Papers
Learning From Small Samples: An Analysis of Simple Decision Heuristics
Ozgur Simsek, Marcus Buckmann
Learning Large-Scale Poisson DAG Models based on OverDispersion Scoring
Gunwoong Park, Garvesh Raskutti
Learning spatiotemporal trajectories from manifold-valued longitudinal data
Jean-Baptiste SCHIRATTI, Stéphanie ALLASSONNIERE, Olivier Colliot et al.
Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels
Felipe Tobar, Thang D Bui, Richard E Turner
Learning structured densities via infinite dimensional exponential families
Siqi Sun, Mladen Kolar, Jinbo Xu
Learning Structured Output Representation using Deep Conditional Generative Models
Kihyuk Sohn, Honglak Lee, Xinchen Yan
Learning Theory and Algorithms for Forecasting Non-stationary Time Series
Vitaly Kuznetsov, Mehryar Mohri
Learning to Linearize Under Uncertainty
Ross Goroshin, Michael F Mathieu, Yann LeCun
Learning to Segment Object Candidates
Pedro O O. Pinheiro, Ronan Collobert, Piotr Dollar
Learning to Transduce with Unbounded Memory
Edward Grefenstette, Karl Moritz Hermann, Mustafa Suleyman et al.
Learning visual biases from human imagination
Carl Vondrick, Hamed Pirsiavash, Aude Oliva et al.
Learning Wake-Sleep Recurrent Attention Models
Jimmy Ba, Ruslan Salakhutdinov, Roger B Grosse et al.
Learning with a Wasserstein Loss
Charlie Frogner, Chiyuan Zhang, Hossein Mobahi et al.
Learning with Group Invariant Features: A Kernel Perspective.
Youssef Mroueh, Stephen Voinea, Tomaso A Poggio
Learning with Incremental Iterative Regularization
Lorenzo Rosasco, Silvia Villa
Learning with Relaxed Supervision
Jacob Steinhardt, Percy Liang
Learning with Symmetric Label Noise: The Importance of Being Unhinged
Brendan van Rooyen, Aditya Menon, Robert C. Williamson
Less is More: Nyström Computational Regularization
Alessandro Rudi, Raffaello Camoriano, Lorenzo Rosasco
Lifelong Learning with Non-i.i.d. Tasks
Anastasia Pentina, Christoph H. Lampert
Lifted Inference Rules With Constraints
Happy Mittal, Anuj Mahajan, Vibhav G Gogate et al.
Lifted Symmetry Detection and Breaking for MAP Inference
Timothy Kopp, Parag Singla, Henry Kautz
Linear Multi-Resource Allocation with Semi-Bandit Feedback
Tor Lattimore, Koby Crammer, Csaba Szepesvari
Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes
Ryan J Giordano, Tamara Broderick, Michael I Jordan
Local Causal Discovery of Direct Causes and Effects
Tian Gao, Qiang Ji
Local Expectation Gradients for Black Box Variational Inference
Michalis Titsias RC AUEB, Miguel Lázaro-Gredilla