Papers
Discriminative Unsupervised Feature Learning with Convolutional Neural Networks
Alexey Dosovitskiy, Jost Tobias Springenberg, Martin Riedmiller et al.
Distance-Based Network Recovery under Feature Correlation
David Adametz, Volker Roth
Distributed Balanced Clustering via Mapping Coresets
Mohammadhossein Bateni, Aditya Bhaskara, Silvio Lattanzi et al.
Distributed Bayesian Posterior Sampling via Moment Sharing
Minjie Xu, Balaji Lakshminarayanan, Yee Whye Teh et al.
Distributed Estimation, Information Loss and Exponential Families
Qiang Liu, Alex Ihler
Distributed Parameter Estimation in Probabilistic Graphical Models
Yariv D Mizrahi, Misha Denil, Nando de Freitas
Distributed Power-law Graph Computing: Theoretical and Empirical Analysis
Cong Xie, Ling Yan, Wu-Jun Li et al.
Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models
Yarin Gal, Mark van der Wilk, Carl Edward Rasmussen
Diverse Randomized Agents Vote to Win
Albert Jiang, Leandro Soriano Marcolino, Ariel D Procaccia et al.
Diverse Sequential Subset Selection for Supervised Video Summarization
Boqing Gong, Wei-Lun Chao, Kristen Grauman et al.
Divide-and-Conquer Learning by Anchoring a Conical Hull
Tianyi Zhou, Jeff A. Bilmes, Carlos Guestrin
Do Convnets Learn Correspondence?
Jonathan L Long, Ning Zhang, Trevor Darrell
Do Deep Nets Really Need to be Deep?
Jimmy Ba, Rich Caruana
Dynamic Rank Factor Model for Text Streams
Shaobo Han, Lin Du, Esther Salazar et al.
Efficient Inference of Continuous Markov Random Fields with Polynomial Potentials
Shenlong Wang, Alex Schwing, Raquel Urtasun
Efficient learning by implicit exploration in bandit problems with side observations
Tomáš Kocák, Gergely Neu, Michal Valko et al.
Efficient Minimax Signal Detection on Graphs
Jing Qian, Venkatesh Saligrama
Efficient Minimax Strategies for Square Loss Games
Wouter M. Koolen, Alan Malek, Peter L Bartlett
Efficient Optimization for Average Precision SVM
Pritish Mohapatra, C.V. Jawahar, M. Pawan Kumar
Efficient Partial Monitoring with Prior Information
Hastagiri P Vanchinathan, Gábor Bartók, Andreas Krause
Efficient Sampling for Learning Sparse Additive Models in High Dimensions
Hemant Tyagi, Bernd Gärtner, Andreas Krause
Efficient Structured Matrix Rank Minimization
Adams Wei Yu, Wanli Ma, Yaoliang Yu et al.
Elementary Estimators for Graphical Models
Eunho Yang, Aurelie C. Lozano, Pradeep K Ravikumar
Encoding High Dimensional Local Features by Sparse Coding Based Fisher Vectors
Lingqiao Liu, Chunhua Shen, Lei Wang et al.
Estimation with Norm Regularization
Arindam Banerjee, Sheng Chen, Farideh Fazayeli et al.