Papers
Distributed, partially collapsed MCMC for Bayesian Nonparametrics
Kumar Avinava Dubey, Michael Zhang, Eric Xing et al.
Distributionally Robust Bayesian Optimization
Johannes Kirschner, Ilija Bogunovic, Stefanie Jegelka et al.
Distributionally Robust Bayesian Quadrature Optimization
Thanh Nguyen, Sunil Gupta, Huong Ha et al.
Distributionally Robust Formulation and Model Selection for the Graphical Lasso
Pedro Cisneros-Velarde, Alexander Petersen, Sang-Yun Oh
Domain-Liftability of Relational Marginal Polytopes
Ondrej Kuzelka, Yuyi Wang
Doubly Sparse Variational Gaussian Processes
Vincent Adam, Stefanos Eleftheriadis, Artem Artemev et al.
Dynamic content based ranking
Seppo Virtanen, Mark Girolami
DYNOTEARS: Structure Learning from Time-Series Data
Roxana Pamfil, Nisara Sriwattanaworachai, Shaan Desai et al.
Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy
Majid Jahani, Xi He, Chenxin Ma et al.
Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning
Tianyu Li, Bogdan Mazoure, Doina Precup et al.
Efficient Spectrum-Revealing CUR Matrix Decomposition
Cheng Chen, Ming Gu, Zhihua Zhang et al.
Elimination of All Bad Local Minima in Deep Learning
Kenji Kawaguchi, Leslie Kaelbling
EM Converges for a Mixture of Many Linear Regressions
Jeongyeol Kwon, Constantine Caramanis
Enriched mixtures of generalised Gaussian process experts
Charles Gadd, Sara Wade, Alexis Boukouvalas
Ensemble Gaussian Processes with Spectral Features for Online Interactive Learning with Scalability
Qin Lu, Georgios Karanikolas, Yanning Shen et al.
Entropy Weighted Power k-Means Clustering
Saptarshi Chakraborty, Debolina Paul, Swagatam Das et al.
Equalized odds postprocessing under imperfect group information
Pranjal Awasthi, Matthäus Kleindessner, Jamie Morgenstern
Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions
Kamiar Rahnama Rad, Wenda Zhou, Arian Maleki
Explaining the Explainer: A First Theoretical Analysis of LIME
Damien Garreau, Ulrike Luxburg
Explicit Mean-Square Error Bounds for Monte-Carlo and Linear Stochastic Approximation
Shuhang Chen, Adithya Devraj, Ana Busic et al.
Expressiveness and Learning of Hidden Quantum Markov Models
Sandesh Adhikary, Siddarth Srinivasan, Geoff Gordon et al.
Fair Correlation Clustering
Sara Ahmadian, Alessandro Epasto, Ravi Kumar et al.
Fair Decisions Despite Imperfect Predictions
Niki Kilbertus, Manuel Gomez Rodriguez, Bernhard Schölkopf et al.