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Theory

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Papers

Reduced Space and Faster Convergence in Imperfect-Information Games via Pruning ICML 2017
Strong NP-Hardness for Sparse Optimization with Concave Penalty Functions ICML 2017
On Relaxing Determinism in Arithmetic Circuits ICML 2017
Consistency Analysis for Binary Classification Revisited ICML 2017
No Spurious Local Minima in Nonconvex Low Rank Problems: A Unified Geometric Analysis ICML 2017
Dissipativity Theory for Nesterov’s Accelerated Method ICML 2017
Fairness in Reinforcement Learning ICML 2017
Contextual Decision Processes with low Bellman rank are PAC-Learnable ICML 2017
How to Escape Saddle Points Efficiently ICML 2017
An Adaptive Test of Independence with Analytic Kernel Embeddings ICML 2017
Cost-Optimal Learning of Causal Graphs ICML 2017
Understanding Black-box Predictions via Influence Functions ICML 2017
Convergence Analysis of Proximal Gradient with Momentum for Nonconvex Optimization ICML 2017
Algorithmic Stability and Hypothesis Complexity ICML 2017
Spherical Structured Feature Maps for Kernel Approximation ICML 2017
Tight Bounds for Approximate Carathéodory and Beyond ICML 2017
The Loss Surface of Deep and Wide Neural Networks ICML 2017
Geometry of Neural Network Loss Surfaces via Random Matrix Theory ICML 2017
On the Expressive Power of Deep Neural Networks ICML 2017
Analytical Guarantees on Numerical Precision of Deep Neural Networks ICML 2017
On the Iteration Complexity of Support Recovery via Hard Thresholding Pursuit ICML 2017
Neural Networks and Rational Functions ICML 2017
Evaluating the Variance of Likelihood-Ratio Gradient Estimators ICML 2017
Unifying Task Specification in Reinforcement Learning ICML 2017
Learning Latent Space Models with Angular Constraints ICML 2017