Papers
Discovering and Exploiting Additive Structure for Bayesian Optimization
Jacob Gardner, Chuan Guo, Kilian Weinberger et al.
Learning the Network Structure of Heterogeneous Data via Pairwise Exponential Markov Random Fields
Youngsuk Park, David Hallac, Stephen Boyd et al.
Signal-based Bayesian Seismic Monitoring
David Moore, Stuart Russell
Learning Structured Weight Uncertainty in Bayesian Neural Networks
Shengyang Sun, Changyou Chen, Lawrence Carin
Communication-Efficient Learning of Deep Networks from Decentralized Data
Brendan McMahan, Eider Moore, Daniel Ramage et al.
Prediction Performance After Learning in Gaussian Process Regression
Johan Wagberg, Dave Zachariah, Thomas Schon et al.
Fast Classification with Binary Prototypes
Kai Zhong, Ruiqi Guo, Sanjiv Kumar et al.
Thompson Sampling for Linear-Quadratic Control Problems
Marc Abeille, Alessandro Lazaric
Relativistic Monte Carlo
Xiaoyu Lu, Valerio Perrone, Leonard Hasenclever et al.
Local Group Invariant Representations via Orbit Embeddings
Anant Raj, Abhishek Kumar, Youssef Mroueh et al.
Diverse Neural Network Learns True Target Functions
Bo Xie, Yingyu Liang, Le Song
Compressed Least Squares Regression revisited
Martin Slawski
Modal-set estimation with an application to clustering
Heinrich Jiang, Samory Kpotufe
Sketchy Decisions: Convex Low-Rank Matrix Optimization with Optimal Storage
Alp Yurtsever, Madeleine Udell, Joel Tropp et al.
Communication-efficient Distributed Sparse Linear Discriminant Analysis
Lu Tian, Quanquan Gu
A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models
Beilun Wang, Ji Gao, Yanjun Qi
Finite-sum Composition Optimization via Variance Reduced Gradient Descent
Xiangru Lian, Mengdi Wang, Ji Liu
Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data
Jialei Wang, Jason Lee, Mehrdad Mahdavi et al.
Belief Propagation in Conditional RBMs for Structured Prediction
Wei Ping, Alex Ihler
Tracking Objects with Higher Order Interactions via Delayed Column Generation
Shaofei Wang, Steffen Wolf, Charless Fowlkes et al.
Identifying Groups of Strongly Correlated Variables through Smoothed Ordered Weighted L_1-norms
Raman Sankaran, Francis Bach, Chiranjib Bhattacharya
Optimistic Planning for the Stochastic Knapsack Problem
Ciara Pike-Burke, Steffen Grunewalder
Learning with Feature Feedback: from Theory to Practice
Stefanos Poulis, Sanjoy Dasgupta
Generalization Error of Invariant Classifiers
Jure Sokolic, Raja Giryes, Guillermo Sapiro et al.