conftrace_
← Optimization
Mathematics & Optimization › Optimization ›

Continuous Optimization

3907 directly classified papers

Papers per year

Papers

Simple steps are all you need: Frank-Wolfe and generalized self-concordant functions NIPS 2021
Learning to Learn Graph Topologies NIPS 2021
A No-go Theorem for Robust Acceleration in the Hyperbolic Plane NIPS 2021
Exploiting Local Convergence of Quasi-Newton Methods Globally: Adaptive Sample Size Approach NIPS 2021
Solving Min-Max Optimization with Hidden Structure via Gradient Descent Ascent NIPS 2021
Smooth Bilevel Programming for Sparse Regularization NIPS 2021
Unique sparse decomposition of low rank matrices NIPS 2021
Fast Tucker Rank Reduction for Non-Negative Tensors Using Mean-Field Approximation NIPS 2021
Global Transport for Fluid Reconstruction With Learned Self-Supervision CVPR 2021
Incremental Learning via Rate Reduction CVPR 2021
MongeNet: Efficient Sampler for Geometric Deep Learning CVPR 2021
Square Root Bundle Adjustment for Large-Scale Reconstruction CVPR 2021
Normal Integration via Inverse Plane Fitting With Minimum Point-to-Plane Distance CVPR 2021
Timeline Summarization based on Event Graph Compression via Time-Aware Optimal Transport EMNLP 2021
Block-wise Word Embedding Compression Revisited: Better Weighting and Structuring EMNLP 2021
Automatic Text Evaluation through the Lens of Wasserstein Barycenters EMNLP 2021
Physarum Powered Differentiable Linear Programming Layers and Applications AAAI 2021
Dual Principal Component Pursuit for Learning a Union of Hyperplanes: Theory and Algorithms AISTATS 2021
Fast Statistical Leverage Score Approximation in Kernel Ridge Regression AISTATS 2021
Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization AISTATS 2021
Fenchel-Young Losses with Skewed Entropies for Class-posterior Probability Estimation AISTATS 2021
Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed Optimization AISTATS 2021
Identification of Matrix Joint Block Diagonalization AISTATS 2021
Last iterate convergence in no-regret learning: constrained min-max optimization for convex-concave landscapes AISTATS 2021
Momentum Improves Optimization on Riemannian Manifolds AISTATS 2021