Papers
Information-Geometric Optimization Algorithms: A Unifying Picture via Invariance Principles
Yann Ollivier, Ludovic Arnold, Anne Auger et al.
Joint Label Inference in Networks
Deepayan Chakrabarti, Stanislav Funiak, Jonathan Chang et al.
Kernel Partial Least Squares for Stationary Data
Marco Singer, Tatyana Krivobokova, Axel Munk
Knowledge Graph Completion via Complex Tensor Factorization
Théo Trouillon, Christopher R. Dance, Éric Gaussier et al.
Learning Instrumental Variables with Structural and Non-Gaussianity Assumptions
Ricardo Silva, Shohei Shimizu
Learning Local Dependence In Ordered Data
Guo Yu, Jacob Bien
Learning Partial Policies to Speedup MDP Tree Search via Reduction to I.I.D. Learning
Jervis Pinto, Alan Fern
Learning Scalable Deep Kernels with Recurrent Structure
Maruan Al-Shedivat, Andrew Gordon Wilson, Yunus Saatchi et al.
Learning Theory of Distributed Regression with Bias Corrected Regularization Kernel Network
Zheng-Chu Guo, Lei Shi, Qiang Wu
Lens Depth Function and k-Relative Neighborhood Graph: Versatile Tools for Ordinal Data Analysis
Matthäus Kleindessner, Ulrike von Luxburg
Local algorithms for interactive clustering
Pranjal Awasthi, Maria Florina Balcan, Konstantin Voevodski
Making Decision Trees Feasible in Ultrahigh Feature and Label Dimensions
Weiwei Liu, Ivor W. Tsang
Matrix Completion with Noisy Entries and Outliers
Raymond K. W. Wong, Thomas C. M. Lee
Memory Efficient Kernel Approximation
Si Si, Cho-Jui Hsieh, Inderjit S. Dhillon
Minimax Estimation of Kernel Mean Embeddings
Ilya Tolstikhin, Bharath K. Sriperumbudur, Krikamol Muandet
Multiscale Strategies for Computing Optimal Transport
Samuel Gerber, Mauro Maggioni
Nearly optimal classification for semimetrics
Lee-Ad Gottlieb, Aryeh Kontorovich, Pinhas Nisnevitch
Non-parametric Policy Search with Limited Information Loss
Herke van Hoof, Gerhard Neumann, Jan Peters
Nonparametric Risk Bounds for Time-Series Forecasting
Daniel J. McDonald, Cosma Rohilla Shalizi, Mark Schervish
On Computationally Tractable Selection of Experiments in Measurement-Constrained Regression Models
Yining Wang, Adams Wei Yu, Aarti Singh
Online Bayesian Passive-Aggressive Learning
Tianlin Shi, Jun Zhu
Online but Accurate Inference for Latent Variable Models with Local Gibbs Sampling
Christophe Dupuy, Francis Bach
Online Learning to Rank with Top-k Feedback
Sougata Chaudhuri, Ambuj Tewari