Greedy Algorithms for Structurally Constrained High Dimensional Problems

No abstract is available for this paper.

• Publication year

  2011

• Venue

  Neural Information Processing Systems

• Publication date

  2011-12-12

• Fields of study

  Mathematics, Computer Science

• Identifiers

  No identifiers available.

• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Submodular meets Spectral: Greedy Algorithms for Subset Selection, Sparse Approximation and Dictionary Selection

  2011cited by this paper
• Large-Scale Convex Minimization with a Low-Rank Constraint

  2011cited by this paper
• Group Orthogonal Matching Pursuit for Logistic Regression

  2011cited by this paper
• The Convex Geometry of Linear Inverse Problems

  2010cited by this paper
• Fast global convergence rates of gradient methods for high-dimensional statistical recovery

  2010cited by this paper
• Trading Accuracy for Sparsity in Optimization Problems with Sparsity Constraints

  2010cited by this paper
• Grouped Orthogonal Matching Pursuit for Variable Selection and Prediction

  2009cited by this paper
• Nonparametric Greedy Algorithms for the Sparse Learning Problem

  2009cited by this paper
• A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers

  2009influential reference
• Most Tensor Problems Are NP-Hard

  2009cited by this paper
• Greedy approximation

  2008cited by this paper
• Uniformly convex functions on Banach spaces

  2008cited by this paper
• Coresets, sparse greedy approximation, and the Frank-Wolfe algorithm

  2008cited by this paper
• History of Banach Spaces and Linear Operators

  2007cited by this paper
• The Boosting Approach to Machine Learning An Overview

  2003cited by this paper
• Sequential greedy approximation for certain convex optimization problems

  2003cited by this paper
• Martingales with values in uniformly convex spaces

  1975cited by this paper
• An algorithm for quadratic programming

  1956cited by this paper
• Constructive Approximation Rates of Convex Approximation in Non-hilbert Spaces

  year unknowncited by this paper

• Brief introduction in greedy approximation

  2025cites this paper
• Geometry-dependent matching pursuit: a transition phase for convergence on linear regression and LASSO

  2024cites this paper
• On greedy approximation in complex Banach spaces

  2024cites this paper
• Refined Convergence and Topology Learning for Decentralized SGD with Heterogeneous Data

  2022cites this paper
• Open Journal of Mathematical Optimization

  2022cites this paper
• Open Journal of Mathematical Optimization

  2022cites this paper
• Open Journal of Mathematical Optimization

  2022cites this paper
• Extending generalized unsupervised manifold alignment

  2022cites this paper
• Refined Convergence and Topology Learning for Decentralized Optimization with Heterogeneous Data

  2022cites this paper
• Yes, Topology Matters in Decentralized Optimization: Refined Convergence and Topology Learning under Heterogeneous Data

  2022cites this paper
• High-probability bounds for robust stochastic Frank-Wolfe algorithm

  2022cites this paper
• Control Oriented Learning in the Era of Big Data

  2021cites this paper
• Screening for a Reweighted Penalized Conditional Gradient Method

  2021cites this paper
• ENNS: Variable Selection, Regression, Classification and Deep Neural Network for High-Dimensional Data

  2021cites this paper
• Few-Shot Learning

  2020cites this paper
• Biorthogonal greedy algorithms in convex optimization

  2020influential citation
• Feature-Based Transfer Learning

  2020cites this paper
• AutoTL: Learning to Transfer Automatically

  2020cites this paper
• Model-Based Transfer Learning

  2020cites this paper
• Transfer Learning in Reinforcement Learning

  2020cites this paper
• Privacy-Preserving Transfer Learning

  2020cites this paper
• Transfer Learning in Dialogue Systems

  2020cites this paper
• Transfer Learning in Recommender Systems

  2020cites this paper
• SWAG: A Wrapper Method for Sparse Learning

  2020cites this paper
• Recursive approximation of complex behaviours with IoT-data imperfections

  2020cites this paper
• Safe Screening for the Generalized Conditional Gradient Method

  2020cites this paper
• New Computational and Statistical Aspects of Regularized Regression with Application to Rare Feature Selection and Aggregation

  2019cites this paper
• Convex and nonconvex optimization geometries

  2019cites this paper
• Lecture Notes: Optimization for Machine Learning

  2019cites this paper
• Transfer Learning in Natural Language Processing

  2019cites this paper
• Greedy and IHT Algorithms for Non-convex Optimization with Monotone Costs of Non-zeros

  2019cites this paper
• M ay 2 01 6 Structured Sparse Regression via Greedy Hard-Thresholding

  2018cites this paper
• A Randomized Algorithm for Parsimonious Model Identification

  2018cites this paper
• Gradient Hard Thresholding Pursuit

  2018cites this paper
• Adversarial Transfer Learning

  2018cites this paper
• L G ] 1 6 A pr 2 01 4 ORTHOGONAL RANK-ONE MATRIX PURSUIT FOR LOW RANK MATRIX COMPLETION

  2018influential citation
• Deep Neural Networks for High Dimension, Low Sample Size Data

  2017cites this paper
• Distributing Frank–Wolfe via map-reduce

  2017cites this paper
• An Internet of Things compliant model identification methodology for smart buildings

  2017cites this paper
• Submitted to the Annals of Statistics RESTRICTED STRONG CONVEXITY IMPLIES WEAK SUBMODULARITY By

  2017cites this paper
• Differentially Private Matrix Completion, Revisited

  2017cites this paper
• Non-convex Optimization for Machine Learning

  2017cites this paper
• The Interplay Between Big Data and Sparsity in Systems Identification

  2017cites this paper
• Heterogeneous transfer learning

  2017cites this paper
• Convergence and Rate of Convergence of Approximate Greedy-Type Algorithms

  2017cites this paper
• Robust model fitting via convex optimization techniques

  2016cites this paper
• Minimum Description Length Principle Based Atomic Norm for Synthetic Low-Rank Matrix Recovery

  2016cites this paper
• Restricted Strong Convexity Implies Weak Submodularity

  2016cites this paper
• Introduction to Online Convex Optimization

  2016cites this paper
• A super-atomic norm minimization approach to identifying sparse dynamical graphical models

  2016cites this paper
• Approximate support recovery of atomic line spectral estimation: A tale of resolution and precision

  2016cites this paper
• Classification With the Sparse Group Lasso

  2016cites this paper
• A Generalized Matching Pursuit Approach for Graph-Structured Sparsity

  2016cites this paper
• Methods for convex optimization and statistical learning

  2016cites this paper
• Pursuits in Structured Non-Convex Matrix Factorizations

  2016cites this paper
• Worst-Case Hardness of Approximation for Sparse Optimization with L 0 Norm immediate March

  2016cites this paper
• Hardness of Approximation for Sparse Optimization with L 0 Norm

  2016cites this paper
• Greedy Strategies for Convex Optimization

  2016cites this paper
• Structured Sparse Regression via Greedy Hard Thresholding

  2016cites this paper
• Subspace Clustering with Priors via Sparse Quadratically Constrained Quadratic Programming

  2016cites this paper
• Tractable problems in estimation and control subject to sparsity and structural constraints

  2016cites this paper
• Graph-Structured Sparse Optimization for Connected Subgraph Detection

  2016cites this paper
• A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery

  2016cites this paper
• Decomposition Techniques for Bilinear Saddle Point Problems and Variational Inequalities with Affine Monotone Operators

  2015cites this paper
• Minimum Error Entropy Based Sparse Representation for Robust Subspace Clustering

  2015cites this paper
• The Interplay Between Big Data and Sparsity in Systems Identification: Some Lessons from Machine Learning*

  2015cites this paper
• On Solutions of Sparsity Constrained Optimization

  2015cites this paper
• Transitive Transfer Learning

  2015cites this paper
• Collaborative Filtering with Graph Information: Consistency and Scalable Methods

  2015cites this paper
• PU matrix completion with graph information

  2015cites this paper
• On Solutions of Sparsity Constrained Optimization

  2015cites this paper
• Matching Pursuit LASSO Part I: Sparse Recovery Over Big Dictionary

  2015cites this paper
• Structural Atomic Representation for Classification

  2015cites this paper
• Classification via atomic representation

  2015cites this paper
• An Extended Frank-Wolfe Method with "In-Face" Directions, and Its Application to Low-Rank Matrix Completion

  2015cites this paper
• Convex Optimization on Banach Spaces

  2014cites this paper
• Rank-One Matrix Pursuit for Matrix Completion

  2014influential citation
• Hybrid Conditional Gradient - Smoothing Algorithms with Applications to Sparse and Low Rank Regularization

  2014cites this paper
• Greedy Strategies for Convex Optimization

  2014cites this paper
• Towards efficient large-scale learning by exploiting sparsity

  2014cites this paper
• Parsimonious model identification via atomic norm minimization

  2014cites this paper
• Convergence and rate of convergence of some greedy algorithms in convex optimization

  2014cites this paper
• Sparsity-Constrained Optimization

  2014cites this paper
• Estimation Under Model-Based Sparsity

  2014cites this paper
• Generalized Conditional Gradient for Sparse Estimation

  2014influential citation
• Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings

  2014cites this paper
• QUIC & DIRTY: A Quadratic Approximation Approach for Dirty Statistical Models

  2014cites this paper
• Matrix completion based on feature vector and function approximation

  2014cites this paper
• Greedy expansions in convex optimization

  2014cites this paper
• Orthogonal Rank-One Matrix Pursuit for Low Rank Matrix Completion

  2014cites this paper
• A convex optimization approach to semi-supervised identification of switched ARX systems

  2014cites this paper
• Forward–Backward Greedy Algorithms for Atomic Norm Regularization

  2014cites this paper
• Matching Pursuit LASSO Part II: Applications and Sparse Recovery Over Batch Signals

  2013cites this paper
• An efficient atomic norm minimization approach to identification of low order models

  2013cites this paper
• Minimax Sparse Logistic Regression for Very High-Dimensional Feature Selection

  2013cites this paper
• Orthogonal Rank-One Matrix Pursuit for Matrix Completion

  2013influential citation
• Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization

  2013cites this paper
• Learning with high-dimensional noisy data

  2013cites this paper
• Noisy and Missing Data Regression: Distribution-Oblivious Support Recovery

  2013cites this paper
• Fast structure learning in generalized stochastic processes with latent factors

  2013influential citation