Papers
Coresets for k-Segmentation of Streaming Data
Guy Rosman, Mikhail Volkov, Dan Feldman et al.
Covariance shrinkage for autocorrelated data
Daniel Bartz, Klaus-Robert Müller
Decomposing Parameter Estimation Problems
Khaled S Refaat, Arthur Choi, Adnan Darwiche
Deconvolution of High Dimensional Mixtures via Boosting, with Application to Diffusion-Weighted MRI of Human Brain
Charles Y Zheng, Franco Pestilli, Ariel Rokem
Decoupled Variational Gaussian Inference
Mohammad Emtiyaz Khan
Deep Convolutional Neural Network for Image Deconvolution
Li Xu, Jimmy SJ Ren, Ce Liu et al.
Deep Fragment Embeddings for Bidirectional Image Sentence Mapping
Andrej Karpathy, Armand Joulin, Li F Fei-Fei
Deep Joint Task Learning for Generic Object Extraction
Xiaolong Wang, Liliang Zhang, Liang Lin et al.
Deep Learning Face Representation by Joint Identification-Verification
Yi Sun, Yuheng Chen, Xiaogang Wang et al.
Deep Learning for Real-Time Atari Game Play Using Offline Monte-Carlo Tree Search Planning
Xiaoxiao Guo, Satinder Singh, Honglak Lee et al.
Deep Networks with Internal Selective Attention through Feedback Connections
Marijn F Stollenga, Jonathan Masci, Faustino Gomez et al.
Deep Recursive Neural Networks for Compositionality in Language
Ozan Irsoy, Claire Cardie
Deep Symmetry Networks
Robert Gens, Pedro M Domingos
Delay-Tolerant Algorithms for Asynchronous Distributed Online Learning
Brendan McMahan, Matthew Streeter
Dependent nonparametric trees for dynamic hierarchical clustering
Kumar Avinava Dubey, Qirong Ho, Sinead A Williamson et al.
Depth Map Prediction from a Single Image using a Multi-Scale Deep Network
David Eigen, Christian Puhrsch, Rob Fergus
Design Principles of the Hippocampal Cognitive Map
Kimberly L Stachenfeld, Matthew Botvinick, Samuel J Gershman
Deterministic Symmetric Positive Semidefinite Matrix Completion
William E Bishop, Byron M. Yu
DFacTo: Distributed Factorization of Tensors
Joon Hee Choi, S. Vishwanathan
Difference of Convex Functions Programming for Reinforcement Learning
Bilal Piot, Matthieu Geist, Olivier Pietquin
Dimensionality Reduction with Subspace Structure Preservation
Devansh Arpit, Ifeoma Nwogu, Venu Govindaraju
Discovering, Learning and Exploiting Relevance
Cem Tekin, Mihaela van der Schaar
Discovering Structure in High-Dimensional Data Through Correlation Explanation
Greg Ver Steeg, Aram Galstyan
Discrete Graph Hashing
Wei Liu, Cun Mu, Sanjiv Kumar et al.
Discriminative Metric Learning by Neighborhood Gerrymandering
Shubhendu Trivedi, David Mcallester, Greg Shakhnarovich