Papers
Learning Domain-Sensitive and Sentiment-Aware Word Embeddings
Bei Shi, Zihao Fu, Lidong Bing et al.
Learning Dual Convolutional Neural Networks for Low-Level Vision
Jinshan Pan, Sifei Liu, Deqing Sun et al.
Learning Dynamics of Linear Denoising Autoencoders
Arnu Pretorius, Steve Kroon, Herman Kamper
Learning Emotion-enriched Word Representations
Ameeta Agrawal, Aijun An, Manos Papagelis
Learning End-to-End Goal-Oriented Dialog with Multiple Answers
Janarthanan Rajendran, Jatin Ganhotra, Satinder Singh et al.
Learning Environmental Calibration Actions for Policy Self-Evolution
Chao Zhang, Yang Yu, Zhi-Hua Zhou
Learning Equations for Extrapolation and Control
Subham Sahoo, Christoph Lampert, Georg Martius
Learning Explanations from Language Data
David Harbecke, Robert Schwarzenberg, Christoph Alt
Learning Explanatory Rules from Noisy Data (Extended Abstract)
Richard Evans, Edward Grefenstette
Learning Face Age Progression: A Pyramid Architecture of GANs
Hongyu Yang, Di Huang, Yunhong Wang et al.
Learning Facial Action Units From Web Images With Scalable Weakly Supervised Clustering
Kaili Zhao, Wen-Sheng Chu, Aleix M. Martinez
Learning filter widths of spectral decompositions with wavelets
Haidar Khan, Bulent Yener
Learning for Disparity Estimation Through Feature Constancy
Zhengfa Liang, Yiliu Feng, Yulan Guo et al.
Learning from Between-class Examples for Deep Sound Recognition
Yuji Tokozume, Yoshitaka Ushiku, Tatsuya Harada
Learning from Chunk-based Feedback in Neural Machine Translation
Pavel Petrushkov, Shahram Khadivi, Evgeny Matusov
Learning from Comparisons and Choices
Sahand Negahban, Sewoong Oh, Kiran K. Thekumparampil et al.
Learning from discriminative feature feedback
Sanjoy Dasgupta, Akansha Dey, Nicholas Roberts et al.
Learning from Group Comparisons: Exploiting Higher Order Interactions
Yao Li, Minhao Cheng, Kevin Fujii et al.
Learning from Measurements in Crowdsourcing Models: Inferring Ground Truth from Diverse Annotation Types
Paul Felt, Eric Ringger, Jordan Boyd-Graber et al.
Learning From Millions of 3D Scans for Large-Scale 3D Face Recognition
Syed Zulqarnain Gilani, Ajmal Mian
Learning From Noisy Singly-labeled Data
Ashish Khetan, Zachary C. Lipton, Animashree Anandkumar
Learning From Noisy Web Data With Category-Level Supervision
Li Niu, Qingtao Tang, Ashok Veeraraghavan et al.
Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation
Swami Sankaranarayanan, Yogesh Balaji, Arpit Jain et al.
Learning from the experts: From expert systems to machine-learned diagnosis models
Murali Ravuri, Anitha Kannan, Geoffrey J. Tso et al.