Papers
Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design
Kevin K. Yang, Yuxin Chen, Alycia Lee et al.
Bayesian Learning of Conditional Kernel Mean Embeddings for Automatic Likelihood-Free Inference
Kelvin Hsu, Fabio Ramos
Bayesian Learning of Neural Network Architectures
Georgi Dikov, Justin Bayer
Bayesian optimisation under uncertain inputs
Rafael Oliveira, Lionel Ott, Fabio Ramos
Bernoulli Race Particle Filters
Sebastian M. Schmon, Arnaud Doucet, George Deligiannidis
Best of many worlds: Robust model selection for online supervised learning
Vidya Muthukumar, Mitas Ray, Anant Sahai et al.
Binary Space Partitioning Forest
Xuhui Fan, Bin Li, Scott SIsson
Black Box Quantiles for Kernel Learning
Anthony Tompkins, Ransalu Senanayake, Philippe Morere et al.
Blind Demixing via Wirtinger Flow with Random Initialization
Jialin Dong, Yuanming Shi
Block Stability for MAP Inference
Hunter Lang, David Sontag, Aravindan Vijayaraghavan
Boosting Transfer Learning with Survival Data from Heterogeneous Domains
Alexis Bellot, Mihaela van der Schaar
Bounding Inefficiency of Equilibria in Continuous Actions Games using Submodularity and Curvature
Pier Giuseppe Sessa, Maryam Kamgarpour, Andreas Krause
Bridging the gap between regret minimization and best arm identification, with application to A/B tests
Rémy Degenne, Thomas Nedelec, Clement Calauzenes et al.
Calibrating Deep Convolutional Gaussian Processes
Gia-Lac Tran, Edwin V. Bonilla, John Cunningham et al.
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning
Peter Schulam, Suchi Saria
Causal Discovery in the Presence of Missing Data
Ruibo Tu, Cheng Zhang, Paul Ackermann et al.
Classification using margin pursuit
Matthew J. Holland
Classifying Signals on Irregular Domains via Convolutional Cluster Pooling
Angelo Porrello, Davide Abati, Simone Calderara et al.
Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach
Alexander Lin, Yingzhuo Zhang, Jeremy Heng et al.
Complexities in Projection-Free Stochastic Non-convex Minimization
Zebang Shen, Cong Fang, Peilin Zhao et al.
Computation Efficient Coded Linear Transform
Sinong Wang, Jiashang Liu, Ness Shroff et al.
Conditionally Independent Multiresolution Gaussian Processes
Jalil Taghia, Thomas Schön
Conditional Sparse $L_p$-norm Regression With Optimal Probability
John Hainline, Brendan Juba, Hai S. Le et al.
Confidence-based Graph Convolutional Networks for Semi-Supervised Learning
Shikhar Vashishth, Prateek Yadav, Manik Bhandari et al.
Confidence Scoring Using Whitebox Meta-models with Linear Classifier Probes
Tongfei Chen, Jiri Navratil, Vijay Iyengar et al.