Papers
A Two-Stage Penalized Least Squares Method for Constructing Large Systems of Structural Equations
Chen Chen, Min Ren, Min Zhang et al.
auDeep: Unsupervised Learning of Representations from Audio with Deep Recurrent Neural Networks
Michael Freitag, Shahin Amiriparian, Sergey Pugachevskiy et al.
Automatic Differentiation in Machine Learning: a Survey
Atilim Gunes Baydin, Barak A. Pearlmutter, Alexey Andreyevich Radul et al.
Average Stability is Invariant to Data Preconditioning. Implications to Exp-concave Empirical Risk Minimization
Alon Gonen, Shai Shalev-Shwartz
Beyond the Hazard Rate: More Perturbation Algorithms for Adversarial Multi-armed Bandits
Zifan Li, Ambuj Tewari
Can We Trust the Bootstrap in High-dimensions? The Case of Linear Models
Noureddine El Karoui, Elizabeth Purdom
Catalyst Acceleration for First-order Convex Optimization: from Theory to Practice
Hongzhou Lin, Julien Mairal, Zaid Harchaoui
Characteristic and Universal Tensor Product Kernels
Zoltán Szabó, Bharath K. Sriperumbudur
Clustering is semidefinitely not that hard: Nonnegative SDP for manifold disentangling
Mariano Tepper, Anirvan M. Sengupta, Dmitri Chklovskii
CoCoA: A General Framework for Communication-Efficient Distributed Optimization
Virginia Smith, Simone Forte, Chenxin Ma et al.
Compact Convex Projections
Steffen Grünewälder
Complete Graphical Characterization and Construction of Adjustment Sets in Markov Equivalence Classes of Ancestral Graphs
Emilija Perković, Johannes Textor, Markus Kalisch et al.
Concentration inequalities for empirical processes of linear time series
Likai Chen, Wei Biao Wu
Connections with Robust PCA and the Role of Emergent Sparsity in Variational Autoencoder Models
Bin Dai, Yu Wang, John Aston et al.
Convergence Analysis of Distributed Inference with Vector-Valued Gaussian Belief Propagation
Jian Du, Shaodan Ma, Yik-Chung Wu et al.
Convergence of Unregularized Online Learning Algorithms
Yunwen Lei, Lei Shi, Zheng-Chu Guo
Cost-Sensitive Learning with Noisy Labels
Nagarajan Natarajan, Inderjit S. Dhillon, Pradeep Ravikumar et al.
Covariances, Robustness, and Variational Bayes
Ryan Giordano, Tamara Broderick, Michael I. Jordan
DALEX: Explainers for Complex Predictive Models in R
Przemyslaw Biecek
Deep Learning the Ising Model Near Criticality
Alan Morningstar, Roger G. Melko
Design and Analysis of the NIPS 2016 Review Process
Nihar B. Shah, Behzad Tabibian, Krikamol Muandet et al.
Distributed Proximal Gradient Algorithm for Partially Asynchronous Computer Clusters
Yi Zhou, Yingbin Liang, Yaoliang Yu et al.