local minimum

Maximum-and-Concatenation Networks ICML 2020 On the Distribution of Minima in Intrinsic-Metric Rotation Averaging CVPR 2020 Stochastic Recursive Variance-Reduced Cubic Regularization Methods AISTATS 2020 The Usual Suspects? Reassessing Blame for VAE Posterior Collapse ICML 2020 Truth or backpropaganda? An empirical investigation of deep learning theory ICLR 2020 Understanding the Role of Training Regimes in Continual Learning NeurIPS 2020 Are deep ResNets provably better than linear predictors? NeurIPS 2019 Asymmetric Valleys: Beyond Sharp and Flat Local Minima NeurIPS 2019 Comparing EM with GD in Mixture Models of Two Components UAI 2019 Differentially Private Empirical Risk Minimization with Non-convex Loss Functions ICML 2019 How degenerate is the parametrization of neural networks with the ReLU activation function? NeurIPS 2019 Model-free Nonconvex Matrix Completion: Local Minima Analysis and Applications in Memory-efficient Kernel PCA JMLR 2019 No Pressure! Addressing the Problem of Local Minima in Manifold Learning Algorithms NeurIPS 2019 On the loss landscape of a class of deep neural networks with no bad local valleys ICLR 2019 Piecewise Strong Convexity of Neural Networks NeurIPS 2019 Recovery Guarantees For Quadratic Tensors With Sparse Observations AISTATS 2019 Small nonlinearities in activation functions create bad local minima in neural networks ICLR 2019 Adding One Neuron Can Eliminate All Bad Local Minima NeurIPS 2018 An Alternative View: When Does SGD Escape Local Minima? ICML 2018 Are ResNets Provably Better than Linear Predictors? NeurIPS 2018 Critical Percolation as a Framework to Analyze the Training of Deep Networks ICLR 2018 Deep Linear Networks with Arbitrary Loss: All Local Minima Are Global ICML 2018 How To Make the Gradients Small Stochastically: Even Faster Convex and Nonconvex SGD NeurIPS 2018 NEON2: Finding Local Minima via First-Order Oracles NeurIPS 2018 Non-Convex Matrix Completion Against a Semi-Random Adversary COLT 2018