Activities

8月1日至3日,2017年中国计算机协会人工智能会议在云南省昆明市举行,会议安排6个大会特邀报告、3个专题研讨会,并与ACM数据挖掘中国分会联合举办“CCFAI工业高峰论坛暨ACM数据挖掘中国分会年会”。PALM实验室的老师与同学参加了此次会议。耿新老师做特邀报告《标记分布学习范式》,张敏灵老师和薛晖老师分别担任了部分报告的主持人工作。王靖、徐宁、吴璇和孙彦苹代表实验室参与了讲习班。


耿新老师在做特邀报告

张敏灵老师担任分会主持人

与会老师与同学合影

7月26日到28日,第十六届中国机器学习会议(CCML)在天津举办,PALM实验室的老师和同学参与了该会议。张敏灵老师参加了青年学者特别论坛、专委会工作会议,并担任分会报告主持人。同时,薛晖老师也受邀担任分会报告主持人。PALM学生丁思宇替周斌斌做了《基于三元纠错输出编码的偏标记学习算法》。


张敏灵老师参与青年学者特别论文、专委会工作会议并担任分会主持人

薛晖老师担任分会主持人

丁思宇在做报告

与会同学合影

7月16日,“山西省大数据分析与挖掘研究生暑期学校”开班,20余位国内外大数据和人工智能领域的知名学者、杰出专家汇聚山西大学,展开为期一周的专题讲学。PALM实验室的老师和同学参与了该暑期学校。耿新老师和张敏灵老师分别做了《标记分布学习范式》与《多标记机器学习》的专题讲座。


耿新老师在做《标记分布学习范式》的专题讲座

张敏灵老师在做《多标记机器学习》的专题讲座

The Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17) is held February 4–9 at the Hilton San Francisco, San Francisco, California, USA. PALM faulties Xin Geng and Min-ling Zhang and students Miao-gen Ling, Cai-zhi Tang and Hai-ming Xu attended this conference. Miao-gen Ling and Cai-zhi Tang gave a report on their newly research, meanwhile, Hai-ming Xu took part in the post communication.


2016年11月4日至6日,MAL'16会议在南京(南京大学)举行。PALM实验室的老师和同学参加了此次会议。耿新老师担任了会议第四部分的主持。在会议回顾部分,张敏灵老师介绍了KDD'16会议,耿新老师介绍了CVPR'16会议。实验室同学侯鹏、邢超和周斌斌参加了墙展交流,并做了相关报告。


耿新老师在介绍CVPR'16会议

张敏灵老师在介绍KDD'16会议

侯鹏在介绍自己的研究成果

邢超在介绍自己的研究成果

周斌斌在介绍自己的研究成果

侯鹏(左上)、邢超(坐下)和周斌斌(右)与参会人员进行墙展交流

PALM实验室成员与周志华老师合影留念

The IEEE Conference on Computer Vision and Pattern Recognition (CVPR2016) was held from June 26th to July 1st at Las Vegas, NV, USA. Proffessor Xin Geng and student Chao Xing attended the conference. Chao Xing showed the poster about the "Logistic Boosting Regression for Label Distribution Learning", moreover, he gave an oral talk about the CVPR2016 ChaLearn LAP and FoW - Age Estimation Competition named "Deep Age Distribution Learning for Apparent Age Estimation".

Title: Neuroscience-informed sound, music, and wearable computing for rehabilitation and learning

Abstract

The use of music as an aid in improving body and mind has received enormous attention over the last 20 years from a wide range of disciplines, including neuroscience, physical therapy, exercise science, and psychological medicine. We have attempted to transform insights gained from the scientific study of music, learning, and medicine into real-life applications that can be delivered widely, effectively, and accurately. We have been using music to enhance learning as well as to augment evidence-based medicine. In this talk, I will describe tools to facilitate the delivery of established music-enhanced therapies, harnessing the synergy of sound and music computing (SMC), mobile computing, and cloud computing technologies to promote learning and to facilitate disease prevention, diagnosis, and treatment in both developed countries and resource-poor developing countries. These tools are being developed as part of ongoing research projects that combine wearable sensors, smartphone apps, and cloud-based therapy delivery systems to facilitate music-enhanced learning and music-enhanced physical therapy. I will also discuss the joys and pains working in such a multidisciplinary environment.

Biography

Ye Wang is an Associate Professor in the Computer Science Department at the National University of Singapore (NUS) and NUS Graduate School for Integrative Sciences and Engineering (NGS). He established and directed the sound and music computing (SMC) Lab (www.smcnus.org). Before joining NUS he was a member of the technical staff at Nokia Research Center in Tampere, Finland for 9 years. His research interests include sound analysis and music information retrieval (MIR), mobile computing, and cloud computing, and their applications in music edutainment , e-Learning, and e-Health, as well as determining their effectiveness via subjective and objective evaluations. His most recent projects involve the design and evaluation of systems to support 1) therapeutic gait training using Rhythmic Auditory Stimulation (RAS), 2) second language learning, and 3) motivating exercise via music-based systems.

2016年4月22日至24日,VALSE'16会议在武汉(巴山夜雨大酒店)举行。PALM实验室的老师和同学参加了此次会议。张敏灵老师做了题为《多示例学习简介及其在计算机视觉中的应用》的报告。侯鹏(下图左)和邢超(下图右)参加了墙展交流。


Congratulations to the PALM team 'palm_seu' which won the runner-up in the Chalearn LAP Apparent Age Estimation challenge!

The challenge is part of Face Analysis Workshop and Challenge, CVPR'16 and the details can be found in http://gesture.chalearn.org/ . The team is supervised by professor Xin Geng and its members include: Chao Xing, Zeng-wei Huo, Ying Zhou, Xu Yang, Peng Hou and Jia-qi Lv. The result of the challenge is showed in the table.

The Thirtieth AAAI Conference on Artificial Intelligence (AAAI'16) was held February 12-17 at the Phoenix Convertion Center, Phoenix, Arizona, USA. Peng Hou attended the conference and gave an oral talk about the paper "Multi-Label Manifold Learning".

Title: Scene Text Detection/Recognition: Recent Advances and Our Solutions

Abstract

Text information appearing in a scene carries vital information for interpreting the contents, and identifying objects and surrounding environment in images. Although conventional document analysis techniques have bee quite successful, identifying general text in images remains a very challenging research problem. The recent prestigious conferences on computer vision, pattern recognition, and machine learning have seen an increased interest on this topic from the computer vision research community. In this talk, I will show you the challenges and the recent advances in research on scene text recognition and our solutions and attempts.

Biography

Dr. Wenjing Jia is currently a Lecturer at the School of Computing and Communications at University of Technology Sydney (UTS) teaching various under- and postgraduate internetworking subjects. She is also a core research member of UTS Global Big Data Technologies Centre. Her research interests include image processing/analysis and object detection and recognition. In particular, she has been working in the field of text information extraction for several years. This has included working on applications such as vehicle identification via recognizing their license plates, textual information retrieval from images on web pages and emails, and text sign recognition from natural scene images. She has had over 70 publications in journals such as TIP and conferences such as ICIP and ICPR. A focus of more recent work has been to explore deep features and deep learning architectures for detecting and recognising scene text or text signage from unconstrained, outdoor street level imagery. Prior to UTS, Wenjing worked at Fuzhou University from 1999 to 2003 as an Associate Lecturer teaching various subjects in communications and information systems and conducting research on medical image analysis.

Congratulations to the PALM graduates Lei Wu who won the Jiangsu Province outstanding master's degree thesis!

祝贺PALM毕业生吴磊获得江苏省优秀硕士学位论文!

题目: 自然人机交互与情感计算

讲者: 陶建华,研究员,中科院自动化所

摘要: 情感信息是人机交互的重要组成部分,本报告将重点分析多模态人机交互过程中,情感分析与处理的建模方法,以及不同模态信息对情感分析的影响。报告还将对人机交互面临的一系列挑战进行分析。

个人简介:中科院自动化所模式识别国家重点实验室研究员、副主任,中科院脑科学与智能技术卓越创新研究中心核心骨干,中国科学院大学首席教授,国家杰出青年基金获得者。担任中国计算机学会常务理事,中国人工智能学会理事,中国中文信息学会理事,中国声学学会理事,Steering Committee Member of IEEE Trans. On Affective Computing,以及Journal on Multimodal User Interfaces, Speech Communication等期刊编委。主要研究方向为语音识别与合成、人机交互、模式识别等,在主要国际期刊或会议上发表论文100余篇。

2015年11月7日至8日,MLA'15会议在南京大学(仙林校区)举行。PALM实验室的老师和同学参加了此次会议。耿新老师做了题为《Label Distribution Learning and Application》的报告,张老师担任了大会的部分主持人工作。于菲和侯鹏参加了墙展交流。

耿老师在做报告

于菲在做墙展交流

张老师担任大会部分主持人

侯鹏在做墙展交流