Papers
Distributional reinforcement learning with linear function approximation
Marc G. Bellemare, Nicolas Le Roux, Pablo Samuel Castro et al.
Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features
Arno Solin, Manon Kok
Improving the Stability of the Knockoff Procedure: Multiple Simultaneous Knockoffs and Entropy Maximization
Jaime Roquero Gimenez, James Zou
Multi-Task Time Series Analysis applied to Drug Response Modelling
Alex Bird, Chris Williams, Christopher Hawthorne
Learning Controllable Fair Representations
Jiaming Song, Pratyusha Kalluri, Aditya Grover et al.
Risk-Sensitive Generative Adversarial Imitation Learning
Jonathan Lacotte, Mohammad Ghavamzadeh, Yinlam Chow et al.
Regularized Contextual Bandits
Xavier Fontaine, Quentin Berthet, Vianney Perchet
Training Variational Autoencoders with Buffered Stochastic Variational Inference
Rui Shu, Hung Bui, Jay Whang et al.
Knockoffs for the Mass: New Feature Importance Statistics with False Discovery Guarantees
Jaime Roquero Gimenez, Amirata Ghorbani, James Zou
The non-parametric bootstrap and spectral analysis in moderate and high-dimension
Noureddine El Karoui, Elizabeth Purdom
Safe Convex Learning under Uncertain Constraints
Ilnura Usmanova, Andreas Krause, Maryam Kamgarpour
Noisy Blackbox Optimization using Multi-fidelity Queries: A Tree Search Approach
Rajat Sen, Kirthevasan Kandasamy, Sanjay Shakkottai
On Euclidean k-Means Clustering with alpha-Center Proximity
Amit Deshpande, Anand Louis, Apoorv Singh
Distributed Maximization of "Submodular plus Diversity" Functions for Multi-label Feature Selection on Huge Datasets
Mehrdad Ghadiri, Mark Schmidt
Test without Trust: Optimal Locally Private Distribution Testing
Jayadev Acharya, Clement Canonne, Cody Freitag et al.
Provable Robustness of ReLU networks via Maximization of Linear Regions
Francesco Croce, Maksym Andriushchenko, Matthias Hein
Projection-Free Bandit Convex Optimization
Lin Chen, Mingrui Zhang, Amin Karbasi
Renyi Differentially Private ERM for Smooth Objectives
Chen Chen, Jaewoo Lee, Dan Kifer
Variational Information Planning for Sequential Decision Making
Jason Pacheco, John Fisher
Bounding Inefficiency of Equilibria in Continuous Actions Games using Submodularity and Curvature
Pier Giuseppe Sessa, Maryam Kamgarpour, Andreas Krause
Implicit Kernel Learning
Chun-Liang Li, Wei-Cheng Chang, Youssef Mroueh et al.
Gaussian Process Modulated Cox Processes under Linear Inequality Constraints
Andrés F. Lopez-Lopera, ST John, Nicolas Durrande
Bridging the gap between regret minimization and best arm identification, with application to A/B tests
Rémy Degenne, Thomas Nedelec, Clement Calauzenes et al.
Lovasz Convolutional Networks
Prateek Yadav, Madhav Nimishakavi, Naganand Yadati et al.
Non-linear process convolutions for multi-output Gaussian processes
Mauricio A. Alvarez, Wil Ward, Cristian Guarnizo