Research Explorer
Papers
Trends
Conferences
Explore
Authors
Topics
Keywords
Papers
Trends
Conferences
Explore
Authors
Topics
Keywords
Achievements
About
Methodology
← Optimization
Mathematics & Optimization
›
Optimization
›
Continuous Optimization
3907 directly classified papers
Papers per year
2001: 1
2002: 2
2004: 2
2005: 6
2006: 16
2007: 22
2008: 29
2009: 27
2010: 38
2011: 44
2012: 78
2013: 146
2014: 172
2015: 155
2016: 188
2017: 223
2018: 260
2019: 393
2020: 367
2021: 395
2022: 418
2023: 423
2024: 320
2025: 154
2026: 28
Papers
Orthogonal Over-Parameterized Training
CVPR 2021
PluckerNet: Learn To Register 3D Line Reconstructions
CVPR 2021
Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis
NIPS 2021
Localization, Convexity, and Star Aggregation
NIPS 2021
How Data Augmentation affects Optimization for Linear Regression
NIPS 2021
Distributed Saddle-Point Problems Under Data Similarity
NIPS 2021
Escape saddle points by a simple gradient-descent based algorithm
NIPS 2021
The Unbalanced Gromov Wasserstein Distance: Conic Formulation and Relaxation
NIPS 2021
On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry
NIPS 2021
A Highly-Efficient Group Elastic Net Algorithm with an Application to Function-On-Scalar Regression
NIPS 2021
Efficient methods for Gaussian Markov random fields under sparse linear constraints
NIPS 2021
Fast Projection onto the Capped Simplex with Applications to Sparse Regression in Bioinformatics
NIPS 2021
Efficient Mirror Descent Ascent Methods for Nonsmooth Minimax Problems
NIPS 2021
Faster proximal algorithms for matrix optimization using Jacobi-based eigenvalue methods
NIPS 2021
DeepGEM: Generalized Expectation-Maximization for Blind Inversion
NIPS 2021
Non-asymptotic convergence bounds for Wasserstein approximation using point clouds
NIPS 2021
Better Algorithms for Individually Fair $k$-Clustering
NIPS 2021
A novel notion of barycenter for probability distributions based on optimal weak mass transport
NIPS 2021
Rethinking the Variational Interpretation of Accelerated Optimization Methods
NIPS 2021
Modified Frank Wolfe in Probability Space
NIPS 2021
Scaling up Continuous-Time Markov Chains Helps Resolve Underspecification
NIPS 2021
Exploiting Chain Rule and Bayes' Theorem to Compare Probability Distributions
NIPS 2021
TNASP: A Transformer-based NAS Predictor with a Self-evolution Framework
NIPS 2021
Large-Scale Learning with Fourier Features and Tensor Decompositions
NIPS 2021
Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization
NIPS 2021
<
1
…
56
57
58
…
157
>