Theory

On the Correctness and Sample Complexity of Inverse Reinforcement Learning NeurIPS 2019 On the equivalence between graph isomorphism testing and function approximation with GNNs NeurIPS 2019 On the Expressive Power of Deep Polynomial Neural Networks NeurIPS 2019 On the Hardness of Probabilistic Inference Relaxations AAAI 2019 On the Hardness of Robust Classification NeurIPS 2019 On the Inducibility of Stackelberg Equilibrium for Security Games AAAI 2019 On the Inductive Bias of Neural Tangent Kernels NeurIPS 2019 On the Integration of CP-nets in ASPRIN IJCAI 2019 On the Limitations of Representing Functions on Sets ICML 2019 On the loss landscape of a class of deep neural networks with no bad local valleys ICLR 2019 On the number of variables to use in principal component regression NeurIPS 2019 On the Persistence of Clustering Solutions and True Number of Clusters in a Dataset AAAI 2019 On the Problem of Assigning PhD Grants IJCAI 2019 On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length ICLR 2019 On the Relationship Between Satisfiability and Markov Decision Processes UAI 2019 On the Sensitivity of Adversarial Robustness to Input Data Distributions ICLR 2019 On the Structural Sensitivity of Deep Convolutional Networks to the Directions of Fourier Basis Functions CVPR 2019 On the Turing Completeness of Modern Neural Network Architectures ICLR 2019 On the Universal Approximability and Complexity Bounds of Quantized ReLU Neural Networks ICLR 2019 On the Universality of Invariant Networks ICML 2019 On the Value of Target Data in Transfer Learning NeurIPS 2019 On Tractable Computation of Expected Predictions NeurIPS 2019 Open Problem: Monotonicity of Learning COLT 2019 Open Problem: The Oracle Complexity of Convex Optimization with Limited Memory COLT 2019 Optimal Average-Case Reductions to Sparse PCA: From Weak Assumptions to Strong Hardness COLT 2019