Papers
Learning Eigenvectors for Free
Wouter M. Koolen, Wojciech Kotlowski, Manfred K. Warmuth
Learning Higher-Order Graph Structure with Features by Structure Penalty
Shilin Ding, Grace Wahba, Xiaojin Zhu
Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint
Kenji Fukumizu, Gert R. Lanckriet, Bharath K. Sriperumbudur
Learning large-margin halfspaces with more malicious noise
Phil Long, Rocco Servedio
Learning Patient-Specific Cancer Survival Distributions as a Sequence of Dependent Regressors
Chun-Nam Yu, Russell Greiner, Hsiu-Chin Lin et al.
Learning person-object interactions for action recognition in still images
Vincent Delaitre, Josef Sivic, Ivan Laptev
Learning Probabilistic Non-Linear Latent Variable Models for Tracking Complex Activities
Angela Yao, Juergen Gall, Luc V. Gool et al.
Learning Sparse Representations of High Dimensional Data on Large Scale Dictionaries
Zhen J. Xiang, Hao Xu, Peter J. Ramadge
Learning to Agglomerate Superpixel Hierarchies
Viren Jain, Srinivas C. Turaga, K Briggman et al.
Learning to Learn with Compound HD Models
Antonio Torralba, Joshua B. Tenenbaum, Ruslan Salakhutdinov
Learning to Search Efficiently in High Dimensions
Zhen Li, Huazhong Ning, Liangliang Cao et al.
Learning unbelievable probabilities
Zachary Pitkow, Yashar Ahmadian, Ken D. Miller
Learning with the weighted trace-norm under arbitrary sampling distributions
Rina Foygel, Ohad Shamir, Nati Srebro et al.
Linearized Alternating Direction Method with Adaptive Penalty for Low-Rank Representation
Zhouchen Lin, Risheng Liu, Zhixun Su
Linear Submodular Bandits and their Application to Diversified Retrieval
Yisong Yue, Carlos Guestrin
Lower Bounds for Passive and Active Learning
Maxim Raginsky, Alexander Rakhlin
Manifold Precis: An Annealing Technique for Diverse Sampling of Manifolds
Nitesh Shroff, Pavan Turaga, Rama Chellappa
MAP Inference for Bayesian Inverse Reinforcement Learning
Jaedeug Choi, Kee-eung Kim
Matrix Completion for Multi-label Image Classification
Ricardo S. Cabral, Fernando Torre, Joao P. Costeira et al.
Maximal Cliques that Satisfy Hard Constraints with Application to Deformable Object Model Learning
Xinggang Wang, Xiang Bai, Xingwei Yang et al.
Maximum Covariance Unfolding : Manifold Learning for Bimodal Data
Vijay Mahadevan, Chi W. Wong, Jose C. Pereira et al.
Maximum Margin Multi-Instance Learning
Hua Wang, Heng Huang, Farhad Kamangar et al.
Maximum Margin Multi-Label Structured Prediction
Christoph H. Lampert
Message-Passing for Approximate MAP Inference with Latent Variables
Jiarong Jiang, Piyush Rai, Hal Daume
Metric Learning with Multiple Kernels
Jun Wang, Huyen T. Do, Adam Woznica et al.