Papers
Learnable Visual Markers
Oleg Grinchuk, Vadim Lebedev, Victor Lempitsky
Learned Region Sparsity and Diversity Also Predicts Visual Attention
Zijun Wei, Hossein Adeli, Minh Hoai Nguyen et al.
Learning Additive Exponential Family Graphical Models via $\ell_{2,1}$-norm Regularized M-Estimation
Xiaotong Yuan, Ping Li, Tong Zhang et al.
Learning a Metric Embedding for Face Recognition using the Multibatch Method
Oren Tadmor, Tal Rosenwein, Shai Shalev-Shwartz et al.
Learning and Forecasting Opinion Dynamics in Social Networks
Abir De, Isabel Valera, Niloy Ganguly et al.
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling
Jiajun Wu, Chengkai Zhang, Tianfan Xue et al.
Learning Bayesian networks with ancestral constraints
Eunice Yuh-Jie Chen, Yujia Shen, Arthur Choi et al.
Learning Bound for Parameter Transfer Learning
Wataru Kumagai
Learning brain regions via large-scale online structured sparse dictionary learning
Elvis DOHMATOB, Arthur Mensch, Gael Varoquaux et al.
Learning Deep Embeddings with Histogram Loss
Evgeniya Ustinova, Victor Lempitsky
Learning Deep Parsimonious Representations
Renjie Liao, Alex Schwing, Richard Zemel et al.
Learning feed-forward one-shot learners
Luca Bertinetto, João F. Henriques, Jack Valmadre et al.
Learning from Rational Behavior: Predicting Solutions to Unknown Linear Programs
Shahin Jabbari, Ryan M Rogers, Aaron Roth et al.
Learning from Small Sample Sets by Combining Unsupervised Meta-Training with CNNs
Yu-Xiong Wang, Martial Hebert
Learning HMMs with Nonparametric Emissions via Spectral Decompositions of Continuous Matrices
Kirthevasan Kandasamy, Maruan Al-Shedivat, Eric P Xing
Learning Infinite RBMs with Frank-Wolfe
Wei Ping, Qiang Liu, Alex Ihler
Learning Influence Functions from Incomplete Observations
Xinran He, Ke Xu, David Kempe et al.
Learning in Games: Robustness of Fast Convergence
Dylan J Foster, Zhiyuan Li, Thodoris Lykouris et al.
Learning Kernels with Random Features
Aman Sinha, John C. Duchi
Learning Multiagent Communication with Backpropagation
Sainbayar Sukhbaatar, arthur szlam, Rob Fergus
Learning Parametric Sparse Models for Image Super-Resolution
Yongbo Li, Weisheng Dong, Xuemei Xie et al.
Learning Sensor Multiplexing Design through Back-propagation
Ayan Chakrabarti
Learning shape correspondence with anisotropic convolutional neural networks
Davide Boscaini, Jonathan Masci, Emanuele Rodolà et al.
Learning Sparse Gaussian Graphical Models with Overlapping Blocks
Mohammad Javad Hosseini, Su-In Lee
Learning Structured Sparsity in Deep Neural Networks
Wei Wen, Chunpeng Wu, Yandan Wang et al.