Papers
Gaussian Process Volatility Model
Yue Wu, José Miguel Hernández-Lobato, Zoubin Ghahramani
Generalized Dantzig Selector: Application to the k-support norm
Soumyadeep Chatterjee, Sheng Chen, Arindam Banerjee
Generalized Higher-Order Orthogonal Iteration for Tensor Decomposition and Completion
Yuanyuan Liu, Fanhua Shang, Wei Fan et al.
Generalized Unsupervised Manifold Alignment
Zhen Cui, Hong Chang, Shiguang Shan et al.
General Stochastic Networks for Classification
Matthias Zöhrer, Franz Pernkopf
General Table Completion using a Bayesian Nonparametric Model
Isabel Valera, Zoubin Ghahramani
Generative Adversarial Nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza et al.
Global Belief Recursive Neural Networks
Romain Paulus, Richard Socher, Christopher D. Manning
Global Sensitivity Analysis for MAP Inference in Graphical Models
Jasper De Bock, Cassio P de Campos, Alessandro Antonucci
Graph Clustering With Missing Data: Convex Algorithms and Analysis
Ramya Korlakai Vinayak, Samet Oymak, Babak Hassibi
Graphical Models for Recovering Probabilistic and Causal Queries from Missing Data
Karthika Mohan, Judea Pearl
Greedy Subspace Clustering
Dohyung Park, Constantine Caramanis, Sujay Sanghavi
Grouping-Based Low-Rank Trajectory Completion and 3D Reconstruction
Katerina Fragkiadaki, Marta Salas, Pablo Arbelaez et al.
Hamming Ball Auxiliary Sampling for Factorial Hidden Markov Models
Michalis Titsias RC AUEB, Christopher Yau
Hardness of parameter estimation in graphical models
Guy Bresler, David Gamarnik, Devavrat Shah
How hard is my MDP?" The distribution-norm to the rescue"
Odalric-Ambrym Maillard, Timothy A Mann, Shie Mannor
How transferable are features in deep neural networks?
Jason Yosinski, Jeff Clune, Yoshua Bengio et al.
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization
Yann N. Dauphin, Razvan Pascanu, Caglar Gulcehre et al.
Improved Distributed Principal Component Analysis
Yingyu Liang, Maria-Florina F Balcan, Vandana Kanchanapally et al.
Improved Multimodal Deep Learning with Variation of Information
Kihyuk Sohn, Wenling Shang, Honglak Lee
Incremental Clustering: The Case for Extra Clusters
Margareta Ackerman, Sanjoy Dasgupta
Incremental Local Gaussian Regression
Franziska Meier, Philipp Hennig, Stefan Schaal
Inference by Learning: Speeding-up Graphical Model Optimization via a Coarse-to-Fine Cascade of Pruning Classifiers
Bruno Conejo, Nikos Komodakis, Sebastien Leprince et al.
Inferring sparse representations of continuous signals with continuous orthogonal matching pursuit
Karin C Knudson, Jacob Yates, Alexander Huk et al.
Inferring synaptic conductances from spike trains with a biophysically inspired point process model
Kenneth W Latimer, E. J. Chichilnisky, Fred Rieke et al.