Papers
DropoutNet: Addressing Cold Start in Recommender Systems
Maksims Volkovs, Guangwei Yu, Tomi Poutanen
Dual-Agent GANs for Photorealistic and Identity Preserving Profile Face Synthesis
Jian Zhao, Lin Xiong, Panasonic Karlekar Jayashree et al.
Dual Discriminator Generative Adversarial Nets
Tu Nguyen, Trung Le, Hung Vu et al.
Dualing GANs
Yujia Li, Alexander Schwing, Kuan-Chieh Wang et al.
Dual Path Networks
Yunpeng Chen, Jianan Li, Huaxin Xiao et al.
Dynamic-Depth Context Tree Weighting
Joao V Messias, Shimon Whiteson
Dynamic Importance Sampling for Anytime Bounds of the Partition Function
Qi Lou, Rina Dechter, Alex Ihler
Dynamic Revenue Sharing
Santiago Balseiro, Max Lin, Vahab Mirrokni et al.
Dynamic Routing Between Capsules
Sara Sabour, Nicholas Frosst, Geoffrey E. Hinton
Dynamic Safe Interruptibility for Decentralized Multi-Agent Reinforcement Learning
El Mahdi El Mhamdi, Rachid Guerraoui, Hadrien Hendrikx et al.
Early stopping for kernel boosting algorithms: A general analysis with localized complexities
Yuting Wei, Fanny Yang, Martin J. Wainwright
EEG-GRAPH: A Factor-Graph-Based Model for Capturing Spatial, Temporal, and Observational Relationships in Electroencephalograms
Yogatheesan Varatharajah, Min Jin Chong, Krishnakant Saboo et al.
Effective Parallelisation for Machine Learning
Michael Kamp, Mario Boley, Olana Missura et al.
Efficient and Flexible Inference for Stochastic Systems
Stefan Bauer, Nico S Gorbach, Djordje Miladinovic et al.
Efficient Approximation Algorithms for Strings Kernel Based Sequence Classification
Muhammad Farhan, Juvaria Tariq, Arif Zaman et al.
Efficient Modeling of Latent Information in Supervised Learning using Gaussian Processes
Zhenwen Dai, Mauricio Álvarez, Neil Lawrence
Efficient Optimization for Linear Dynamical Systems with Applications to Clustering and Sparse Coding
Wenbing Huang, Mehrtash Harandi, Tong Zhang et al.
Efficient Second-Order Online Kernel Learning with Adaptive Embedding
Daniele Calandriello, Alessandro Lazaric, Michal Valko
Efficient Sublinear-Regret Algorithms for Online Sparse Linear Regression with Limited Observation
Shinji Ito, Daisuke Hatano, Hanna Sumita et al.
Efficient Use of Limited-Memory Accelerators for Linear Learning on Heterogeneous Systems
Celestine Dünner, Thomas Parnell, Martin Jaggi
Eigen-Distortions of Hierarchical Representations
Alexander Berardino, Valero Laparra, Johannes Ballé et al.
Eigenvalue Decay Implies Polynomial-Time Learnability for Neural Networks
Surbhi Goel, Adam Klivans
Elementary Symmetric Polynomials for Optimal Experimental Design
Zelda E. Mariet, Suvrit Sra