| W01 | Jan 7, 9am – 2pm JST Jan 8, 9am – 2pm JST | Principle and Practice of Data and Knowledge Acquisition Workshop (PKAW2020) | Series of PKAW (Principle and Practice of Data and Knowledge Acquisition Workshop) workshop has long been an integral part of PRICAI over nearly two decades.The purpose of this workshop is to provide a place for intensive discussion on all aspects of knowledge acquisition. Multidisciplinary approach for knowledge acquisition is the topic of interests that includes data driven approach based on machine learning etc. as well as those to make human experts’ implicit knowledge machine executable. In this respect, PKAW2020 calls for a wide range of research papers concerning knowledge acquisition. We also invite submissions concerning data acquisition and representation. All the accepted papers are published as the post proceedings of Lecture Notes in Computer Science by Springer. PKAW2020 is sponsored by SIG-KBS, a special interest group of Knowledge Based System of The Japanese Society of Artificial Intelligence. | |
| W02 | Jan 7, 5pm – 10pm JST Jan 8, 5pm – 10pm JST | 8th Artificial Intelligence for Knowledge Management (AI4KM) | The objective of this multidisciplinary session is to gather both researchers and practitioners to discuss experiences in various AI approaches and techniques applied to knowledge management and innovation. It includes methodological, technical and organizational aspects of AI used for knowledge management and feedback from KM applications using AI. Among the topics to address are: knowledge management methods, models, decision support systems, management advisors, virtual training, serious games, applications of machine learning to support innovation and eco-innovation, knowledge visualization for improving the creativity and human-machine interfaces, image mining making links between data and images ex bio-detection are good examples of multidisciplinary applications as well as knowledge management applied to global security and sustainability. | |
| W03 | Jan 8, 9am – 2pm JST | Disease Computational Modeling | Many common chronic diseases remain mysterious as to how they manifest themselves and how they progress. The Disease Computational Modeling (DCM) workshop aims at providing a research forum where AI based computational methods are presented and discussed to further our understanding of how diseases develop over time. This calls for methods that can discover biological association for disease genotyping; clinical representation for disease phenotyping; probabilistic graph models for disease progression; disease-symptom models for screening or early diagnosis; disease-drug models for optimal care patterns; embedding of medical concepts w./w.o. patient visits; or other novel disease computational models with the potential if injecting meaningful insights in healthcare. | |
| W04 | Jan 7, 9am – 2pm JST | 5th International Workshop on Biomedical Informatics with Optimization and Machine learning (BOOM 2020) | The BOOM workshop aims at catalyzing synergies among biomedical informatics, artificial intelligence, machine learning, and optimization. This workshop is targeting an audience of applied mathematicians, computer scientists, industrial engineers, bioinformaticians, computational biologists, clinicians, and healthcare researchers who are interested in exploring the emerging and fascinating interdisciplinary topics. | |
| W05 | Jan 7, 9am – 2pm JST Jan 8, 9am – 2pm JST | 1st Workshop on Artificial Intelligence for Function, Disability, and Health (AI4Function) | The First Workshop on Artificial Intelligence for Function, Disability, and Health (AI4Function 2020) addresses the role of Artificial Intelligence (AI) technologies in collecting and analyzing information on function and disability. Function, as the lived experience of health, describes physical and mental wellness at the whole-person level, and is a key indicator for global health. Better information on function is critical in light of global demographic shifts and increases in chronic conditions, and AI technologies are well-poised to address this need. This workshop brings together members of the AI and health communities interested in function to chart the course of this area of research. |  |
| W06 | Jan 7, 9am – 2pm JST Jan 7, 5pm – 10pm JST | Joint Workshop on Human Brain and Artificial Intelligence (HBAI 2020) | The quest for brain research (BR) is to uncover the nature of brain cognition, consciousness, and intelligence. Artificial Intelligence (AI) is committed to realizing machine-borne intelligence. The development of these two fields is undergoing a continuous trend of convergence. The Human Brain and Artificial Intelligence (HBAI) aim at bringing together active researchers and practitioners in the frontiers of AI and human BR for the presentation of original research results. It provides an opportunity for the exchange and dissemination of innovative research ideas relevant to both fields. HBAI will contribute to answering the following two questions: How can AI techniques help to human brain research (brain computing)? And, how can human brain research inspire the study of AI (brain-inspired computing)? The discussion on the workshop will clearly be great helpful to brain and cognitive science, neural computation and artificial general intelligence, brain-machine interface, brain science+, AI, and their applications. | |
| W08 | Jan 7, 9am – 2pm JST Jan 7, 5pm – 10pm JST | 4th Workshop on Artificial Intelligence in Affective Computing (AffComp) | In recent years, research in affective computing has led to advances across multiple modes of affective expression: affective speech recognition, sentiment understanding and natural language processing in context, new models for facial expression classification, and novel multi-modal data collection and applied machine learning strategies beyond personal computing. Our workshop will focus on the convergence of methodologies that contribute to detecting emotional and psychometric patterns: machine learning algorithms, wearables, Internet of Things (IoT), emotion elicitation strategies, creating affect-related datasets and methodologies for learning while preserving privacy. We also invite papers that help us understand the limitations of current methods of affective algorithms and can help inform regulatory policy around affective computing. Relevant active research areas of include: facial affect and usability; affective content; social influence; non-human affect; affective bias, safe AI, and ethical factors; deep learning from biometric, video, and other affective data; medical devices and fog/edge computing in affect. | |
| W09 | Jan 8, 9am – 2pm JST Jan 8, 5pm – 10pm JST | AI for Social Good | This workshop will explore how artificial intelligence can contribute to solving social problems. For example, what role can AI play in promoting health, access to opportunity, and sustainable development? How can AI initiatives be deployed in an ethical, inclusive, and accountable manner? To address such questions, this workshop will bring together researchers and practitioners across artificial intelligence and a range of application domains. The objective is to share the current state of research and practice, explore directions for future work, and create opportunities for collaboration. The workshop will feature a mix of invited talks, contributed talks, and posters. Submissions spanning the full range of theoretical and applied work are encouraged. | |
| W10 | Jan 7, 9am – 2pm JST | 2nd AI-based Multimodal Analytics for Understanding Human Learning in Real-World Educational Contexts (AIMA4Edu) | Human learning is a complex interactive and iterative process that takes place at a very fine grained level. However, our ability to understand and support this fascinating latent learning process is often limited by what we can perceive and how we can measure. Recent advances of sensing technology and accompanying techniques for processing multimodal data, which manifest the psychological as well physiological processes during the human learning process, give us a new opportunity to look at this classical problem with a new pair of lens. The emerging new type of data includes, but not limited to, student’s physiological signals such as EKG or EEG waveforms, students’ speech, facial expressions and postures, within the context of particular learning activities. In this AIMA4EDU workshop, we expand topic areas to include nascent methodological areas and work beginning to apply multimodal data and AI to support learners. | |
| W11 | Jan 7, 5pm – 10pm JST | 4th International Workshop on Multi-Agent Path Finding | The Multi-agent Path Finding Problem (MAPF) takes as input a team of agents that need to plan collision-free paths from their current locations to their target locations. MAPF has been shown to be NP-hard for several different cost functions, yet one must find high-quality collision-free paths for the agents quickly. Recent years have seen a significant rise of different formulations of the MAPF problem and diverse appreaches with varying complexities, properties and applications. This workshop aims to gather the MAPF community in order to present new and ongoing research, discuss issues that pertain to high-quality research and crass-fertilize ideas between different groups. | |
| W14 | Jan 7, 5pm – 10pm JST Jan 8, 5pm – 10pm JST | Data Science Meets Optimization (DSO) | This workshop on the close relationship and interplay between data science and optimisation continues on the DSO@IJCAI2019 workshop at the International Joint Conference on Artificial Intelligence 2019 in Macao as well as on the DSO@IJCAI-ECAI workshop in 2018 at FAIM in Stockholm. Invited are studies on how techniques from combinatorial optimization and mathematical programming can be enforced by learning from historical data and on how such advanced techniques can contribute to machine learning and data mining. The DSO workshop is closely related to the DSO working group of The Association of European Operational Research Societies (EURO) with yearly streams and workshops at major conferences such as EURO 2018 in Valencia, EURO 2019 in Dublin, IFORS 2017 in Quebec, CPAIOR 2017 in Padua, CEC 2017 in San Sebastian. | |
| W15 | Jan 7, 5pm – 10pm JST | Monte Carlo Search 2020 | Monte Carlo Search is a family of general search algorithms that have many applications in different domains. It is the state of the art in perfect and imperfect information games. Other applications include the RNA inverse folding problem, Logistics, Multiple Sequence Alignment, General Game Playing, Puzzles, 3D Packing with Object Orientation, Cooperative Pathfinding, Software testing and heuristic Model-Checking. In recent years, many researchers have explored different variants of the algorithms, their relations to Deep Reinforcement Learning and their different applications. The purpose of this workshop is to bring these researchers together to present their research, discuss future research directions, and cross-fertilize the different communities. Researchers and practitioners whose research might benefit from Monte Carlo Search in their research are welcome. | |
| W16 | Jan 7, 9am – 2pm JST Jan 7, 5pm – 10pm JST | 1st International Workshop on Heuristic Search in Industry | As an effective method for solving complex optimization problems, heuristic search has been widely used in industry, including logistics, digital maps, cloud computing, as well as manufacturing, among others. Work on heuristic search has a long tradition in AI, and there has been much progress over the last few decades. Advanced techniques in heuristic search are highly relevant for a range of real-world applications. On the other hand, real-world industrial applications give rise to interesting data sets and problems in this areas, and can also reveal bottlenecks and limitations of existing methods. The goal of this workshop is to bring together experts on heuristic search from academia and industry, and to promote real-world applications of heuristic search. | |
| W17 | Jan 7, 5pm – 10pm JST | AI for Internet of Things (AI4IoT 2020) | The Internet of Things (IoT) is the internetworking of physical devices with embedded electronics and an internet address that can transfer data without human interaction. Examples are wearable devices, environmental sensors, factory machinery, devices in homes and buildings, or vehicle components. These connected devices produce an exponentially growing amount of data including sensor data in time series format, image, sound and video data. Today, most of this data is unused. This workshop will explore how AI techniques can be used to (i) Make sense of these vast amounts of IoT data, (ii) Reason about connected physical systems and environments, (iii) Assist humans with the execution of actions. | |
| W18 | Jan 7, 9am – 2pm JST | 1st International Workshop on Harmonious and Symbiotic Interaction in AI & Robotics (HSIAR2020) | Harmonious and symbiotic interaction in AI & Robotics has been widely studied and are one of the emerging areas of research in the field of AI & Robotics. HSIAR2020 is based on Japanese CREST project of “Intelligent Information Processing Systems Creating Co-Experience Knowledge and Wisdom with Human-Machine Harmonious Collaboration”. This research area will advance research and development targeting intelligent information processing systems that create co-experience knowledge and wisdom through “balanced or harmonious collaboration” of humans and machines including AI & Robotics and bring about an improvement in the quality of the intellectual activities of individuals and groups. The balanced or harmonious and symbiotic collaboration means that not only users but also human society may feel the services of machines (or systems) acceptable in the human-machine collaboration. HSIAR2020 brings together researchers to discuss and present the state of the arts on this area. | |
| W19 | Jan 8, 9am – 2pm JST Jan 8, 5pm – 10pm JST | Robot Dialogues – Dialogue Models for Human-Robot Interaction | Large communities in AI, robotics and interaction technology already work on spoken language-based human-robot interaction. Their different starting points and assumptions call for discussions, exchange of ideas and more integrated approaches to implementations and modelling of spoken dialogues on robot platforms. This one-day workshop offers a platform for researchers to discuss and elaborate their views at the intersection of AI, robotics and spoken dialogue modelling. Sophisticated interaction models and implementations are critical in this endeavour but are not often explicitly addressed. Dialogue modelling and dialogue system implementations, on their part, are often developed without sufficiently considering how the models could be used in an embodied robotic system which also interacts with the environment. The workshop offers a platform for discussions concerning appropriate architectures and representations, in order to build a joint understanding of the aspects and features that address the pertinent questions in the multidisciplinary field of robot dialogues. | |
| W20 | Jan 7, 9am – 2pm JST Jan 7, 5pm – 10pm JST | Artificial Intelligence for Anomalies and Novelties | Anomalies are referred to as observations that are significantly different from the majority of observations, while novelties are observations from novel classes that are unseen during learning. Recognition, detection and/or adaption of anomalies/novelties are some of the most active research areas in multiple communities, such as data mining, machine learning and computer vision. Some of the relevant well-established research areas include anomaly/outlier detection, out-of-distribution example detection, adversarial example recognition and detection, open-set recognition and adaption, and they have broad applications in a variety of domains, such as fintech, healthcare, cybersecurity, safety in AI systems, etc. Some of these areas have been extensively explored for decades, but there are still many open problems in these areas due to some unique nature of anomalies and novelties, such as rareness, heterogeneity, unknowingness and uncertainty. This workshop aims to promote the development and applications of anomaly and novelty recognition, detection and adaption techniques. | |
| W21 | Jan 8, 9am – 2pm JST | 2nd International Workshop on Bringing Semantic Knowledge into Vision and Text Understanding | Extracting and understanding the high-level semantic information in vision and text data is considered as one of the key capabilities of effective artificial intelligence (AI) systems. Due to the success of deep representation learning, we have observed increasing research efforts in the intersection between vision and language for a better understanding of semantics, such as image captioning, visual question answering, etc. Besides, the vast amount of external semantic knowledge could assist in having a “deeper” understanding of vision and/or text data, e.g., describing the contents of images in a more natural way, constructing a comprehensive knowledge graph for movies, building a dialog system equipped with commonsense knowledge, etc. This workshop will provide a forum for researchers to review the recent progress of vision and text understanding, with an emphasis on novel approaches that involve a deeper and better semantic understanding of vision and text data. | |
| W22 | Jan 8, 9am – 2pm JST Jan 8, 5pm – 10pm JST | 2nd Workshop on Financial Technology and Natural Language Processing (FinNLP) | The aim of this workshop is to provide a forum where international participants can share knowledge in applying NLP to the FinTech domain. Recently, in the financial fields, FinTech is a new industry that focuses on improving financial activity with technology. Thus, the aim of this workshop is to bridge the gap between NLP researches and financial applications. With the sharing of the researchers in FinNLP, the challenging problems of blending FinTech and NLP will be identified, and the future research direction will be shaped. That can broaden the scope of this interdisciplinary research area. There are two shared tasks collocated with FinNLP-2020, including “Learning Semantic Representations for the Financial Domain” and “Sentence Boundary Detection in PDF Noisy Text in the Financial Domain.” We offer the prize for the best paper in the main track and the best-performing teams in the shared tasks. | |
| W23 | Jan 8, 9am – 2pm JST Jan 8, 5pm – 10pm JST | Linguistic and Cognitive Approaches to Dialogue Agents (LACATODA) | Linguistic and Cognitive Approaches to Dialog Agents (LaCATODA) is a multidisciplinary workshop for researchers whose work could be useful for developing sophisticated dialog agents (we welcome both methods for achieving more natural machine-generated conversation and theoretical studies of human communication which are difficult to mimic algorithmically). By combining Natural Language Processing and Machine Learning methods with cognitive architectures or philosophy of mind, we could discover novel approaches for machines that understand us, our environment, and our feelings. In this context, we see a role for NLP and cognitive science to play in developing a new generation of user- friendly, more autonomous but still safe systems which, through interaction with the user and the world, can learn how to reason, behave or speak naturally. We are interested in research tackling common sense knowledge and reasoning, affective computing, cognitive methods, learning from broad sets of data, and acquiring knowledge / language. | |
| W24 | Jan 7, 5pm – 10pm JST Jan 8, 5pm – 10pm JST | AI4Narratives | It is important to gather the knowledge on AI means, concepts and tools for Narrative Extraction, Representation and Generation and to join the AI community on these topics. This includes AI fields such as NLP, Machine Learning, Knowledge Representation, Inference, Planning, Graphical Communication and Image Processing. Applications include health care (patient stories), media (news outlets), communication science, business and reporting (data stories), industry (transparency) and arts (story generation, graphical depiction of stories). This workshop aims bringing together AI researchers and practitioners working on the topic of Narratives, mainly on NLP, but open to other relevant inputs in this emerging area. We invite researchers and practitioners to submit research papers, demo papers, position papers and nectar papers. | |
| W25 | Jan 8, 9am – 2pm JST Jan 8, 5pm – 10pm JST | Neuro-Cognitive Modeling of Humans and Environments | Recent advances in AI help improving our understanding on dynamic human crowd motion and behavior. These advances provide essential grounds for modeling and simulating human crowd under various environmental conditions such as architectural structures (e.g. buildings, stations, stadiums, museums, airports). There is a growing recent interest in identifying relationship between human (crowd) behavior and the built environmental structures, utilizing recent developments in AI and machine learning techniques as well as incorporating findings from perceptual, cognitive principles. This inaugural IJCAI-PRICAI 2020 Workshop aims to initiate the first-of-its-kind gathering of multidisciplinary experts interested in this area. This multidisciplinary approach combines cognitive principles and many different areas of machine learning to study the relationship between human behavior and the spaces they inhabit. It will also provide a platform for discussion on collecting appropriate data and challenges in the future gatherings. | |
| W26 | Jan 8, 9am – 2pm JST | Tensor Network Representations in Machine Learning | Tensor Networks (TNs) are factorizations of high order tensors into networks of low order tensors, which have been studied in quantum physics, chemistry and applied mathematics. TNs have been increasingly applied to machine learning and AI fields for modeling mutlimodal data, compressing deep neural networks, and scaling up algorithms to high-dimensional data. In particular, TNs have been successfully used to tackle challenging problems in data completion, model compression, multimodal fusion, multitask learning and learning theory. TNs are rapidly emerging and finding many interesting applications in machine learning, including modeling probability functions and implementing efficient TN computations in GPU. However, the topic of TNs in machine learning is relatively young and many open problems are still to be explored. This workshop will promote discussions among researchers investigating innovative TNs technology for fundamental theory and algorithms for ML and deep learning, and applications in computer vision, biomedical image processing, NLP, etc. | |
| W27 | Jan 7, 9am – 2pm JST | Knowledge-Based Reinforcement Learning (KBRL) | In recent years, deep Reinforcement Learning (RL) has been widely used in various domains including computer games, robotics, vision, and language. For applications in real-world environments, state of the art reinforcement learning algorithms suffer from a wide range of challenges such as sample inefficiency, safety constraints, partial observability, dynamic environments, hidden rewards in systems, and explainability. We believe that incorporating knowledge can potentially solve many of the most pressing challenges facing reinforcement learning today. The primary goal of this workshop is to facilitate community building: we hope to bring researchers together to consolidate this line of research and foster collaboration in the community. | |
| W28 | Jan 8, 5pm – 10pm JST | 6th Workshop on Semantic Deep Learning | This 6th Workshop on Semantic Deep Learning (SemDeep-6) aims at bringing together Semantic Web (SW) and Deep Learning (DL) research as well as industrial communities. Both disciplines have had a remarkable impact in data and knowledge analysis, as well as knowledge representation, and in fact constitute two complementary directions for modeling linguistic phenomena and solving semantically complex problems. SemDeep-6 addresses the open research question of how Semantic Web technologies can be united with state-of-the-art machine learning approaches in general, with a special focus on how to contribute to Explainable AI (XAI) this year. Given the success of last year’s challenge, we will continue this collaboration and SemDeep-6 will be joined by Target Sense Verification for Words in Context (WiC-TSV), which will extend the WiC dataset in several ways, such as hypernyms and definitions as well as two domain-specific datasets. | |
| W29 | Jan 7, 9am – 2pm JST | Learning Data Representation for Clustering | This workshop aims at discovering the recent advanced on data representation for clustering under different approaches. Thereby, the LDRC workshop is an opportunity to (i) present the recent advances in data representation based clustering algorithms; (ii) outline potential applications that could inspire new data representation approaches for clustering; and (iii) explore benchmark data to better evaluate and study data representation based clustering models. | |
| W30 | Jan 8, 9am – 2pm JST | 2nd International Workshop on Deep Learning for Human Activity Recognition | Human activity recognition (HAR) can be used for a number of applications, such as health-care services and smart home applications. Recently, deep learning has achieved great success in many challenging research areas, such as image recognition and natural language processing. The key merit of deep learning is to automatically learn representative features from massive data. This technology can be a good candidate for human activity recognition. Some initial attempts can be found in the literature. However, many challenging research problems in terms of accuracy, device heterogeneous, environment changes, etc. remain unsolved. This workshop intends to prompt state-of-the-art approaches on deep learning for human activity recognition. | |
| W32 | Jan 8, 5pm – 10pm JST | Federated Machine Learning for Data Privacy and Confidentiality | In order to explore how the AI research community can adapt to a more privacy conscious world, we organize a one-day workshop on Federated Learning for data privacy and user confidentiality. The workshop will focus on machine learning systems adhering to the privacy-preserving and security principles. Technical issues include but not limit to data collection, integration, training and modelling, both in the centralized and distributed setting. The workshop intends to provide a forum to discuss the open problems and share the most recent and ground-breaking work on the study and application of secure and privacy-preserving compliant machine learning. Both theoretical and application-based contributions are welcome. | |
| W34 | Jan 8, 9am – 2pm JST | Applied Mechanism Design | The aim of the workshop is to provide an internationally respected forum for scientific research and proposal in the fundamental challenges of mechanism design for real-world applications such as resource allocation, task allocation, and preference aggregation. As a crucial field of game theory, research on mechanism design has brought many novel solutions to the practice such as Google’s ad auctions, kidney exchanges, student-school matching, online recommendation, online QnA and digital/sharing economy platforms. Mechanism design has played an essential role in these systems to, for example, incentivize the users to behave in a desirable manner and optimize the resource/task allocations. Due to the tremendous development of IoT and social networks, system design has to consider the users’ swift reaction and collision formation via their social interactions and also the heavy computational costs. We need to investigate new mechanisms to handle these new challenges in both theory and practice. | |
| W35 | Jan 8, 9am – 2pm JST Jan 8, 5pm – 10pm JST | 3D Artificial Intelligence Challenge through 3D-FUTURE Benchmark | The goal of the workshop is to facilitate innovative research on high quality 3D shape understanding and generation, and to build a bridge between academic research and 3D applications in industry. Towards this goal, we release 3D-FUTURE (3D FUrniture shape with TextURE) which contains 20,000+ clean and realistic synthetic scenes in 5,000+ diverse rooms which contain 10,000+ unique industrial 3D instances of furniture with high resolution informative textures developed by professional designers. Building on 3D-FUTURE, we propose the Alibaba 3D Artificial Intelligence Challenge 2020 with three tracks: 1) Image-based 3D shape retrieval, 2) 3D object reconstruction, and 3) 3D shape assisted instance segmentation. In addition, a discussion panel is included in the workshop to provide a forum for potential research topics such as the recovery of both 3D shape and texture from 2D images. | |
| W36 | Jan 7, 9am – 2pm JST | Workshop on AI and Blockchains | The workshop will offer a systematic linkage between AI and blockchains and explore research challenges that arise at the forefront of AI and a broad range of Blockchain applications. The workshop will bring together researchers in Computer Science, Finance, Statistics, and Data Science, from academia, industry and the government, and will create an open interdisciplinary forum for discussing recent advances at the intersection of AI and Blockchains. In doing so, we aim to better understand the practical requirements of this domain and limitations of our current methodology – thereby, inspiring development of new algorithms for Blockchain Data analytics and leveraging blockchains for trustworthy AI applications. | |
| W38 | Jan 7, 5pm – 10pm JST Jan 8, 9am – 2pm JST | Workshop on Artificial Intelligence Safety (AISafety) | In the last decade, there has been a growing concern on risks of AI. Safety is becoming increasingly relevant as humans are progressively ruled out from the decision/control loop of intelligent, and learning-enabled machines. In particular, the technical foundations and assumptions on which traditional safety engineering principles are based, are inadequate for systems in which AI algorithms, in particular Machine Learning (ML) algorithms, are interacting with the physical world at increasingly higher levels of autonomy. The AISafety workshop seeks to explore new ideas on safety engineering, as well as broader strategic, ethical and policy aspects of safety-critical AI-based systems. As part of this 2-days workshop, we organise a full-day workshop on the AI Safety Landscape initiative. This initiative aims at defining an AI safety landscape providing a “view” of the current needs, challenges and state of the art and the practice of this field. | |
| W40 | Jan 8, 9am – 2pm JST | 2nd Workshop on AI & Food (AIxFood) | Food and cooking analysis present exciting challenges for modern AI, particularly in the context of multimodal data. A meal is a product of a progression of cooking stages, captured in recipes. Ingredients change physical properties, combine with other ingredients, all to produce a final, highly variable, appearance of the meal. Recognizing food items from images or videos, their amount or calories, food attributes such as flavors, the cooking action plan, or creating robotic assistants to help users complete the cooking process, is of essential scientific value yet technically extremely challenging. 2nd AIxFood Workshop aims to bring together researchers from academia and industry with interest in AI, nutrition and cooking. The workshop will focus on fundamental AI and machine learning problems, such as fine-grained object recognition, cross-modal retrieval & captioning, activity understanding, mutlimodal reference resolution, human-robot interaction, and design of novel user interfaces & experiences in the context of food AI. | |
| W41 | Jan 8, 9am – 2pm JST Jan 8, 5pm – 10pm JST | Explainable Artificial Intelligence (XAI) | As AI becomes more ubiquitous, complex and consequential, the need for people to understand how decisions are made and to judge their correctness becomes increasingly crucial due to concerns of ethics and trust. The field of Explainable AI (XAI), aims to address this problem by designing AI whose decisions can be understood by humans. This workshop aims to bring together researchers working in explainable AI to share and learning about recent research, with the hope of fostering meaningful connections between researchers from diverse backgrounds, including but not limited to artificial intelligence, human-computer interaction, human factors, philosophy, cognitive & social psychology. | |
