Papers
8,340 papers found
Robust and Discriminative Self-Taught Learning
Hua Wang, Feiping Nie, Heng Huang
Robust Regression on MapReduce
Xiangrui Meng, Michael Mahoney
Robust Sparse Regression under Adversarial Corruption
Yudong Chen, Constantine Caramanis, Shie Mannor
Robust Structural Metric Learning
Daryl Lim, Gert Lanckriet, Brian McFee
Rounding Methods for Discrete Linear Classification
Yann Chevaleyre, Frédéerick Koriche, Jean-daniel Zucker
SADA: A General Framework to Support Robust Causation Discovery
Ruichu Cai, Zhenjie Zhang, Zhifeng Hao
Safe Policy Iteration
Matteo Pirotta, Marcello Restelli, Alessio Pecorino et al.
Safe Screening of Non-Support Vectors in Pathwise SVM Computation
Kohei Ogawa, Yoshiki Suzuki, Ichiro Takeuchi
Scalable Optimization of Neighbor Embedding for Visualization
Zhirong Yang, Jaakko Peltonen, Samuel Kaski
Scalable Simple Random Sampling and Stratified Sampling
Xiangrui Meng
Scale Invariant Conditional Dependence Measures
Sashank J Reddi, Barnabas Poczos
Scaling Multidimensional Gaussian Processes using Projected Additive Approximations
Elad Gilboa, Yunus Saatçi, John Cunningham et al.
Scaling the Indian Buffet Process via Submodular Maximization
Colorado Reed, Ghahramani Zoubin
Semi-supervised Clustering by Input Pattern Assisted Pairwise Similarity Matrix Completion
Jinfeng Yi, Lijun Zhang, Rong Jin et al.
Sequential Bayesian Search
Zheng Wen, Branislav Kveton, Brian Eriksson et al.
Sharp Generalization Error Bounds for Randomly-projected Classifiers
Robert Durrant, Ata Kaban
Smooth Operators
Steffen Grunewalder, Gretton Arthur, John Shawe-Taylor
Smooth Sparse Coding via Marginal Regression for Learning Sparse Representations
Krishnakumar Balasubramanian, Kai Yu, Guy Lebanon
Solving Continuous POMDPs: Value Iteration with Incremental Learning of an Efficient Space Representation
Sebastian Brechtel, Tobias Gindele, Rüdiger Dillmann
Sparse coding for multitask and transfer learning
Andreas Maurer, Massi Pontil, Bernardino Romera-Paredes
Sparse Gaussian Conditional Random Fields: Algorithms, Theory, and Application to Energy Forecasting
Matt Wytock, Zico Kolter
Sparse PCA through Low-rank Approximations
Dimitris Papailiopoulos, Alexandros Dimakis, Stavros Korokythakis