This workshop is positioned as a forum to present and discuss novel research directions in interactive and conversational recommender systems as well as constituent AI technologies that represent the next generation of recommender systems and personalized, conversational assistants. What safety engineering considerations are required to develop safe human-machine interaction? Full papers are allocated 20m presentation and 10m discussion. Electronic submissions to be uploaded at https://easychair.org/conferences/?conf=deepdial20. The workshop will consist of contributed talks, contributed posters, and invited talks on a wide variety of methods and applications. Topics of interest include AI/ML related techniques, methodologies, and experiences for cloud intelligence and DevOps solutions. The First International Workshop on Deep Learning on Graphs: Methodologies and Applications (DLGMA’20) February 8, 2020 New York, NY, USA. Consumer psychology and marketing pursues a different direction to ground affect in its theoretical underpinnings as well as their real-world applications. Program Chair: Jian Zhang (Microsoft, jianzha@microsoft.com)Steering Committee: Ricardo Bianchini (Microsoft Research Redmond), Mike Dahlin (Google), Marcus Fontoura (Microsoft Azure), Ahmed E. Hassan (Queen’s University), Erik Meijer (Facebook), Tao Xie (Peking University), Dongmei Zhang (Microsoft Research Asia ), Yuanyuan Zhou (UCSD), Supplemental workshop site: https://cloudintelligenceworkshop.github.io/. For instance, researchers have also devoted to reducing the monotonous and tedious grading workloads of teaching professionals by building automatic grading systems that are underpinned by effective models from natural language process fields. The AAAI-20 Workshop on Knowledge Discovery from Unstructured Data in Financial Services The 2020 AAAAI Virtual Annual Meeting includes recordings of various sessions originally programmed for the 2020 AAAAI Annual Meeting. AAAI 2020. In conjunction with AAAI-20 on Feb 7, 2020, @ NYC. DSTC, the Dialog System Technology Challenge, has been a premier research competition for dialog systems since its inception in 2013. Papers must between 4-8 pages in the AAAI submission format, with the eighth page containing only references. Such challenges are profound in applications in social attributed networks, natural language processing, inductive logic programming, and program synthesis and analysis. Submission deadline: November 1, 2019Notification: December 4, 2019, Javier Segovia-Aguas (Institut de Robòtica i Informàtica Industrial (IRI), Spain, jsegovia@iri.upc.edu), Siddharth Srivastava (Arizona State University, USA, siddharths@asu.edu), Raquel Fuentetaja (Universidad Carlos III de Madrid, Spain, rfuentet@inf.uc3m.es), Aviv Tamar (Israel Institute for Technology, Israel, aviv.tamar.mail@gmail.com), Anders Jonsson (Universitat Pompeu Fabra, Spain, anders.jonsson@upf.edu), Supplemental workshop site: https://sites.google.com/view/genplan20/. The program of the workshop will include invited speakers, paper presentations, and poster sessions. Workshops will be held Friday and Saturday, February 7-8, 2020 at the New York Hilton Midtown in New York, New York, USA. The manual knowledge discovery and extraction process is usually low in efficiency, error prone, and inconsistent. Furthermore, the rise of Conversational AI-based assistants in the form of Apple’s Siri, Amazon’s Alexa, and the Google Assistant have re-invigorated interest in dialog-based sequential interaction, with a limited degree of personalization. Submission link: https://sites.google.com/dstc.community/dstc8/paper-submission, Workshop Chair: Michel Galley (Microsoft Research AI)Challenge Chair: Seokhwan Kim (Amazon Alexa AI)Publication Chair: Chulaka Gunasekara (IBM Research AI)Publicity Chair: Sungjin Lee (Amazon Alexa AI). In recent years, we have seen examples of general approaches that learn to play these games via self-play reinforcement learning (RL), as first demonstrated in Backgammon. AAAI early registration deadline: Jan 15, 2021. As there is no commonly accepted conference for this work, the workshop we propose will provide a valuable place to discuss, standardize and improve past work of this sub-field. In spite of major AI research focusing on data sources like news, web, and social media, its application to data in professional settings such as legal documents and financial filings, still present huge challenges. At least one author of each accepted submission must be present at the workshop. Participation in each workshop is in the range of 25-65 participants, and participation is usually by invitation from the workshop organizers. Demo TrackThis year the PAIR workshop will include a demo track. Users can easily use, maintain, and troubleshoot their workloads or get efficient support on top of the underlying cloud service offerings.Highly efficient and effective DevOps (Developer and Operations). We solicit original papers in two formats – Technical Paper (6 pages) and project showcase (2 pages) in AAAI format. Important Dates. The fields often use different terminology for the same concepts and, as a result, keeping-up and understanding the results in the other field is cumbersome, thus slowing down research. The papers adhere to the 2-column AAAI format up to 8 pages long with page 8 containing nothing but references, will be considered for review. Knowledge discovery from unstructured data has gained the attention of many practitioners over the past decades. We invite all the teams participated in DSTC8 to submit their work to this workshop. We invite researchers and industrial practitioners to submit their original contributions following the AAAI format through EasyChair (https://easychair.org/conferences/?conf=w3phiai20). This AAAI-2020 workshop aims to bridge the gap between the rapidly growing RPA software industry and the AI research community. This is especially the case for non- traditional online resources such as social networks, blogs, news feed, twitter posts, and online communities with the sheer size and ever-increasing growth and change rate of their data. Although it is still in the early stage, promising results have been achieved in solving various critical problems in education. crowdsourced) and online (e.g. The scope of the workshop includes, but is not limited to, the following areas: The workshop will consist of a welcome session, a keynote talk, full/short paper presentations, demos, and posters. Full technical papers (6-8 pages) describing original research. Proposals of technical talk (up to one-page abstract including short Bio of the main speaker), Position papers for general topics (2-4 pages), and. However, the large-scale and high complexity of cloud services brings great challenges to the industry. Short position papers (2-4 pages) describing initial work or real-world results of applications of AI. As cyber security has rapidly matured, data collection has become easier to instrument, implement, and collect. At AAAI-20, the Reasoning for Complex Question Answering (RCQA) workshop series will feature a special focus on Commonsense Reasoning, and the overall umbrella area of Machine Common Sense (MCS). Slides are also permitted in lieu of video, but greater weight will be given to submissions accompanied by videos. Special issues in flagship academic journals are under consideration to host the extended versions of best/selected papers in the workshop. January 15, 2020: Camera-ready deadline for workshop papers . Dennis M. Ross (MIT Lincoln Laboratory, MA, USA), Diane P. Staheli (MIT Lincoln Laboratory, MA, USA), David R. Martinez (MIT Lincoln Laboratory, MA, USA), William W. Streilein (MIT Lincoln Laboratory, MA, USA), Arunesh Sinha (Singapore Management University, Singapore), Milind Tambe (Harvard University, MA, USA), Supplemental workshop site: http://aics.site/AICS2020. The AAAI author kit can be downloaded from: https://www.aaai.org/Publications/Templates/AuthorKit20.zip. Natural conversation is a hallmark of intelligent systems. This has led to a massive increase of the amount of data that must be analyzed to achieve situational awareness- the scale of which is beyond human capabilities. Until recently, however, research in them has progressed independently with little or no interaction. Modeling highly structured data with time-evolving, multi-relational, and multi-modal nature. AAAI-20 is the Thirty-Fourth AAAI Conference on Artificial Intelligence. Martin Michalowski, Cochair, (University of Minnesota – Twin Cities, martinm@umn.edu); Arash Shaban-Nejad, Cochair, (The University of Tennessee Health Science Center – Oak-Ridge National Lab (UTHSC-ORNL) Center for Biomedical Informatics, ashabann@uthsc.edu); Szymon Wilk, (Poznan University of Technology); David L. Buckeridge, (McGill University); John S. Brownstein, (Boston Children’s Hospital, Harvard University); Byron C. Wallace, (Northeastern University); Michael J. Paul, (The University of Colorado Boulder), Supplemental workshop site: http://w3phiai2020.w3phi.com/. Copyright © 1995–2019 AAAI, Association for the Advancement of Artificial Intelligence, AI for Social Impact Special Track Schedule, AAAI/ACM Conference on AI, Ethics, and Society (AIES 2020), https://aaai.org/Conferences/AAAI-20/ws20/, W1: Affective Content Analysis (AffCon 2020): Interactive Affective Response, W2: Artificial Intelligence for Cyber Security (AICS), W3: Artificial Intelligence for Education, W4: Artificial Intelligence in Team Sports, W5: Artificial Intelligence of Things (AIoT), W6: Artificial Intelligence Safety (SafeAI), W7: Cloud Intelligence: AI/ML for Efficient and Manageable Cloud Services, W8: Deep Learning on Graphs: Methodologies and Applications, W9: Dialog System Technology Challenge (DSTC8), W10: Engineering Dependable and Secure Machine Learning Systems, W14: Intelligent Process Automation — RPA Meets AI, W15: Interactive and Conversational Recommendation Systems (WICRS), W16: Knowledge Discovery from Unstructured Data in Financial Services, W17: Plan, Activity, and Intent Recognition (PAIR), W18: Privacy-Preserving Artificial Intelligence, W19: Reasoning and Learning for Human-Machine Dialogues (DEEP-DIAL20), W20: Reasoning for Complex Question Answering, W22: Reproducibility in AI (RAI 2020) – Future Direction and Reproducibility Challenge. This year we are asking the AI for cyber security community to submit solutions to a challenge problem. There is ever increasing interest and need for innovation in human-technology-interaction as addressed in the context of companion technology. KDF is a one-day workshop. December 04, 2019: Workshop paper submission due (23:59, Pacific Standard Time) December 15, 2019: Workshop paper notifications . According to a recent report (https://urlzs.com/tsvbY), the estimated size of the global sports industry is $1.3 trillion, and has an audience of over 1 billion. How do metrics of capability and generality, and trade-offs with performance affect safety? Machine Common Sense (MCS), taking after the name of a recent DARPA program, has once again become an area of focus. This calls for novel methods and new methodologies and tools to address quality and reliability challenges of ML systems. The focus of the workshop will be on general-purpose representation, reasoning and learning tools for StarAI as well as practical applications. The focus of this workshop is not on evaluating AI systems, but on evaluating the quality of evaluations of AI systems. A large part of this is due to the realization that MCS may be the one of the biggest missing components in the transition of current day narrow AI systems into truly broader general AI systems. The AAAI-20 workshop program includes 23 workshops covering a wide range of topics in artificial intelligence. Submission site: https://cmt3.research.microsoft.com/CIEMCS2020/Submission/Index. Encouraged by this recent interest in interactive and conversational recommender systems, the workshop aspires to bring together AI researchers from recommender systems, machine and reinforcement learning, dialog systems, natural language processing, human computer interaction, psychology and econometrics for a day of research presentations and open discussion about the future of this high impact and highly cross-disciplinary research area. Deep Learning models are at the core of research in Artificial Intelligence research today. Knowledge alignment and integration from heterogeneous data; Data acquisition, augmentation, feature engineering, and analysis for investment and risk management, Automatic knowledge extraction from financial fillings and quality verification, AI systems for relationship extraction and risk assessment from legal documents, Event discovery from alternative data and impact on organization equity price, Coordination in robots and software agents, Plan, activity, intent, or behavior recognition, User modeling on the web and in intelligent user interfaces, Plan recognition and user modeling in marketplaces and e-commerce, Machine learning for plan recognition and user modeling, Monitoring agent conversations (overhearing), Observation-based coordination and collaboration (teamwork), Uncertainty reasoning for plan recognition, Commercial applications of user modeling and plan recognition, Reverse engineering and program recognition, Applications of privacy-preserving AI systems, Architectures and privacy-preserving learning protocols, Differential privacy: theory and applications, Distributed privacy-preserving algorithms, Privacy-preserving algorithms for medical applications, Privacy-preserving algorithms for temporal data, Privacy-preserving test cases and benchmarks, Style, voice and personality in spoken dialogue and written text, Novel Methods for NL Generation for dialogs, Early experiences with implemented dialog systems, Mixed-initiative dialogs where a partner is a combination of agent and human, Domain model acquisition, especially from unstructured text, Planning and reasoning in the context of dialog systems, Handling uncertainty of conversation and data, Ethical issues with learning and reasoning in dialog systems, Corpora, Tools and Methodology for Dialogue Systems. The deadline to submit papers is November 15, 2019. 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. Specifically, the workshop will encourage active participation from researchers in the following communities, and integration thereof: satisfiability, knowledge representation, constraint satisfaction and programming, (inductive) logic programming, graphical models and probabilistic reasoning, statistical learning, relational embeddings, neural-symbolic integration, graph mining and probabilistic databases. The workshop will last span a full day and will include invited talks, oral and poster presentations of submitted work, a panel and open discussion on how to make research results presented at AAAI reproducible. However, the valuable knowledge is always comingled with immense noise and the precision and recall requirements for extracted knowledge to be used in business process are fastidious. We aim to synthesize and highlight recent research on the topic from multiple sub-fields of AI, including those of reinforcement learning, classical planning, planning under uncertainty, as well as learning for planning. Specifically, we intend to extend our community by reaching out to recognition researchers from the machine learning community and encourage them to submit their work to the workshop. The demo track will be chaired by Dr. Mor Vered; questions regarding demos should be referred to mor.vered@unimelb.edu.au. It will also include discussion sessions tuned to the topics presented at the workshop. The workshop is the third edition of the Workshop on Reasoning and Learning for Human-Machine Dialogues. Papers will be selected for oral and/or poster presentation at the workshop. Principally among them are: 1) Determining optimal techniques to improve AI performance given targeted, limited human input, 2) understanding the extent to which the interaction between humans and AI introduces an attack surface for adversarial techniques to influence the performance of both the human and computer systems, 3) establishing and quantifying trust between humans and AI systems, 4) providing explainable AI where humans are required to do ‘last mile’ synthesis of information provided from a black box algorithm, and 5) defining the scope in which an AI system can operate autonomously in distinct cyber security domains while maintaining safety. We cordially welcome researchers, practitioners, and students from academic and industrial communities who are interested in the topics to participate; at least one author of each accepted submission must be present at the workshop. The purpose of the Statistical Relational AI (StarAI) workshop is to bring together researchers and practitioners from three fields: logical (or relational) AI/learning, probabilistic (or statistical) AI/learning and neural approaches for AI/learning with knowledge graphs and other structured data. Internet of Things (IoT) is a disruptive technology that extends data collection to almost everything around us and enables them to react through intelligent data processing. Like other systems, ML systems must meet quality requirements. While classical security vulnerabilities are relevant, ML techniques have additional weaknesses, some already known (e.g., sensitivity to training data manipulation), and some yet to be discovered. The artificial intelligence (AI) and computational linguistics (CL) communities are making strides in identifying and measuring affect from user signals especially in language, while the human-computer interaction (HCI) community independently explores affect through user experience evaluations. If a work is under submission for the main conference as well or for a different conference, it should be written in the title. These problems remain longstanding open problems for Artificial Intelligence (AI). What AI safety considerations and experiences are relevant from industry? Student learning efficiency, similar excitement has been a premier research competition for dialog systems have been published elsewhere the!, demos, and three invited speakers, paper presentations, a paper workshops are day., insightfulness, depth, clarity, and algorithmic game aaai workshop 2020 of representations and algorithms and identify best. 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