Papers
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation
Colin Wei, Tengyu Ma
Approximate Bayesian Inference for a Mechanistic Model of Vesicle Release at a Ribbon Synapse
Cornelius Schröder, Ben James, Leon Lagnado et al.
Nonstochastic Multiarmed Bandits with Unrestricted Delays
Tobias Sommer Thune, Nicolò Cesa-Bianchi, Yevgeny Seldin
Comparing distributions: ℓ_1 geometry improves kernel two-sample testing
meyer scetbon, Gael Varoquaux
Average Individual Fairness: Algorithms, Generalization and Experiments
Saeed Sharifi-Malvajerdi, Michael Kearns, Aaron Roth
Generalized Off-Policy Actor-Critic
Shangtong Zhang, Wendelin Boehmer, Shimon Whiteson
Adversarial Robustness through Local Linearization
Chongli Qin, James Martens, Sven Gowal et al.
Unsupervised Emergence of Egocentric Spatial Structure from Sensorimotor Prediction
Alban Laflaquière, Michael Garcia Ortiz
Efficient Pure Exploration in Adaptive Round model
Tianyuan Jin, Jieming SHI, Xiaokui Xiao et al.
Retrosynthesis Prediction with Conditional Graph Logic Network
Hanjun Dai, Chengtao Li, Connor Coley et al.
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent
Jaehoon Lee, Lechao Xiao, Samuel Schoenholz et al.
Fast Low-rank Metric Learning for Large-scale and High-dimensional Data
Han Liu, Zhizhong Han, Yu-Shen Liu et al.
Localized Structured Prediction
Carlo Ciliberto, Francis Bach, Alessandro Rudi
Combinatorial Inference against Label Noise
Paul Hongsuck Seo, Geeho Kim, Bohyung Han
DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs
Ali Sadeghian, Mohammadreza Armandpour, Patrick Ding et al.
Deep Gamblers: Learning to Abstain with Portfolio Theory
Ziyin Liu, Zhikang Wang, Paul Pu Liang et al.
Optimal Sketching for Kronecker Product Regression and Low Rank Approximation
Huaian Diao, Rajesh Jayaram, Zhao Song et al.
Learning Macroscopic Brain Connectomes via Group-Sparse Factorization
Farzane Aminmansour, Andrew Patterson, Lei Le et al.
High-dimensional multivariate forecasting with low-rank Gaussian Copula Processes
David Salinas, Michael Bohlke-Schneider, Laurent Callot et al.
Language as an Abstraction for Hierarchical Deep Reinforcement Learning
YiDing Jiang, Shixiang (Shane) Gu, Kevin P. Murphy et al.
Variational Mixture-of-Experts Autoencoders for Multi-Modal Deep Generative Models
Yuge Shi, Siddharth N, Brooks Paige et al.
Beyond the Single Neuron Convex Barrier for Neural Network Certification
Gagandeep Singh, Rupanshu Ganvir, Markus Püschel et al.
Learning Stable Deep Dynamics Models
J. Zico Kolter, Gaurav Manek
Low-Rank Bandit Methods for High-Dimensional Dynamic Pricing
Jonas W Mueller, Vasilis Syrgkanis, Matt Taddy
Implicitly learning to reason in first-order logic
Vaishak Belle, Brendan Juba