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Theory

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Papers

Learning Deep ResNet Blocks Sequentially using Boosting Theory ICML 2018
Topological mixture estimation ICML 2018
Deep Density Destructors ICML 2018
Residual Unfairness in Fair Machine Learning from Prejudiced Data ICML 2018
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness ICML 2018
On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups ICML 2018
Data-Dependent Stability of Stochastic Gradient Descent ICML 2018
Deep Linear Networks with Arbitrary Loss: All Local Minima Are Global ICML 2018
The Multilinear Structure of ReLU Networks ICML 2018
On the Limitations of First-Order Approximation in GAN Dynamics ICML 2018
On the Spectrum of Random Features Maps of High Dimensional Data ICML 2018
Towards Black-box Iterative Machine Teaching ICML 2018
Delayed Impact of Fair Machine Learning ICML 2018
Open Category Detection with PAC Guarantees ICML 2018
PDE-Net: Learning PDEs from Data ICML 2018
The Edge Density Barrier: Computational-Statistical Tradeoffs in Combinatorial Inference ICML 2018
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations ICML 2018
Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion ICML 2018
Bounds on the Approximation Power of Feedforward Neural Networks ICML 2018
Dropout Training, Data-dependent Regularization, and Generalization Bounds ICML 2018
Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions ICML 2018
Is Generator Conditioning Causally Related to GAN Performance? ICML 2018
Deep One-Class Classification ICML 2018
Learning with Abandonment ICML 2018
Learning the Reward Function for a Misspecified Model ICML 2018