Papers
Learning Ordered Representations with Nested Dropout
Oren Rippel, Michael Gelbart, Ryan Adams
Learning Polynomials with Neural Networks
Alexandr Andoni, Rina Panigrahy, Gregory Valiant et al.
Learning Sum-Product Networks with Direct and Indirect Variable Interactions
Amirmohammad Rooshenas, Daniel Lowd
Learning the Consistent Behavior of Common Users for Target Node Prediction across Social Networks
Shan-Hung Wu, Hao-Heng Chien, Kuan-Hua Lin et al.
Learning the Irreducible Representations of Commutative Lie Groups
Taco Cohen, Max Welling
Learning Theory and Algorithms for revenue optimization in second price auctions with reserve
Mehryar Mohri, Andres Munoz Medina
Learning the Parameters of Determinantal Point Process Kernels
Raja Hafiz Affandi, Emily Fox, Ryan Adams et al.
Learning to Disentangle Factors of Variation with Manifold Interaction
Scott Reed, Kihyuk Sohn, Yuting Zhang et al.
Least Squares Revisited: Scalable Approaches for Multi-class Prediction
Alekh Agarwal, Sham Kakade, Nikos Karampatziakis et al.
Linear and Parallel Learning of Markov Random Fields
Yariv Mizrahi, Misha Denil, Nando De Freitas
Linear Programming for Large-Scale Markov Decision Problems
Alan Malek, Yasin Abbasi-Yadkori, Peter Bartlett
Linear Time Solver for Primal SVM
Feiping Nie, Yizhen Huang, Heng Huang
Local algorithms for interactive clustering
Pranjal Awasthi, Maria Balcan, Konstantin Voevodski
Local Ordinal Embedding
Yoshikazu Terada, Ulrike Luxburg
Low-density Parity Constraints for Hashing-Based Discrete Integration
Stefano Ermon, Carla Gomes, Ashish Sabharwal et al.
Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians
Christopher Tosh, Sanjoy Dasgupta
Making Fisher Discriminant Analysis Scalable
Bojun Tu, Zhihua Zhang, Shusen Wang et al.
Marginalized Denoising Auto-encoders for Nonlinear Representations
Minmin Chen, Kilian Weinberger, Fei Sha et al.
Marginal Structured SVM with Hidden Variables
Wei Ping, Qiang Liu, Alex Ihler
Margins, Kernels and Non-linear Smoothed Perceptrons
Aaditya Ramdas, Javier Peña
Maximum Margin Multiclass Nearest Neighbors
Aryeh Kontorovich, Roi Weiss
Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection
Arun Iyer, Saketha Nath, Sunita Sarawagi
Max-Margin Infinite Hidden Markov Models
Aonan Zhang, Jun Zhu, Bo Zhang
Memory and Computation Efficient PCA via Very Sparse Random Projections
Farhad Pourkamali Anaraki, Shannon Hughes