Jingyan Wang, Ivan Stelmakh, Yuting Wei, Nihar B. Shah

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Sanghamitra Deb

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nlp, recommendation, deep learning, classification

Shaoxiong Feng, Hongshen Chen, Xuancheng Ren and

Zhuoye Ding, Kan Li, Xu Sun

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Junshu Jiang, Songyun Ye, Wei Wang and

Jingran Xu, Xiaosheng Luo

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person-job fit, deepfm, lstm, cnn, job post, resume, feature fusion

Wanwei He, Min Yang, Rui Yan and

Chengming Li, Ying Shen, Ruifeng Xu

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task completion, generating responses, task-oriented dialogue, task-oriented systems

Shiwei Tong, Qi Liu, Runlong Yu and

Wei Huang, Zhenya Huang, Zachary A. Pardos, Weijie Jiang

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Humans and AI, Personalization and User Modeling, Computer-Aided Education

Jibing Gong, Shen Wang, Jinlong Wang and

Wenzheng Feng, Hao Peng, Jie Tang, Philip S. Yu

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graph neural networks, heterogeneous information network, recommender system

Roy Miles, Krystian Mikolajczyk

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pruning, knowledge distillation, image classification

Tongzhou Mu, Jiayuan Gu, Zhiwei Jia and

Hao Tang, Hao Su

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Zheng Li, Ying Huang, Defang Chen and

Tianren Luo, Ning Cai, Zhigeng Pan

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Tanner Fiez, Nihar Shah, Lillian Ratliff

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Xiaowu Dai, Michael Jordan

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generative model, fairness

Pramuditha Perera, Vlad I. Morariu, Rajiv Jain and

Varun Manjunatha, Curtis Wigington, Vicente Ordonez, Vishal M. Patel

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open-set recognition, open-set detection, novelty detection, out-of-distribution detection, recognition

Bowen Hao, Jing Zhang, Cuiping Li and

Hong Chen, Hongzhi Yin

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Bingchen Zhao, Kai Han

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deep learning, machine learning, clustering, transfer learning, semi-supervised learning

Guodong Wang, Shumin Han, Errui Ding, Di Huang

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anomaly detection, knowledge distillation, student-teacher framework, feature pyramid matching

Han-Jia Ye, Su Lu, De-Chuan Zhan

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knowledge distillation, model reuse, knowledge transfer, cross-task learning, embedding learning

Yiming Li, Shunli Ren, Pengxiang Wu and

Siheng Chen, Chen Feng, Wenjun Zhang

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vision, graph learning

Qitian Wu, Hengrui Zhang, Xiaofeng Gao and

Junchi Yan, Hongyuan Zha

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Applications, Recommender Systems

Sashank Reddi, Rama Kumar Pasumarthi, Aditya Menon and

Ankit Singh Rawat, Felix Yu, Seungyeon Kim, Andreas Veit, Sanjiv Kumar

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Gaurush Hiranandani, Jatin Mathur, Harikrishna Narasimhan and

Mahdi Milani Fard, Sanmi Koyejo

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Algorithms, Supervised Learning

Iman Yeckehzaare, Tirdad Barghi, Paul Resnick

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question generation, concept mapping, learnersourcing, cscl, collaborative learning, intrinsic motivation, learner-centered design

Zhiqiang Tao, Yaliang Li, Bolin Ding and

Ce Zhang, Jingren Zhou, Yun Fu

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Chen Zheng, Quan Guo, Parisa Kordjamshidi

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Cross-Modality Relevance, Language Vision, visual answering, VQA

Jing Yao, Zhicheng Dou, Ji-Rong Wen

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personalized search, personal word embedding, user interest

Michael Wan, Tanmay Gangwani, Jian Peng

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Chuanguang Yang, Zhulin An, Linhang Cai, Yongjun Xu

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Computer Vision, Recognition

Marco Morik, Ashudeep Singh, Jessica Hong, Thorsten Joachims

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Machine Learning, Learning Preferences or Rankings, Fairness, Information Retrieval, Online Learning

Brian Brubach, Darshan Chakrabarti, John Dickerson and

Samir Khuller, Aravind Srinivasan, Leonidas Tsepenekas

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Unsupervised and Semi-Supervised Learning

Hengtong Hu, Lingxi Xie, Richang Hong, Qi Tian

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cross-model retrieval, cross-model hashing, unsupervised learning, knowledge distillation, similarity calculation, teacher-student network, supervised learning, unsupervised model guiding supervised model, exploiting information from output features, achieving sota performance

Chao Ye, Huaidong Zhang, Xuemiao Xu and

Weiwei Cai, Jing Qin, Kup-Sze Choi

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Computer Vision, Recognition, Deep Learning, Semi-Supervised Learning

Jianquan Li, Xiaokang Liu, Honghong Zhao and

Ruifeng Xu, Min Yang, Yaohong Jin

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natural tasks, nlp tasks, matching, many-to-many mapping

Chaoqi Wang, Adish Singla, Yuxin Chen

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optimization, active learning

Wangshu Zhang, Junhong Liu, Zujie Wen and

Yafang Wang, Gerard de Melo

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Qiushan Guo, Xinjiang Wang, Yichao Wu and

Zhipeng Yu, Ding Liang, Xiaolin Hu, Ping Luo

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knowledge distillation, collaborative learning, transfer learning, deep neural network

Marco Morik, Ashudeep Singh, Jessica Hong, Thorsten Joachims

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learning-to-rank, selection bias, exposure, fairness, ranking, bias

Dana Ruiter, Josef van Genabith, Cristina España-Bonet

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training, self-supervised, ssnmt, ssnmt model

Yaling Tao, Kentaro Takagi, Kouta Nakata

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deep embedding, clustering, representation learning

Xiaobo Wang

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Aria Masoomi, Chieh T Wu, Tingting Zhao and

Zifeng Wang, Peter Castaldi, Jennifer Dy

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