Clinical time series derived from electronic health records (EHRs) are inherently irregular, with asynchronous sampling, missing values, and heterogeneous feature dynamics. While numerical laboratory measurements are highly informative, existing embedding strategies usually combine feature identity and value embeddings through additive operations, which constrains their ability to capture value-dependent feature interactions. We propose MedFuse, a framework for irregular clinical time series centered on the MuFuse (Multiplicative Embedding Fusion) module. MuFuse fuses value and feature embeddings through multiplicative modulation, preserving feature-specific information while modeling higher-order dependencies across features. Experiments on three real-world datasets covering both intensive and chronic care show that MedFuse consistently outperforms state-of-the-art baselines on key predictive tasks. Analysis of the learned representations further demonstrates that multiplicative fusion enhances expressiveness and supports cross-dataset pretraining. These results establish MedFuse as a generalizable approach for modeling irregular clinical time series.

First of all, we would like to thank all reviewers for their suggestions to improve our paper submission. These results restate that UMAL is always in the best positions. Comparison of the Negative Log-Likelihood of the test set over different train-test folds proposed in [3].

It has been noticed that through COVID-19 greenhouse gas emissions had a sudden reduction. Based on this significant observation, we decided to conduct a research to quantify the impact of scientific conferences' air-travelling, explore and suggest alternative ways for greener conferences to re-duce the global carbon footprint. Specifically, we focused on the most popular conferences for the Artificial Intelligence community based on their scientific impact factor, their scale, and the well-organized proceedings towards measuring the impact of air travelling participation. This is the first time that systematic quantification of a state-of-the-art subject like Artificial Intelligence takes place to define its conferencing footprint in the broader frames of environmental awareness. Our findings highlight that the virtual way is the first on the list of green conferences' conduction although there are serious concerns about it. Alternatives to optimal conferences' location selection have demonstrated savings on air-travelling CO2 emissions of up to 63.9%.

Best papers of the workshop, after further revisions and independent reviews, will be considered for publication in a special issue of a renowned journal. By this holistic view we encounter a variety of challenges along the AI modeling cycle and software system engineering lifecycle as outlined in the figure below such as: • theory-practice gap in machine learning with impact on stability, reproducibility or integrity due to limitations of nowadays theoretical foundations in statistical learning theory or lack of control of high-dimensionality effects of deep learning; • facing computational constraints, e.g. All submissions will be peer-reviewed by, at least, 3 reviewers and judged on the basis of originality, contribution to the field, technical and presentation quality, and relevance to the workshop. Short papers are meant for timely discussion and feedback at the workshop. Papers are accepted with the understanding that at least one author will register for the conference to present the paper.

Humans interact with each other through several means (e.g., voice, gestures, written text, facial expressions, etc.) and a natural human-machine interaction system should preserve the same modality. However, traditional Natural Language Processing (NLP) focuses on analyzing textual input to solve language understanding and reasoning tasks, and other modalities are only partially targeted. This workshop aims to be a forum for both academia and industry researchers where new and unfinished research in the area of Multi/Cross-Modal NLP can be discussed. In particular, the focus of this workshop are (i) studying how to bridge the gap between NLP on spoken and written language and (ii) exploring how NLU models can be empowered by jointly analyzing multiple input sources, including language (spoken or written), vision (gestures and expressions) and acoustic (paralingustic) modalities. All deadlines must be considered at 11.59pm GMT-12 (anywhere on Earth).

The Conference on Empirical Methods in Natural Language Processing (EMNLP) is one of the top natural language processing conferences in the world. In 2019, it is to be held in Hong Kong, China. There were 1,813 long paper submissions, of which 465 were accepted and 1,063 short paper submissions, of which 218 were accepted. A large number of these papers also published their code ( code download link). To help the community quickly catch up on the work presented in this conference, Paper Digest Team processed all accepted papers, and generated one highlight sentence (typically the main topic) for each paper.

The ACL 2018 conference invites the submission of long and short papers on substantial, original, and unpublished research in all aspects of Computational Linguistics and Natural Language Processing. As in recent years, some of the presentations at the conference will be of papers accepted by the Transactions of the ACL journal. ACL 2018 adopts the new policies for submission, review, and citation. Submissions that violate any of these policies will be rejected without review. Most importantly, the policies refer to the anonymity period, which starts at January 22nd, 2018 for ACL 2018.

The Seventeenth International FLAIRS Conference seeks high quality, original, unpublished submissions in all areas of AI, including, but not limited to, neural networks, autonomous agents, case-based reasoning, computer vision, data mining, expert systems, genetic algorithms, intelligent user interfaces, intelligent tutoring systems, knowledge representation and management, learning, automated reasoning, multi-agent systems, natural language processing, planning, uncertainty reasoning, robotics, semantic web, speech recognition, temporal reasoning, AI and the Web, AI applications, AI and education, and verification/validation. All accepted papers will appear in the conference proceedings published by AAAI Press. Selected papers will receive best-paper awards. Selected authors will be invited to submit extended versions of their papers to a special issue of the International Journal on Artificial Intelligence Tools (IJAIT) to be published in 2005. The papers should not exceed 5 pages and is due by October 24, 2003.

The 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2018) will be held in New Orleans, Louisiana, June 1 to June 6, 2018. NAACL-HLT 2018 invites the submission of long and short papers on substantial, original, and unpublished research in all aspects of computational linguistics. NAACL-HLT 2018 has a goal of a broad technical program. Long paper submissions must describe substantial, original, completed and unpublished work. Wherever appropriate, concrete evaluation and analysis should be included.

The 7th International Conference on Intelligent Environments (IE11) was held July 25–28 2011 at the Nottingham Trent University, Nottingham, UK. The general chairs were Ahmad Lotfi (Nottingham Trent University), and Sean Hanna (Bartlett School of Graduate Studies, University College London). Juan Carlos Augusto (University of Ulster) and Achilles Kameas (Hellenic Open University and Computer Technology Institute), served as program chairs. This article presents a report of the conference.