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← Optimization
Mathematics & Optimization
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Optimization
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Convex Optimization
589 directly classified papers
Papers per year
2004: 1
2005: 1
2006: 8
2007: 14
2008: 7
2009: 12
2010: 14
2011: 16
2012: 27
2013: 49
2014: 45
2015: 23
2016: 30
2017: 27
2018: 32
2019: 39
2020: 48
2021: 43
2022: 61
2023: 37
2024: 40
2025: 15
Papers
Better Approximation and Faster Algorithm Using the Proximal Average
NIPS 2013
On the Linear Convergence of the Proximal Gradient Method for Trace Norm Regularization
NIPS 2013
Linear Convergence with Condition Number Independent Access of Full Gradients
NIPS 2013
BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables
NIPS 2013
A Comparative Framework for Preconditioned Lasso Algorithms
NIPS 2013
Convex Calibrated Surrogates for Low-Rank Loss Matrices with Applications to Subset Ranking Losses
NIPS 2013
Sparse Inverse Covariance Estimation with Calibration
NIPS 2013
Trading Computation for Communication: Distributed Stochastic Dual Coordinate Ascent
NIPS 2013
Efficient 3D Endfiring TRUS Prostate Segmentation with Globally Optimized Rotational Symmetry
CVPR 2013
A Practical Rank-Constrained Eight-Point Algorithm for Fundamental Matrix Estimation
CVPR 2013
Robust Regression on MapReduce
ICML 2013
Convex Tensor Decomposition via Structured Schatten Norm Regularization
NIPS 2013
O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions
ICML 2013
Learning Convex QP Relaxations for Structured Prediction
ICML 2013
Accelerated Training for Matrix-norm Regularization: A Boosting Approach
NIPS 2012
Mirror Descent Meets Fixed Share (and feels no regret)
NIPS 2012
Random Design Analysis of Ridge Regression
COLT 2012
A quasi-Newton proximal splitting method
NIPS 2012
A Polynomial-time Form of Robust Regression
NIPS 2012
Finding Exemplars from Pairwise Dissimilarities via Simultaneous Sparse Recovery
NIPS 2012
A Stochastic Gradient Method with an Exponential Convergence _Rate for Finite Training Sets
NIPS 2012
Forging The Graphs: A Low Rank and Positive Semidefinite Graph Learning Approach
NIPS 2012
Stochastic Gradient Descent with Only One Projection
NIPS 2012
Globally Convergent Dual MAP LP Relaxation Solvers using Fenchel-Young Margins
NIPS 2012
Optimal Regularized Dual Averaging Methods for Stochastic Optimization
NIPS 2012
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