Papers
Perturbation based Large Margin Approach for Ranking
Eunho Yang, Ambuj Tewari, Pradeep Ravikumar
Active Learning from Multiple Knowledge Sources
Yan Yan, Romer Rosales, Glenn Fung et al.
Robust Multi-task Regression with Grossly Corrupted Observations
Huan Xu, Chenlei Leng
Statistical Optimization in High Dimensions
Huan Xu, Constantine Caramanis, Shie Mannor
Primal-Dual methods for sparse constrained matrix completion
Yu Xin, Tommi Jaakkola
Causality with Gates
John Winn
Generalized Optimal Reverse Prediction
Martha White, Dale Schuurmans
Nonlinear low-dimensional regression using auxiliary coordinates
Weiran Wang, Miguel Carreira-Perpinan
A Hybrid Neural Network-Latent Topic Model
Li Wan, Leo Zhu, Rob Fergus
Minimax Rates of Estimation for Sparse PCA in High Dimensions
Vincent Vu, Jing Lei
Bayesian Group Factor Analysis
Seppo Virtanen, Arto Klami, Suleiman Khan et al.
Krylov Subspace Descent for Deep Learning
Oriol Vinyals, Daniel Povey
Learning from Weak Teachers
Ruth Urner, Shai Ben David, Ohad Shamir
A Bayesian Analysis of the Radioactive Releases of Fukushima
Ryota Tomioka, Morten Mrup
Fast Variational Mode-Seeking
Bo Thiesson, Jingu Kim
Randomized Optimum Models for Structured Prediction
Daniel Tarlow, Ryan Adams, Richard Zemel
Structured Output Learning with High Order Loss Functions
Daniel Tarlow, Richard Zemel
Multiresolution Deep Belief Networks
Yichuan Tang, Abdel-Rahman Mohamed
Lifted Variable Elimination with Arbitrary Constraints
Nima Taghipour, Daan Fierens, Jesse Davis et al.
On Estimation and Selection for Topic Models
Matt Taddy
Fast Learning Rate of Multiple Kernel Learning: Trade-Off between Sparsity and Smoothness
Taiji Suzuki, Masashi Sugiyama
Constrained 1-Spectral Clustering
Syama Sundar Rangapuram, Matthias Hein
Efficient and Exact MAP-MRF Inference using Branch and Bound
Min Sun, Murali Telaprolu, Honglak Lee et al.
Learning Fourier Sparse Set Functions
Peter Stobbe, Andreas Krause
Bayesian Inference for Change Points in Dynamical Systems with Reusable States - a Chinese Restaurant Process Approach
Florian Stimberg, Andreas Ruttor, Manfred Opper