Papers
Deep IV: A Flexible Approach for Counterfactual Prediction
Jason Hartford, Greg Lewis, Kevin Leyton-Brown et al.
Deep Latent Dirichlet Allocation with Topic-Layer-Adaptive Stochastic Gradient Riemannian MCMC
Yulai Cong, Bo Chen, Hongwei Liu et al.
Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction
Wen Sun, Arun Venkatraman, Geoffrey J. Gordon et al.
Deep Spectral Clustering Learning
Marc T. Law, Raquel Urtasun, Richard S. Zemel
Deep Tensor Convolution on Multicores
David Budden, Alexander Matveev, Shibani Santurkar et al.
Deep Transfer Learning with Joint Adaptation Networks
Mingsheng Long, Han Zhu, Jianmin Wang et al.
Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs
Michael Gygli, Mohammad Norouzi, Anelia Angelova
Deep Voice: Real-time Neural Text-to-Speech
Sercan Ö. Arık, Mike Chrzanowski, Adam Coates et al.
Deletion-Robust Submodular Maximization: Data Summarization with “the Right to be Forgotten”
Baharan Mirzasoleiman, Amin Karbasi, Andreas Krause
Delta Networks for Optimized Recurrent Network Computation
Daniel Neil, Jun Haeng Lee, Tobi Delbruck et al.
Density Level Set Estimation on Manifolds with DBSCAN
Heinrich Jiang
Depth-Width Tradeoffs in Approximating Natural Functions with Neural Networks
Itay Safran, Ohad Shamir
Deriving Neural Architectures from Sequence and Graph Kernels
Tao Lei, Wengong Jin, Regina Barzilay et al.
Developing Bug-Free Machine Learning Systems With Formal Mathematics
Daniel Selsam, Percy Liang, David L. Dill
Device Placement Optimization with Reinforcement Learning
Azalia Mirhoseini, Hieu Pham, Quoc V. Le et al.
Diameter-Based Active Learning
Christopher Tosh, Sanjoy Dasgupta
Dictionary Learning Based on Sparse Distribution Tomography
Pedram Pad, Farnood Salehi, Elisa Celis et al.
Differentiable Programs with Neural Libraries
Alexander L. Gaunt, Marc Brockschmidt, Nate Kushman et al.
Differentially Private Chi-squared Test by Unit Circle Mechanism
Kazuya Kakizaki, Kazuto Fukuchi, Jun Sakuma
Differentially Private Clustering in High-Dimensional Euclidean Spaces
Maria-Florina Balcan, Travis Dick, Yingyu Liang et al.
Differentially Private Learning of Undirected Graphical Models Using Collective Graphical Models
Garrett Bernstein, Ryan McKenna, Tao Sun et al.
Differentially Private Submodular Maximization: Data Summarization in Disguise
Marko Mitrovic, Mark Bun, Andreas Krause et al.
Discovering Discrete Latent Topics with Neural Variational Inference
Yishu Miao, Edward Grefenstette, Phil Blunsom
Dissipativity Theory for Nesterov’s Accelerated Method
Bin Hu, Laurent Lessard