人工智能 | 国际会议截稿信息9条

人工智能

DSML 2018

Dependable and Secure Machine Learning

全文截稿: 2018-04-01

开会时间: 2018-06-25

会议难度: ★★★

CCF分类: 无

会议地点: Luxembourg City, Luxembourg

网址：https://dependablesecureml.github.io

Machine learning (ML) is increasingly used in critical domains such as health and wellness, criminal sentencing recommendations, commerce, transportation, human capital management, entertainment, and communication. The design of ML systems has mainly focused on developing models, algorithms, and datasets on which they are trained to demonstrate high accuracy for specific tasks such as object recognition and classification. Machine learning algorithms typically construct a model by training on a labeled training dataset and their performance is assessed based on the accuracy in predicting labels for unseen (but often similar) testing data. This is based on the assumption that the training dataset is representative of the inputs that the system will face in deployment. However, in practice there are a wide variety of unexpected accidental, as well as adversarially-crafted, perturbations on the ML inputs that might lead to violations of this assumption. Further, ML algorithms are often executed on special-purpose hardware accelerators, which may themselves be subject to faults. Thus, there is a growing concern regarding the reliability, safety, security, and accountability of machine learning systems.

The DSN Workshop on Dependable and Secure Machine Learning (DSML) is an open forum for researchers, practitioners, and regulatory experts, to present and discuss innovative ideas and practical techniques and tools for producing dependable and secure ML systems. A major goal of the workshop is to draw the attention of the research community to the problem of establishing guarantees of reliability, security, safety, and robustness for systems that incorporate increasingly complex ML models, and to the challenge of determining whether such systems can comply with requirements for safety-critical systems. A further goal is to build a research community at the intersection of machine learning and dependable and secure computing.

人工智能

PALE 2018

International Workshop on Personalization Approaches in Learning Environments

全文截稿: 2018-04-15

开会时间: 2018-06-27

会议难度: ★★

CCF分类: 无

会议地点: London and Singapore

网址：http://adenu.ia.uned.es/workshops/pale2018/

PALE 2018 is a follow-up of the seven previous editions of PALE (see details at history). The focus of this workshop series is put on the different and complementary perspectives in which personalization can be addressed in learning environments (e.g., informal, workplace, lifelong, mobile, contextualized, and self-regulated learning). Previous editions have shown several important issues in this field, such as behavior and embodiment of pedagogic agents, suitable support of self-regulated learning, appropriate balance between learner control and expert guidance, design of personal learning environments, contextual recommendations at various levels of the learning process, tracking and reacting to affective states of learners, harmonization of educational and technological standards, big data processing for learning purposes, predicting student outcomes, adaptive learning assessment, and evaluation of personalized learning systems. PALE workshop offers an opportunity to present and discuss a wide spectrum of issues and solutions.

From the past experience we have identified new areas of interest in this research scope to complement the previous ones.

Thus, in this workshop edition we would like to share and discuss the new trends in current research on how user modeling and associated artificial intelligent techniques are able to contextualize and manage the increasing amount of information coming from the task at hand and its surrounding environment in order to provide the personalization support in a wide range of learning environments, which are increasingly more sensitive to the learners and their context. This covers many interrelated fields such as: intelligent tutoring systems, learning management systems, personal learning environments, serious games, agent-based learning environments, and others. Furthermore, we aim to cover the demanding need of personalized learning in wider contexts ranging from daily life activities to massive open online courses (MOOCs).

人工智能

NLP-Era 2018

ESSLLI Workshop on NLP in the Era of Big Data, Deep Learning, and Post Truth

全文截稿: 2018-04-16

开会时间: 2018-08-13

会议难度: ★★

CCF分类: 无

会议地点: Sofia, Bulgaria

网址：http://alt.qcri.org/esslli2018-nlp-era/

Recent years have seen fast advances of the field of Natural Language Processing (NLP) due to the simultaneous influence of two revolutionary forces: Big Data and Deep Learning. The aim of using large corpora has been prominent in NLP since an earlier statistical, corpus-based revolution of the 1990s. Indeed, in corpus-based NLP size does matter, and researchers have been exploring corpora as large as the entire Web; now this abundance of data has enabled the return of Neural Networks and the rise of Deep Learning. More recently, we have further seen the rise of Big Data with its 3Vs: Volume, Velocity, and Variety. Even more recently, with the spread of fake news, it has been suggested that a fourth V should be considered: Veracity.

The workshop welcomes work presenting new developments in applying NLP for solving problems related to Big Data, Deep Learning, and Veracity. We also invite discussion about the impact of these revolutionary forces on the field of NLP as a whole.

The workshop will be held during the whole second week of the 30th edition of ESSLLI (European Summer School in Logic, Language and Information) August 13 - 17, 2018.

人工智能

MRQA 2018

Machine Reading for Question Answering

全文截稿: 2018-04-23

开会时间: 2018-07-15

会议难度: ★★★

CCF分类: 无

会议地点: Melbourne, Australia

网址：https://mrqa2018.github.io/

Machine Reading for Question Answering (MRQA) has become an important testbed for evaluating how well computer systems understand human language, as well as a crucial technology for industry applications such as search engines and dialog systems. The research community has recently created a multitude of large-scale datasets over text sources such as Wikipedia (WikiReading, SQuAD, WikiHop), news and other articles (CNN/Daily Mail, NewsQA, RACE), fictional stories (MCTest, CBT, NarrativeQA), and general web sources (MS MARCO, TriviaQA, SearchQA). These new datasets have in turn inspired an even wider array of new question answering systems.

This workshop will gather researchers to address and discuss important research topics surrounding MRQA, including:
-Accuracy: How can we make MRQA systems more accurate?
-Interpretability: How can systems provide rationales for their predictions?
-Speed and Scalability: How can systems scale to consider larger contexts, from long documents to the whole web?
-Robustness: How can systems generalize to other datasets and settings beyond the training distribution?
-Dataset Creation: What are effective methods for building new MRQA datasets?
-Dataset Analysis: What challenges do current MRQA datasets pose?
-Error Analysis: What types of questions or documents are particularly challenging for existing systems?

人工智能

FFER 2018

International Workshop on Face and Facial Expression Recognition

全文截稿: 2018-05-21

开会时间: 2018-08-20

会议难度: ★★

CCF分类: 无

会议地点: Beijing, China

网址：https://ffer.aau.dk/

The face plays a key role in many real-world applications such as security systems, human computer interaction, remote monitoring of patients, video annotation, and gaming. Having detected the face, pattern recognition techniques and machine learning algorithms are applied to facial images, for example, to find the identity of a subject or analyze her/his emotional status. Though face and facial expression recognition in still images and in ideal imaging conditions have been around for many years, they have been less explored in video sequences in uncontrolled real-world videos. Given the ubiquitous presence of video cameras, face and facial expression recognition from such videos is becoming increasingly important for many applications, for instance for security surveillance, remote patient monitoring. Recognizing faces and facial expressions from real-world videos, however, remain challenging because of low video quality, illumination variation, head pose variation, and significant occlusion. Despite these challenges, video offers dynamics and motion information that is not available in still image and they can be exploited to improve the recognition. The purpose of this workshop is to bring together researchers who are working on developing face and facial expression recognition systems that involve non-ideal conditions, like those that might be present in a real-world video. We welcome research papers focusing on the following (and similar) topics:
-Video face recognition
-Video facial expression recognition
-Face and facial expression recognition from facial dynamics
-Face detection and tracking from video
-Multi-face clustering from video
-3D face modeling from video
-Applications of video face recognition
-Applications of video facial expression recognition

人工智能

CoNLL 2018

Conference on Natural Language Learning

全文截稿: 2018-06-01

开会时间: 2018-10-31

会议难度: ★★★

CCF分类: C类

会议地点: Brussels, Belgium

网址：http://www.conll.org/

CoNLL is a top-tier conference, yearly organized by SIGNLL (ACL's Special Interest Group on Natural Language Learning). This year, CoNLL will be colocated with EMNLP 2018 in Brussels, Belgium.

In 2018, CoNLL will have two shared tasks:
-Multilingual Parsing from Raw Text to Universal Dependencies  
-CoNLL–SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection

人工智能

NLIWoD 2018

International Workshop on Natural Language Interfaces for Web of Data

全文截稿: 2018-06-01

开会时间: 2018-10-08

会议难度: ★★

CCF分类: 无

会议地点: Montarey, California, USA

网址：http://2018.NLIWoD.org/

This workshop is a joint event of two active communities in the area of interaction paradigms to Linked Data: NLIWOD4 and QALD-9. NLIWOD, a workshop for discussions on the advancement of natural language interfaces to the Web of Data, has been organized three-times within ISWC, with a focus on soliciting discussions on the development of question answering systems. QALD is a benchmarking campaign powered by the H2020 project HOBBIT (project-hobbit.eu) including question answering over (Big) linked data, has been organized as a challenge within CLEF, ESWC and ISWC. This joint workshop hopes to attract people from the two communities in order to promote active collaboration, to extend the scope of currently addressed topics, and to foster the reuse of resources developed so far. Furthermore, we offer an challenge - QALD-9 - where users are free to demonstrate the capabilities of their systems using the provided online benchmark platform. Furthermore, we want to broaden the scope of this workshop series to dialogue systems and chatbots as increasingly important business intelligence factors.

人工智能

ACCV 2018

Asian Conference on Computer Vision

全文截稿: 2018-07-05

开会时间: 2018-12-02

会议难度: ★★★

CCF分类: C类

会议地点: Perth, Australia

网址：http://accv2018.net/

On behalf of the Organising Committee and program chairs I am delighted to invite you to the 14th Asian Conference on Computer Vision (ACCV). The Conference will be held in the Perth Convention and Exhibition Centre from Sunday 2 December to Thursday 6 December 2018.

This highly successful Conference series provides a premier forum for researchers, developers, and practitioners to present and discuss new problems, solutions, and technologies in computer vision and related areas. ACCV 2018 solicits high-quality original research for publication in its main Conference and co-located workshops.

The Perth Convention and Exhibition Centre is situated along the beautiful Swan River near the Perth CBD, guests enjoy easy access to the centre and nearby attractions.

Perth is Australia’s only capital city where you can enjoy the beach lifestyle, relax in natural bushland, sample world-class local wines and watch an ocean sunset within just 30 minutes of the city.

Our social program will open with a Welcome Reception in the Perth Convention and Exhibition Centre summer gardens on Monday evening where you will be able to catch up with old friends and meet new colleagues. Wednesday evening will host the Gala Dinner in the breathtaking Belleview Ballroom of the Perth Convention and Exhibition Centre, don’t miss this evening of fine food, wine and company.

Clear blue skies with balmy weather are the norm during summer in Perth. I would highly recommend coming to Perth earlier or staying longer afterwards to enjoy and explore what our vast and amazing state of Western Australia has to offer – food, wine, natural attractions and a wide variety of outdoor activities.

人工智能

ICICKM 2018

International Conference on Intellectual Capital, Knowledge Management & Organisational Learning

摘要截稿: 2018-05-18

全文截稿: 2018-07-06

开会时间: 2018-11-29

会议难度: ★★

CCF分类: 无

会议地点: Cape Town, South Africa

网址：https://www.academic-conferences.org/conferences/icickm/

The International Conference on Intellectual Capital, Knowledge Management and Organisational Learning was established 15 years ago. It has been held in Australia, USA, Thailand, Canada, South Africa, to mention only a few of the countries who have hosted it.  ICICKM is generally attended by participants from more than 35 countries and attracts an interesting combination of academic scholars, practitioners and individuals who are engaged in various aspects of Intellectual Capital and Knowledge Management.

下载Call4Papers App，获取更多详细内容！