In this paper, based on the hinge loss and SVM, a new dictionary learning with multi-task transfer learning method(DMTTL) is proposed. The dictionary learning method is utilized to learn sparse representation of the given samples. Moreover, a regularization term for two dictionaries are ...
A Multitask Learning Approach to Action Quality Assessment 来源/作者机构情况: Paritosh Parmar,nevada大学 解决问题/主要思想贡献: 提出使用三种方法来共同决定动作得分: -fine-grained action recognition,commentary generation,and estimating the AQA score. 成果/优点: 更准确的打分率 缺点: 反思改进/灵感: 动作...
Finally, a multi-task learning method is used to predict traffic speed on different types of road segments because of heterogeneity and shares the underlying network parameters. The evaluation experiments use the monitoring data of the highway in Yinchuan City, Ningxia Province, China. The ...
inputs. PrismNet [51] and Multi-resBind [41] (another multi-task model) further increase network depth via stacking of convolutional layers, while adding residual connections to combat the vanishing gradient problem. PrismNet [51] additionally makes use of a Squeeze-and-Excitation (SE) module ...
Paper download:"Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning in Targeted Display Advertising" Source code:https://github.com/xidongbo/AITM Job Offers Meituan's financial intelligence application team continues to recruit algorithm positions, and sincerely...
【MultiDomain Learning】A Multi-Scenario Multi-Task Meta Learning Approach for Advertiser Modeling 1. 背景 不同于大多数针对用户建模的研究,本文是针对广告主的行为进行建模。大型电商平台通常提供多种营销场景(赞助搜索、展示广告、直播广告),而广告主的行为往往分散在许多平台中。所以,多任务&多场景建模对于学习...
Understanding Fine-Grained Sentiments of Super-Priority Destination Visitors using Multi-task Learning for Extraction of Aspect Terms and Polarity Classifi... The method used for sentiment analysis of these tourist reviews is the Local Context Focus - Aspect Term Extraction & Aspect Polarization ...
A new method for multitask learning in a Bayesian network context is presented for multiorganism gene network estimation. When the input datasets are sparse, as is the case in microarray gene expression data, it becomes difficult to separate random correlations from actual edges in the true under...
When Age-Invariant Face Recognition Meets Face Age Synthesis:A Multi-Task Learning Framework 为了在人脸识别中最小化年龄变化的影响,之前的工作要么通过最小化身份和年龄相关特征之间的相关性来提取与身份相关的有区分度特征,称为年龄不变人脸识别(age-invariant face recognition, AIFR),或者通过将不同年龄组的...
1. Deep Multi-task Learning : 本文的目标是,用一个联合的预测模型,同时预测多个人脸属性。当大量 face attributes 给特征学习效率上带来挑战的同时,他们也提供了结合属性内部关系的机会(leveraging the attribute inter-correlations to obtain informative and robust feature representation)。例如,CelebA dataset 中的...