Proximal Optimization

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21 papers3 papers in the last four weeks, level with the four weeks before. 0.0% of all new papers.

Rethinking Optimization Methods for Hierarchical Feature Selection
Nov 6, 2026Xinyuan Song, Zekun Cai, Liang ZhaoFeature Selection Proximal Optimization
Emory University, Atlanta, GA, USA · The University of Tokyo, Tokyo, Japan
Last-Iterate Convergence of Stochastic Gradient Methods for Unbounded Problems
Nov 5, 2026Kevin Kurian Thomas Vaidyan, Ahmet Alacaoglu, Michael P. FriedlanderLast-Iterate Convergence Stochastic Optimization Convergence
Department of Computer Science, University of British Columbia · Department of Computer Science and Mathematics, University of British Columbia
FLINT: Coupling Proximal Initialization and Bounded Stochasticity for Flow-Matching Inverse Problems
Nov 4, 2026Junseo Bang, Daewon Choi, Dong Ju Mun +1Flow-Based Generative Modeling Inverse Problems
Dept. of ECE, Seoul National University, Republic of Korea · IPAI, Seoul National University, Republic of Korea · INMC & AIIS, Seoul National University, Republic of Korea
On the Complexity of Finite-Sum Nonconvex-Strongly-Concave Minimax Optimization with Exact Proximal Oracles
Nov 3, 2026Yuxing Peng, Zhiqing Tang, Weijia JiaMin-Max Optimization Oracle Complexity
Faculty of Arts and Sciences, Beijing Normal University, Zhuhai 519087, China · Institute of Artificial Intelligence and Future Networks, Faculty of Arts and Sciences, Beijing Normal University, Zhuhai 519087, China · Guangdong Key Lab of AI and Multi-Modal Data Processing, Beijing Normal-Hong Kong Baptist University, Zhuhai 519087, China
Riemannian Optimization on Unknown Manifolds via Stochastic Proximal Refinement
Oct 30, 2026Ruixiang Wu, Jiahao Ai, Tinko Sebastian Bartels +5Riemannian Optimization Stochastic Optimization
The Chinese University of Hong Kong, Shenzhen · University of Pennsylvania · Stanford University
Controlled Block Proximal Linearized Method for Nonconvex and Nonsmooth Optimization
Oct 25, 2026Weifeng YangGraph Regularization Proximal Optimization
Hessian-Similar Optimization with Capped Participation: Lower Bounds and Virtual Masters
Oct 24, 2026Rui WangFederated Learning Variance Reduction
Microsoft, Vancouver, BC, Canada
Anchored Extra-Proximal Methods: Optimal Higher-Order Methods for Monotone Inclusion Problems
Sep 24, 2026Ruichen Jiang, TaeHo YoonOracle Complexity Second-Order Optimization
Google Research · Johns Hopkins University
Complexities of Weak Proximal Oracle Methods for Composite Convex Optimization
Sep 21, 2026Dan GarberOracle Complexity Optimization Convergence Analysis
Faculty of Data and Decision Sciences Technion - Israel Institute of Technology
Convex Optimization with Nested Evolving Feasible Sets (CONES) under Time-Varying Loss Functions
Sep 10, 2026Rahul VazeOnline Convex Optimization Proximal Optimization
Adaptive Bregman Proximal Stochastic Gradient with a Stabilized Barzilai--Borwein Step Size
Aug 12, 2026Chenhan Jin, Shengze Xu, Binghui Xie +4Nonconvex Stochastic Optimization Adaptive Gradient Methods
1The Chinese University of Hong Kong · University of Utah · 3Beijing Normal-Hong Kong Baptist University +1
An Inertial Block Proximal Linearized Method with Adaptive Momentum for Nonconvex and Nonsmooth Optimization
Aug 6, 2026Weifeng YangMomentum Methods Nonconvex Optimization
Yunnan Earthquake Administration, Kunming 650224, China
Online Optimization of Difference-of-Convex Compositions with Smooth Mappings
Jul 21, 2026Jingwei Ji, Jong-Shi Pang, Renyuan XuNonconvex Optimization Constrained Optimization
Management Science and Engineering, Stanford University · The Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California
LCPNet: Latent Consistent Proximal Unfolding Network for Infrared Small Target Detection
Jul 6, 2026Tianfang Zhang, Lei Li, Chang Liu +3Remote Sensing Small Object Detection Proximal Optimization
Department of Automation, Tsinghua University, Beijing, 100190, China. · School of Artificial Intelligence, Beijing Institute of Technology, Beijing, 100081, China. · School of Information and Communication Engineering and the Laboratory of Imaging Detection and Intelligent Perception, University of Electronic Science and Technology of China, Chengdu, 610054, China.
Trajectory Constraints for Imaging Inverse Problems
May 27, 2026Chaoyan Huang, Haijie Yuan, Bharath Subramanian +1Proximal Optimization Image Reconstruction
Department of Computational Mathematics, Science, & Engineering, Michigan State University · Department of Electrical Engineering and Computer Science, University of Michigan · Department of Biomedical Engineering, Michigan State University
Proximal basin hopping: global optimization with guarantees
May 18, 2026Guillaume Lauga, Cesare Molinari, Samuel VaiterProximal Optimization Global Optimization
LJAD · LJAD Université Côte d’Azur France · MaLGA +3
Task Switching Without Forgetting via Proximal Decoupling
Apr 20, 2026Pourya Shamsolmoali, Masoumeh Zareapoor, Eric Granger +2Proximal Optimization Continual Learning
Department of Computer Science, University of York, UK · SEIEE, Shanghai Jiao Tong University, China · LIVIA, Dept. of Systems Engineering, ETS Montreal, Canada +1
Score-Guided Proximal Projection: A Unified Geometric Framework for Rectified Flow Editing
Mar 5, 2026Vansh Bansal, James G ScottProximal Optimization Rectified Flow
Department of Statistics and Data Sciences, UT Austin
General Proximal Flow Networks
Feb 28, 2026Alexander Strunk, Roland AssamProximal Optimization Generative Modeling
Evercot AI
Beyond SGD, Without SVD: Proximal Subspace Iteration LoRA with Diagonal Fractional K-FAC
Feb 18, 2026Abdulla Jasem Almansoori, Maria Ivanova, Andrey Veprikov +3Proximal Optimization Kronecker-Factored Approximation
MBZUAI, Abu Dhabi, UAE · Yandex School of Data Analysis, Moscow, Russia · SB AI Lab, Moscow, Russia +2
Neural Operators Which Certifiably Simultaneously Solve Infinitely Many Convex Programs using Logarithmic Rank and Linear Complexity
Aug 20, 2025Anastasis Kratsios, Ariel Neufeld, Philipp SchmockerNeural Operators Operator Learning
Department of Mathematics, McMaster University and the Vector Institute, Canada · Division of Mathematical Sciences, Nanyang Technological University, Singapore

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Rethinking Optimization Methods for Hierarchical Feature Selection

Xinyuan Song, Zekun Cai, Liang Zhao

Emory University, Atlanta, GA, USA · The University of Tokyo, Tokyo, Japan

Feature Selection Proximal Optimization Structured Sparsity Rare-Event Prediction

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Rare-event forecasting often depends on interpretable conjunctions: a single keyword, location, or temporal cue may be weak, while their joint occurrence can identify a meaningful precursor. Hierarchical-Task Numerical conjunctive feature Learning (HTNL) selects Numerical Conjunctive Features (NCFs) through a structured sparsity objective. However, the resulting optimization problem is challenging, making optimization design critical to its practical performance. We give a unified diagnosis of four HTNL optimization families: original majorization-minimization (MM), variational quadratic form (VQF), alternating direction method of multipliers (ADMM), and weighted group lasso (WGL). Our analysis distinguishes three key factors that jointly determine HTNL optimization behavior. First, VQF and MM are algebraically equivalent under matched variational updates and optimize a squared-penalty formulation. Second, ADMM optimizes the unsquared objective through consensus splitting; we replace its truncated FISTA proximal solver with a scalar bisection update (ADMM-Bisect) for more accurate treatment of near-threshold blocks. Third, WGL targets the same unsquared objective, while all methods face rapidly decaying active-set admission scores. Across two synthetic datasets and 11 civil-unrest and flu-surveillance tasks, VQF achieves the highest mean AUC with the most compact non-collapsing supports. ADMM-Bisect reduces measured runtime, while calibrated WGL avoids the empty-support failures of its original scale. Synthetic results further show how proximal accuracy, pruning, and search budget affect candidate recovery, especially for longer conjunctions. Code will be made publicly available upon publication.