±¨ ¸æ ÈË£ºÎâ¼Ñ ¸±½ÌÊÚ£¬°Ä´ïÀûÑÇÂó¿¼Èð´óѧ
»ã±¨¹¦·ò£º06ÔÂ16ÈÕ£¨ÖÜËÄ£©14:00¡«18:00
»ã±¨µØÖ·£ºÌÚѶ»áÒ飨942-458-858£©
Ñû Çë ÈË£ºÓຽ ½²Ê¦
»ã±¨ÌáÒª£º
Big Data is an emerging paradigm, characterized by complex information that is beyond the processing capability of conventional tools. Traditional data analytics methods are commonly used in many applications, such as text classification and image recognition, and these data are often required to be represented as vectors for analysis purposes. Data may also come from heterogeneous domains, such as traditional tabular-based data,
sequential patterns, social networks, time series information, or semi-structured data. Complex data poses new challenges for current research in data mining and knowledge discovery as new processing, mining, and learning methods are required.
»ã±¨È˼ò½é:
Jia Wu ¸±½ÌÊÚ£¨ARC DECRA Fellow£¬ÓÅÇ࣬Top Êý¾ÝÍÚ¾òÆÚ¿¯ ACM TKDD ¸±Ö÷±à£©¡£ÏÖÈΰĴóÀûÑÇÂó¿¼Èð´óѧÈËΪÖÇÄÜ×êÑÐÖÐÐÄ Research Director¡£ÒѾ°ä·¢¸ßˮƽÂÛÎÄ 100 ¶àƪ£¬Ô̺¬ CCF A ÀàTPAMI, TKDE, KDD, NIPS, WWW, IJCAI, AAAI ºÍ ACM/IEEE Trans ÆÚ¿¯ TNNLS, TMM, TII, TCYB, TKDD µÈ¡£ÏÖÈιú¼ÊÊý¾ÝÍÚ¾ò¶¥¼¶ÆÚ¿¯ ACM TKDD, Neural Networks ¸±Ö÷±à¡£2019Äê»ñµÃ°ÄÖÞ¿ÆÑ§Ôº Heidelberg Laureate Forum Fellowship¡£Ëù¸¨µ¼µÄ×êÑÐÍŶӻñµÃ 2021ÄêÊý¾ÝÍÚ¾ò¶¥¼¶¹ú¼Ê»áÒé IEEE ICDM£¨Â¼ÓÃÂÊ 9.9%£©¡£×î¼ÑѧÉúÂÛÎĽ±£¬2018Äê¹ú¼Ê¶¥¼¶Êý¾ÝÍÚ¾ò´ó»á SDM ×î¼ÑÊý¾Ý¿ÆÑ§ÀûÓý±£¬2017Äê¹ú¼Ê¶¥¼¶ÈËΪÉñ¾ÍøÂçIJCNN×î¼ÑѧÉúÂÛÎĽ±¡£