Non-Convex Optimization
Optimization in non-convex landscapes
Related Topics (Optimization)
Top Papers
GLOP: Learning Global Partition and Local Construction for Solving Large-Scale Routing Problems in Real-Time
Haoran Ye, Jiarui Wang, Helan Liang et al.
Methods for Convex $(L_0,L_1)$-Smooth Optimization: Clipping, Acceleration, and Adaptivity
Eduard Gorbunov, Nazarii Tupitsa, Sayantan Choudhury et al.
SimPER: A Minimalist Approach to Preference Alignment without Hyperparameters
Teng Xiao, Yige Yuan, Zhengyu Chen et al.
What's in a Prior? Learned Proximal Networks for Inverse Problems
Zhenghan Fang, Sam Buchanan, Jeremias Sulam
ConFIG: Towards Conflict-free Training of Physics Informed Neural Networks
Qiang Liu, Mengyu Chu, Nils Thuerey
The Loss Landscape of Deep Linear Neural Networks: a Second-order Analysis
El Mehdi Achour, Francois Malgouyres, Sebastien Gerchinovitz
Leaving the Nest: Going beyond Local Loss Functions for Predict-Then-Optimize
Sanket Shah, Bryan Wilder, Andrew Perrault et al.
Constrained Bayesian Optimization under Partial Observations: Balanced Improvements and Provable Convergence
Shengbo Wang, Ke Li
Understanding Optimization in Deep Learning with Central Flows
Jeremy Cohen, Alex Damian, Ameet Talwalkar et al.
Boosting Neural Combinatorial Optimization for Large-Scale Vehicle Routing Problems
Fu Luo, Xi Lin, Yaoxin Wu et al.
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold
Jun Chen, Haishan Ye, Mengmeng Wang et al.
Compositional Generative Inverse Design
Tailin Wu, Takashi Maruyama, Long Wei et al.
Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization
XiangCheng Zhang, Fang Kong, Baoxiang Wang et al.
Deep Distributed Optimization for Large-Scale Quadratic Programming
Augustinos Saravanos, Hunter Kuperman, Alex Oshin et al.
Faster Algorithms for Structured Linear and Kernel Support Vector Machines
Yuzhou Gu, Zhao Song, Lichen Zhang
Pareto Deep Long-Tailed Recognition: A Conflict-Averse Solution
Zhipeng Zhou, Liu Liu, Peilin Zhao et al.
Learning to Pivot as a Smart Expert
Tianhao Liu, Shanwen Pu, Dongdong Ge et al.
Cumulative Regret Analysis of the Piyavskii–Shubert Algorithm and Its Variants for Global Optimization
Kaan Gokcesu, Hakan Gökcesu
DiscoMatch: Fast Discrete Optimisation for Geometrically Consistent 3D Shape Matching
Paul Roetzer, Ahmed Abbas, Dongliang Cao et al.
Neural Exploratory Landscape Analysis for Meta-Black-Box-Optimization
Zeyuan Ma, Jiacheng Chen, Hongshu Guo et al.
Improving Physics-Augmented Continuum Neural Radiance Field-Based Geometry-Agnostic System Identification with Lagrangian Particle Optimization
Takuhiro Kaneko
Decomposition Polyhedra of Piecewise Linear Functions
Marie-Charlotte Brandenburg, Moritz Grillo, Christoph Hertrich
Deep Nonlinear Sufficient Dimension Reduction
Yinfeng Chen, Yuling Jiao, Rui Qiu et al.
Pareto Front-Diverse Batch Multi-Objective Bayesian Optimization
Alaleh Ahmadianshalchi, Syrine Belakaria, Janardhan Rao Doppa
SILO: Solving Inverse Problems with Latent Operators
Ron Raphaeli, Sean Man, Michael Elad
Few for Many: Tchebycheff Set Scalarization for Many-Objective Optimization
Xi Lin, Yilu Liu, Xiaoyuan Zhang et al.
Online Guidance Graph Optimization for Lifelong Multi-Agent Path Finding
Hongzhi Zang, Yulun Zhang, He Jiang et al.
Right Now, Wrong Then: Non-Stationary Direct Preference Optimization under Preference Drift
Seongho Son, William Bankes, Sayak Ray Chowdhury et al.
Large-Scale Multi-Robot Coverage Path Planning via Local Search
Jingtao Tang, Hang Ma
ALE-Bench: A Benchmark for Long-Horizon Objective-Driven Algorithm Engineering
Yuki Imajuku, Kohki Horie, Yoichi Iwata et al.
Two-timescale Extragradient for Finding Local Minimax Points
Jiseok Chae, Kyuwon Kim, Donghwan Kim
Multi-Session SLAM with Differentiable Wide-Baseline Pose Optimization
Lahav Lipson, Jia Deng
Optimizing ADMM and Over-Relaxed ADMM Parameters for Linear Quadratic Problems
Song Jintao, Wenqi Lu, Yunwen Lei et al.
Locally Convex Global Loss Network for Decision-Focused Learning
Haeun Jeon, Hyunglip Bae, Minsu Park et al.
Massively Parallel Continuous Local Search for Hybrid SAT Solving on GPUs
Yunuo Cen, Zhiwei Zhang, Xuanyao Fong
Toward Efficient Kernel-Based Solvers for Nonlinear PDEs
Zhitong Xu, Da Long, Yiming Xu et al.
DOGE-Train: Discrete Optimization on GPU with End-to-End Training
Ahmed Abbas, P. Swoboda
Volume Optimality in Conformal Prediction with Structured Prediction Sets
Chao Gao, Liren Shan, Vaidehi Srinivas et al.
Learning a Neural Solver for Parametric PDEs to Enhance Physics-Informed Methods
Lise Le Boudec, Emmanuel de Bézenac, Louis Serrano et al.
General framework for online-to-nonconvex conversion: Schedule-free SGD is also effective for nonconvex optimization
Kwangjun Ahn, Gagik Magakyan, Ashok Cutkosky
LVFace: Progressive Cluster Optimization for Large Vision Models in Face Recognition
Jinghan You, Shanglin Li, Yuanrui Sun et al.
Optimization by Parallel Quasi-Quantum Annealing with Gradient-Based Sampling
Yuma Ichikawa, Yamato Arai
ADMM for Nonconvex Optimization under Minimal Continuity Assumption
Ganzhao Yuan
Constrained Optimization From a Control Perspective via Feedback Linearization
Runyu Zhang, Arvind Raghunathan, Jeff Shamma et al.
Flavors of Margin: Implicit Bias of Steepest Descent in Homogeneous Neural Networks
Nikolaos Tsilivis, Gal Vardi, Julia Kempe
Scaling Convex Neural Networks with Burer-Monteiro Factorization
Arda Sahiner, Tolga Ergen, Batu Ozturkler et al.
Nesterov acceleration in benignly non-convex landscapes
Kanan Gupta, Stephan Wojtowytsch
UniAP: Unifying Inter- and Intra-Layer Automatic Parallelism by Mixed Integer Quadratic Programming
Hao Lin, Ke Wu, Jie Li et al.
Functional Homotopy: Smoothing Discrete Optimization via Continuous Parameters for LLM Jailbreak Attacks
Zi Wang, Divyam Anshumaan, Ashish Hooda et al.
Rethinking Neural Combinatorial Optimization for Vehicle Routing Problems with Different Constraint Tightness Degrees
Fu Luo, Yaoxin Wu, Zhi Zheng et al.
Second-Order Min-Max Optimization with Lazy Hessians
Lesi Chen, Chengchang Liu, Jingzhao Zhang
Do Deep Neural Network Solutions Form a Star Domain?
Ankit Sonthalia, Alexander Rubinstein, Ehsan Abbasnejad et al.
Foreseeing Reconstruction Quality of Gradient Inversion: An Optimization Perspective
Hyeong Gwon Hong, Yooshin Cho, Hanbyel Cho et al.
High-Dimensional Analysis for Generalized Nonlinear Regression: From Asymptotics to Algorithm
Jian Li, Yong Liu, Weiping Wang
Aligned Multi Objective Optimization
Yonathan Efroni, Ben Kretzu, Daniel Jiang et al.
Exploring The Loss Landscape Of Regularized Neural Networks Via Convex Duality
Sungyoon Kim, Aaron Mishkin, Mert Pilanci
BOIDS: High-Dimensional Bayesian Optimization via Incumbent-Guided Direction Lines and Subspace Embeddings
Lam Ngo, Huong Ha, Jeffrey Chan et al.
Accelerated Methods with Compressed Communications for Distributed Optimization Problems Under Data Similarity
Dmitry Bylinkin, Aleksandr Beznosikov
Approximation algorithms for combinatorial optimization with predictions
Antonios Antoniadis, Marek Elias, Adam Polak et al.
Implicit Riemannian Optimism with Applications to Min-Max Problems
Christophe Roux, David Martinez-Rubio, Sebastian Pokutta
Improving Pareto Set Learning for Expensive Multi-objective Optimization via Stein Variational Hypernetworks
Minh-Duc Nguyen, Phuong Mai Dinh, Quang-Huy Nguyen et al.
Exploiting Curvature in Online Convex Optimization with Delayed Feedback
Hao Qiu, Emmanuel Esposito, Mengxiao Zhang
LancBiO: Dynamic Lanczos-aided Bilevel Optimization via Krylov Subspace
Yan Yang, Bin Gao, Ya-xiang Yuan
Learning to Solve Differential Equation Constrained Optimization Problems
Vincenzo Di Vito Francesco, Mostafa Mohammadian, Kyri Baker et al.
Dueling Convex Optimization with General Preferences
Aadirupa Saha, Tomer Koren, Yishay Mansour
Improving Generalization of Neural Combinatorial Optimization for Vehicle Routing Problems via Test-Time Projection Learning
Yuanyao Chen, Rongsheng Chen, Fu Luo et al.
Non-monotone Sequential Submodular Maximization
Shaojie Tang, Jing Yuan
Optimising Spatial Teamwork Under Uncertainty
Gregory Everett, Ryan J. Beal, Tim Matthews et al.
The adaptive complexity of parallelized log-concave sampling
Huanjian Zhou, Baoxiang Wang, Masashi Sugiyama
Loss Landscape of Shallow ReLU-like Neural Networks: Stationary Points, Saddle Escape, and Network Embedding
Frank Zhengqing Wu, Berfin Simsek, François Ged
SAMO: A Lightweight Sharpness-Aware Approach for Multi-Task Optimization with Joint Global-Local Perturbation
Hao Ban, Gokul Ram Subramani, Kaiyi Ji
Derivative-Free Diffusion Manifold-Constrained Gradient for Unified XAI
Won Jun Kim, Hyungjin Chung, Jaemin Kim et al.
GSO-Net: Grid Surface Optimization via Learning Geometric Constraints
Chaoyun Wang, Jingmin Xin, Nanning Zheng et al.
How to Find the Exact Pareto Front for Multi-Objective MDPs?
Yining Li, Peizhong Ju, Ness Shroff
Geometry-Aware Approaches for Balancing Performance and Theoretical Guarantees in Linear Bandits
Yuwei Luo, Mohsen Bayati
Solver-Free Decision-Focused Learning for Linear Optimization Problems
Senne Berden, Ali Mahmutoğulları, Dimos Tsouros et al.
Geometric Algebra Planes: Convex Implicit Neural Volumes
Irmak Sivgin, Sara Fridovich-Keil, Gordon Wetzstein et al.
Differentiable Quadratic Optimization For the Maximum Independent Set Problem
Ismail Alkhouri, Cedric Le Denmat, Yingjie Li et al.
Adaptive backtracking for faster optimization
Joao V. Cavalcanti, Laurent Lessard, Ashia Wilson
A Variational Perspective on Generative Protein Fitness Optimization
Lea Bogensperger, Dominik Narnhofer, Ahmed Allam et al.
FSNet: Feasibility-Seeking Neural Network for Constrained Optimization with Guarantees
Hoang Nguyen, Priya Donti
A geometric framework for momentum-based optimizers for low-rank training
Steffen Schotthöfer, Timon Klein, Jonas Kusch
Set Smoothness Unlocks Clarke Hyper-stationarity in Bilevel Optimization
He Chen, Jiajin Li, Anthony Man-Cho So
Escaping saddle points without Lipschitz smoothness: the power of nonlinear preconditioning
Alexander Bodard, Panagiotis Patrinos
Improving Diffusion-based Inverse Algorithms under Few-Step Constraint via Linear Extrapolation
Jiawei Zhang, Ziyuan Liu, Leon Yan et al.
Stochastic Gradients under Nuisances
Facheng Yu, Ronak Mehta, Alex Luedtke et al.
Threshold UCT: Cost-Constrained Monte Carlo Tree Search with Pareto Curves
Martin Kurečka, Václav Nevyhoštěný, Petr Novotný et al.
Balancing Gradient and Hessian Queries in Non-Convex Optimization
Deeksha Adil, Brian Bullins, Aaron Sidford et al.
Error Analysis Affected by Heavy-Tailed Gradients for Non-Convex Pairwise Stochastic Gradient Descent
Jun Chen, Hong Chen, Bin Gu et al.
AutoScape: Geometry-Consistent Long-Horizon Scene Generation
Jiacheng Chen, Ziyu Jiang, Mingfu Liang et al.
DUET: Decentralized Bilevel Optimization without Lower-Level Strong Convexity
Zhen Qin, Zhuqing Liu, Songtao Lu et al.
DisCo-DSO: Coupling Discrete and Continuous Optimization for Efficient Generative Design in Hybrid Spaces
Jacob F. Pettit, Chak Shing Lee, Jiachen Yang et al.
LEAD: Min-Max Optimization from a Physical Perspective
Guillaume Lajoie, Amartya Mitra, Reyhane Askari Hemmat et al.
ADMM for Structured Fractional Minimization
Ganzhao Yuan
Fast Globally Optimal and Geometrically Consistent 3D Shape Matching
Paul Roetzer, Florian Bernard
Differentiable Convex Polyhedra Optimization from Multi-view Images
Daxuan Ren, Haiyi Mei, Hezi Shi et al.
Improving Convergence Guarantees of Random Subspace Second-order Algorithm for Nonconvex Optimization
Rei Higuchi, Pierre-Louis Poirion, Akiko Takeda
Elliptic Loss Regularization
Ali Hasan, Haoming Yang, Yuting Ng et al.
Utilitarian Algorithm Configuration for Infinite Parameter Spaces
Devon Graham, Kevin Leyton-Brown
Learning Cocoercive Conservative Denoisers via Helmholtz Decomposition for Poisson Imaging Inverse Problems
Deliang Wei, Peng Chen, Haobo Xu et al.