitably exposes ML software to attacks. 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. We welcome the submissions in the following two formats: The submissions should adhere to theAAAI paper guidelines. The impact of robustness assurance on other AI ethics principles: RAISA will also explore aspects related to ethical AI that overlap and interact with robustness concerns, including security, fairness, privacy, and explainability. This manual extraction process is usually inefficient, error-prone, and inconsistent. It is a forum to bring attention towards collecting, measuring, managing, mining, and understanding multimodal disinformation, misinformation, and malinformation data from social media. We are interested in a broad range of topics, both foundational and applied. We will accept the extended abstracts of the relevant and recently published work too. "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. and facilitate discussions and collaborations in developing trustworthy AI methods that are reliable and more acceptable to physicians.
Conference Management Toolkit - Login No supplement is allowed for extended abstracts. Self-supervised learning approaches involving the interaction of speech/audio and other modalities. Additional advantages are possible, including decreased computational resources to solve a problem, reduced time for the network to make predictions, reduced requirements for training set size, and avoiding catastrophic forgetting. Spatio-temporal Event Forecasting Using Incremental Multi-source Feature Learning. In particular, we encourage papers covering late-breaking results and work-in-progress research. The bottleneck to discovery is now our ability to analyze and make sense of heterogeneous, noisy, streaming, and often massive datasets. 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. 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. Integration of Deep learning and Constraint programming. 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. 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.