Papers
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
Distributed and Provably Good Seedings for k-Means in Constant Rounds
Olivier Bachem, Mario Lucic, Andreas Krause
Distributed Batch Gaussian Process Optimization
Erik A. Daxberger, Bryan Kian Hsiang Low
Distributed Mean Estimation with Limited Communication
Ananda Theertha Suresh, Felix X. Yu, Sanjiv Kumar et al.
Doubly Accelerated Methods for Faster CCA and Generalized Eigendecomposition
Zeyuan Allen-Zhu, Yuanzhi Li
Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization
Qi Lei, Ian En-Hsu Yen, Chao-yuan Wu et al.
Dropout Inference in Bayesian Neural Networks with Alpha-divergences
Yingzhen Li, Yarin Gal
Dual Iterative Hard Thresholding: From Non-convex Sparse Minimization to Non-smooth Concave Maximization
Bo Liu, Xiao-Tong Yuan, Lezi Wang et al.
Dual Supervised Learning
Yingce Xia, Tao Qin, Wei Chen et al.
Dueling Bandits with Weak Regret
Bangrui Chen, Peter I. Frazier