2016
Analyzing the oversampling of different classes and types of examples in multi-class imbalanced datasets
2016.05.26
발표자: 이재동
발표일자: 2016-05-23
저자: José A. Sáez et al
학회명: Pattern Recognition 2016
Deep Convolutional Neural Networks for Sentiment Analysis of Short Texts
2016.05.26
발표자: 전창용
발표일자: 2016-05-23
저자: Cicero Nogueira dos Santos, Maira Gatti
학회명: Proceedings of the 25th International Conference on Computational Linguistics (COLING), Dublin, Ireland, 2014
Improving Music Recommendation in Session-Based Collaborative Filtering by using Temporal Context
2016.05.26
발표자: 김베드로
발표일자: 2016-05-16
저자: Dias, Ricardo, and Manuel J. Fonseca
학회명: IEEE 25th International Conference on Tools with Artificial Intelligence (ICTAI), 2013
Deep Captioning With Multimodal Recurrent Neural Networks (m-RNN)
2016.05.26
발표자: 김수아
발표일자: 2016-05-16
저자: Junhua Mao, Wei Xu, Yi Yang, JiangWang, Zhiheng Huang, Alan Yuille
학회명: The Annual Conference on Neural Information Processing Systems (NIPS), 2014
A Neural Algorithm of Artistic Style
2016.05.26
발표자: 박경한
발표일자: 2016-05-16
저자: Leon A. Gatys, Alexander S. Ecker, Matthias Bethge
Document Modeling with Gated Recurrent Neural Network for Sentiment Classification
2016.05.26
발표자: 스터디팀
발표일자: 2016-05-16
저자: Duyu Tang, Bing Qin, Ting Liu
학회명: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing
Recommendation in heterogeneous information networks with implicit user feedback
2016.05.16
발표자: Umar
발표일자: 2016-05-12
저자: Xiao Yu, et al.
학회명: RecSys’ 13, October 12-16, 2013
Learning Statistical Scripts with LSTM Recurrent Neural Networks
2016.05.16
발표자: 김다해
발표일자: 2016-05-12
저자: Karl Pichotta and Raymond J. Mooney
학회명: Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16).
Virtual User Approach for Group Recommender Systems using Precedence Relations
2016.05.16
발표자: 김누리
발표일자: 2016-05-02
저자: Venkateswara Rao Kagita, Arun K. Pujari, and Vineet Padmanabhan
논문지: Information Sciences 294 (2015): 15-30
A Model for Proactivity in Mobile, Context-aware Recommender Systems
2016.05.16
발표자: 박혜진
발표일자: 2016-05-02
저자: W. Woerndl, J. Huebner, R. Bader, and D. G. Vico
학회명: Proceedings of the fifth ACM conference on Recommender systems. ACM, 2011
Recurrent Convolutional neural networks for text classification
2016.05.16
발표자: 스터디팀
발표일자: 2016-05-02
저자: Siwei lai et al
학회명: Proceedings of the twenty-ninth aaai conference on artificial intelligence
SoCo: A Social Network Aided Context-Aware Recommender System
2016.05.16
발표자: 방한별
발표일자: 2016-04-18
저자: Xin Liu et al
학회명: Proceedings of the 22nd international conference on World
Language Understanding for Text-based Games using Deep Reinforcement Learning
2016.05.16
발표자: 이세희
발표일자: 2016-04-18
저자: Karthik Narasimhan, Tejas Kulkarni, Regina Barzilay
학회명: Proceedings of the Conference on Empirical Methods in Natural Language Processing(EMNLP-15)
Adaptive semi-unsupervised weighted oversampling (A-SUWO) for imbalanced datasets
2016.05.16
발표자: 이재동
발표일자: 2016-04-18
저자: Iman Nekooeimehr et al
논문지: Expert Systems with Applications 2016
Phrase-based Image Captioning
2016.05.16
발표자: 김수아
발표일자: 2016-04-11
저자: R´emi Lebret, Pedro O. Pinheiro, Ronan Collobert
학회명: Proceedings of the 32nd International Conference on Machine Learning
Semi-supervised Convolutional Neural Networks for Text Categorization via Region Embedding
2016.05.16
발표자: 김진아
발표일자: 2016-04-11
저자: Rie Johnson, Tong Zhang
학회명: Advances in Neural Information Processing Systems 28
Generating Sequences With Recurrent Neural Networks
2016.05.16
발표자: 스터디팀
발표일자: 2016-04-11
저자: Alex Graves
논문지: arxiv
Question/Answer Matching for CQA System via Combining Lexical and Sequential Information
2016.03.28
발표자: 봉원재
발표일자: 2016-03-28
저자: Yikang Shen
학회명: AAAI Conference on Artificial Intelligence
Style recommendation for fashion items using heterogeneous information network
2016.03.28
발표자: Umar
발표일자: 2016-03-28
저자: Hanbit Lee
학회명: RecSys 2015 Poster Proceedings
Context-Based Splitting of Item Ratings in Collaborative filtering
2016.03.28
발표자: 김베드로
발표일자: 2016-03-28
저자: Baltrunas, Linas
학회명: Proceedings of the 3th ACM conference on Recommender systems