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Optimization

14,983 papers

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Papers

Sparse Tensor Additive Regression JMLR 2021
Approximate Newton Methods JMLR 2021
Path Length Bounds for Gradient Descent and Flow JMLR 2021
Optimization with Momentum: Dynamical, Control-Theoretic, and Symplectic Perspectives JMLR 2021
Kernel Operations on the GPU, with Autodiff, without Memory Overflows JMLR 2021
POT: Python Optimal Transport JMLR 2021
Communication-Efficient Distributed Covariance Sketch, with Application to Distributed PCA JMLR 2021
PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings JMLR 2021
Gradient Methods Never Overfit On Separable Data JMLR 2021
Risk Bounds for Unsupervised Cross-Domain Mapping with IPMs JMLR 2021
Safe Policy Iteration: A Monotonically Improving Approximate Policy Iteration Approach JMLR 2021
A Unified Analysis of First-Order Methods for Smooth Games via Integral Quadratic Constraints JMLR 2021
Online stochastic gradient descent on non-convex losses from high-dimensional inference JMLR 2021
L-SVRG and L-Katyusha with Arbitrary Sampling JMLR 2021
A Lyapunov Analysis of Accelerated Methods in Optimization JMLR 2021
Stochastic Proximal Methods for Non-Smooth Non-Convex Constrained Sparse Optimization JMLR 2021
Some Theoretical Insights into Wasserstein GANs JMLR 2021
Sparse Convex Optimization via Adaptively Regularized Hard Thresholding JMLR 2021
Bandit Convex Optimization in Non-stationary Environments JMLR 2021
An Inertial Newton Algorithm for Deep Learning JMLR 2021
Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives JMLR 2021
An algorithmic view of L2 regularization and some path-following algorithms JMLR 2021
Non-attracting Regions of Local Minima in Deep and Wide Neural Networks JMLR 2021
On efficient multilevel Clustering via Wasserstein distances JMLR 2021
Statistical guarantees for local graph clustering JMLR 2021