Papers
Learning Possibilistic Logic Theories from Default Rules
Ondřej Kuželka, Jesse Davis, Steven Schockaert
Learning Predictive State Representations via Monte-Carlo Tree Search
Yunlong Liu, Hexing Zhu, Yifeng Zeng et al.
Learning principled bilingual mappings of word embeddings while preserving monolingual invariance
Mikel Artetxe, Gorka Labaka, Eneko Agirre
Learning privately from multiparty data
Jihun Hamm, Yingjun Cao, Mikhail Belkin
Learning Probabilistic Submodular Diversity Models Via Noise Contrastive Estimation
Sebastian Tschiatschek, Josip Djolonga, Andreas Krause
Learning Prototypical Event Structure from Photo Albums
Antoine Bosselut, Jianfu Chen, David Warren et al.
Learning Qualitative Spatial Relations for Robotic Navigation
Abdeslam Boularias, Felix Duvallet, Jean Oh et al.
Learning Reconstruction-Based Remote Gaze Estimation
Pei Yu, Jiahuan Zhou, Ying Wu
Learning Relationships between Data Obtained Independently
Alexandra Carpentier, Teresa Schlueter
Learning Relaxed Deep Supervision for Better Edge Detection
Yu Liu, Michael S. Lew
Learning Representations for Counterfactual Inference
Fredrik Johansson, Uri Shalit, David Sontag
Learning Robust Features using Deep Learning for Automatic Seizure Detection
Pierre Thodoroff, Joelle Pineau, Andrew Lim
Learning Robust Representations of Text
Yitong Li, Trevor Cohn, Timothy Baldwin
Learning Semantically and Additively Compositional Distributional Representations
Ran Tian, Naoaki Okazaki, Kentaro Inui
Learning Sensor Multiplexing Design through Back-propagation
Ayan Chakrabarti
Learning Sentence Embeddings with Auxiliary Tasks for Cross-Domain Sentiment Classification
Jianfei Yu, Jing Jiang
Learning shape correspondence with anisotropic convolutional neural networks
Davide Boscaini, Jonathan Masci, Emanuele Rodolà et al.
Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization
Zhao Song, Ricardo Henao, David Carlson et al.
Learning Simple Algorithms from Examples
Wojciech Zaremba, Tomas Mikolov, Armand Joulin et al.
Learning Simple Auctions
Jamie Morgenstern, Tim Roughgarden
Learning Social Affordance for Human-Robot Interaction
Tianmin Shu, M. S. Ryoo, Song-Chun Zhu
Learning Sparse Additive Models with Interactions in High Dimensions
Hemant Tyagi, Anastasios Kyrillidis, Bernd Gärtner et al.
Learning Sparse Combinatorial Representations via Two-stage Submodular Maximization
Eric Balkanski, Baharan Mirzasoleiman, Andreas Krause et al.
Learning Sparse Gaussian Graphical Models with Overlapping Blocks
Mohammad Javad Hosseini, Su-In Lee