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Optimization

1184 directly classified papers

Papers per year

Papers

Proximal Exploration for Model-guided Protein Sequence Design ICML 2022
Gradient-Free Method for Heavily Constrained Nonconvex Optimization ICML 2022
Closed-Form Diffeomorphic Transformations for Time Series Alignment ICML 2022
Joint Continuous and Discrete Model Selection via Submodularity JMLR 2022
On the Finite-Time Complexity and Practical Computation of Approximate Stationarity Concepts of Lipschitz Functions ICML 2022
Early Stopping for Iterative Regularization with General Loss Functions JMLR 2022
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions ICML 2022
Generic Coreset for Scalable Learning of Monotonic Kernels: Logistic Regression, Sigmoid and more ICML 2022
A Unified Weight Initialization Paradigm for Tensorial Convolutional Neural Networks ICML 2022
SGD with Coordinate Sampling: Theory and Practice JMLR 2022
Reverse Engineering $\ell_p$ attacks: A block-sparse optimization approach with recovery guarantees ICML 2022
Project and Forget: Solving Large-Scale Metric Constrained Problems JMLR 2022
Handling Hard Affine SDP Shape Constraints in RKHSs JMLR 2022
Distributed Stochastic Gradient Descent: Nonconvexity, Nonsmoothness, and Convergence to Local Minima JMLR 2022
On Low-rank Trace Regression under General Sampling Distribution JMLR 2022
Projected Robust PCA with Application to Smooth Image Recovery JMLR 2022
Extensions to the Proximal Distance Method of Constrained Optimization JMLR 2022
KNOT: Knowledge Distillation Using Optimal Transport for Solving NLP Tasks COLING 2022
Individual Fairness Guarantees for Neural Networks IJCAI 2022
tntorch: Tensor Network Learning with PyTorch JMLR 2022
Accelerating Adaptive Cubic Regularization of Newton's Method via Random Sampling JMLR 2022
Sum of Ranked Range Loss for Supervised Learning JMLR 2022
Reverse-mode differentiation in arbitrary tensor network format: with application to supervised learning JMLR 2022
Provable Tensor-Train Format Tensor Completion by Riemannian Optimization JMLR 2022
Let's Make Block Coordinate Descent Converge Faster: Faster Greedy Rules, Message-Passing, Active-Set Complexity, and Superlinear Convergence JMLR 2022