Papers
Learning for Tail Label Data: A Label-Specific Feature Approach
Tong Wei, Wei-Wei Tu, Yu-Feng Li
Learning from a Learner
Alexis Jacq, Matthieu Geist, Ana Paiva et al.
Learning from Bad Data via Generation
Tianyu Guo, Chang Xu, Boxin Shi et al.
Learning from brains how to regularize machines
Zhe Li, Wieland Brendel, Edgar Walker et al.
Learning (from) Deep Hierarchical Structure among Features
Yu Zhang, Lei Han
Learning from Delayed Outcomes via Proxies with Applications to Recommender Systems
Timothy Arthur Mann, Sven Gowal, Andras Gyorgy et al.
Learning from demonstration with model-based Gaussian process
Noémie Jaquier, David Ginsbourger, Sylvain Calinon
Learning from Dialogue after Deployment: Feed Yourself, Chatbot!
Braden Hancock, Antoine Bordes, Pierre-Emmanuel Mazare et al.
Learning from Few Subjects with Large Amounts of Voice Monitoring Data
Jose Javier Gonzalez Ortiz, Daryush D. Mehta, Jarrad H. Van Stan et al.
Learning from Implicit Information in Natural Language Instructions for Robotic Manipulations
Ozan Arkan Can, Pedro Zuidberg Dos Martires, Andreas Persson et al.
Learning from Label Proportions with Generative Adversarial Networks
Jiabin Liu, Bo Wang, Zhiquan Qi et al.
Learning from My Partner’s Actions: Roles in Decentralized Robot Teams
Dylan P. Losey, Mengxi Li, Jeannette Bohg et al.
Learning From Noisy Labels by Regularized Estimation of Annotator Confusion
Ryutaro Tanno, Ardavan Saeedi, Swami Sankaranarayanan et al.
Learning from Omission
Bill McDowell, Noah Goodman
Learning from Positive and Unlabeled Data with a Selection Bias
Masahiro Kato, Takeshi Teshima, Junya Honda
Learning from sparsely annotated data for semantic segmentation in histopathology images
John-Melle Bokhorst, Hans Pinckaers, Peter van Zwam et al.
Learning From Synthetic Data for Crowd Counting in the Wild
Qi Wang, Junyu Gao, Wei Lin et al.
Learning from the Experience of Doctors: Automated Diagnosis of Appendicitis Based on Clinical Notes
Steven Kester Yuwono, Hwee Tou Ng, Kee Yuan Ngiam
Learning from Trajectories via Subgoal Discovery
Sujoy Paul, Jeroen Vanbaar, Amit Roy-Chowdhury
Learning from Weakly Dependent Data under Dobrushin’s Condition
Yuval Dagan, Constantinos Daskalakis, Nishanth Dikkala et al.
Learning from Web Data Using Adversarial Discriminative Neural Networks for Fine-Grained Classification
Xiaoxiao Sun, Liyi Chen, Jufeng Yang
Learning Fully Dense Neural Networks for Image Semantic Segmentation
Mingmin Zhen, Jinglu Wang, Lei Zhou et al.
Learning GANs and Ensembles Using Discrepancy
Ben Adlam, Corinna Cortes, Mehryar Mohri et al.
Learning Generalizable Device Placement Algorithms for Distributed Machine Learning
ravichandra addanki, Shaileshh Bojja Venkatakrishnan, Shreyan Gupta et al.