Papers
Learning Semantic Relationships for Better Action Retrieval in Images
Vignesh Ramanathan, Congcong Li, Jia Deng et al.
Learning Semi-Supervised Representation Towards a Unified Optimization Framework for Semi-Supervised Learning
Chun-Guang Li, Zhouchen Lin, Honggang Zhang et al.
Learning Shape, Motion and Elastic Models in Force Space
Antonio Agudo, Francesc Moreno-Noguer
Learning Similarity Metrics for Dynamic Scene Segmentation
Damien Teney, Matthew Brown, Dmitry Kit et al.
Learning Social Relation Traits From Face Images
Zhanpeng Zhang, Ping Luo, Chen-Change Loy et al.
Learning Sparse Low-Threshold Linear Classifiers
Sivan Sabato, Shai Shalev-Shwartz, Nathan Srebro et al.
Learning Spatially Regularized Correlation Filters for Visual Tracking
Martin Danelljan, Gustav Hager, Fahad Shahbaz Khan et al.
Learning Spatiotemporal Features With 3D Convolutional Networks
Du Tran, Lubomir Bourdev, Rob Fergus et al.
Learning spatiotemporal trajectories from manifold-valued longitudinal data
Jean-Baptiste SCHIRATTI, Stéphanie ALLASSONNIERE, Olivier Colliot et al.
Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels
Felipe Tobar, Thang D Bui, Richard E Turner
Learning structured densities via infinite dimensional exponential families
Siqi Sun, Mladen Kolar, Jinbo Xu
Learning Structured Output Representation using Deep Conditional Generative Models
Kihyuk Sohn, Honglak Lee, Xinchen Yan
Learning Submodular Losses with the Lovasz Hinge
Jiaqian Yu, Matthew Blaschko
Learning Temporal Embeddings for Complex Video Analysis
Vignesh Ramanathan, Kevin Tang, Greg Mori et al.
Learning the dependence structure of rare events: a non-asymptotic study
Nicolas Goix, Anne Sabourin, Stéphan Clémen\ccon
Learning Theory and Algorithms for Forecasting Non-stationary Time Series
Vitaly Kuznetsov, Mehryar Mohri
Learning Theory of Randomized Kaczmarz Algorithm
Junhong Lin, Ding-Xuan Zhou
Learning the Structure and Parameters of Large-Population Graphical Games from Behavioral Data
Jean Honorio, Luis Ortiz
Learning The Structure of Deep Convolutional Networks
Jiashi Feng, Trevor Darrell
Learning to Boost Filamentary Structure Segmentation
Lin Gu, Li Cheng
Learning to Combine Mid-Level Cues for Object Proposal Generation
Tom Lee, Sanja Fidler, Sven Dickinson
Learning to Compare Image Patches via Convolutional Neural Networks
Sergey Zagoruyko, Nikos Komodakis
Learning to Detect Motion Boundaries
Philippe Weinzaepfel, Jerome Revaud, Zaid Harchaoui et al.
Learning to Divide and Conquer for Online Multi-Target Tracking
Francesco Solera, Simone Calderara, Rita Cucchiara
Learning to Generate Chairs With Convolutional Neural Networks
Alexey Dosovitskiy, Jost Tobias Springenberg, Thomas Brox