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optimization landscape

39 papers

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Co-occurring keywords

neural network (6616) neural network optimization (1293) gradient descent (1144) local minimum (61) local minima (39) policy gradient (520) non-convex optimization (547) loss landscape (149) hessian matrix (33) convolutional neural network (4226)

Papers

Language-Based Bayesian Optimization Research Assistant (BORA) IJCAI 2025
On Convergence in Wasserstein Distance and f-divergence Minimization Problems AISTATS 2024
The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof NIPS 2024
Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems NIPS 2023
Geometric Analysis of Matrix Sensing over Graphs NIPS 2023
Fractal Landscapes in Policy Optimization NIPS 2023
Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Method NIPS 2023
Demystify the Gravity Well in the Optimization Landscape (Student Abstract) AAAI 2023
Blessing of Depth in Linear Regression: Deeper Models Have Flatter Landscape Around the True Solution NIPS 2022
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features ICML 2022
Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments ICML 2022
Annihilation of Spurious Minima in Two-Layer ReLU Networks NIPS 2022
Inductive Matrix Completion: No Bad Local Minima and a Fast Algorithm ICML 2022
On the Stability Properties and the Optimization Landscape of Training Problems with Squared Loss for Neural Networks and General Nonlinear Conic Approximation Schemes JMLR 2021
The Effects of Mild Over-parameterization on the Optimization Landscape of Shallow ReLU Neural Networks COLT 2021
Analysis of the Optimization Landscape of Linear Quadratic Gaussian (LQG) Control L4DC 2021
When Expressivity Meets Trainability: Fewer than $n$ Neurons Can Work NIPS 2021
Sparse linear networks with a fixed butterfly structure: theory and practice UAI 2021
What Deep CNNs Benefit From Global Covariance Pooling: An Optimization Perspective CVPR 2020
Optimization Theory for ReLU Neural Networks Trained with Normalization Layers ICML 2020
Analytic Characterization of the Hessian in Shallow ReLU Models: A Tale of Symmetry NIPS 2020
Learning to Forget for Meta-Learning CVPR 2020
How many samples is a good initial point worth in Low-rank Matrix Recovery? NIPS 2020
Global Guarantees for Blind Demodulation with Generative Priors NIPS 2019
Understanding the Impact of Entropy on Policy Optimization ICML 2019