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https://arxiv.org/abs/1606.02338 [1606.02338] The Sound of APALM Clapping: Faster Nonsmooth Nonconvex Optimization with Stochastic... Abstract page for arXiv paper 1606.02338: The Sound of APALM Clapping: Faster Nonsmooth Nonconvex Optimization with Stochastic Asynchronous PALM the sound of https://deepai.org/publication/nonconvex-optimization-via-mm-algorithms-convergence-theory Nonconvex Optimization via MM Algorithms: Convergence Theory | DeepAI Jun 5, 2021 - 06/05/21 - The majorization-minimization (MM) principle is an extremely general framework for deriving optimization algorithms. It includes t... nonconvex optimization via mm algorithms https://deepai.org/publication/robustness-of-quantum-algorithms-for-nonconvex-optimization Robustness of Quantum Algorithms for Nonconvex Optimization | DeepAI Dec 5, 2022 - 12/05/22 - Recent results suggest that quantum computers possess the potential to speed up nonconvex optimization problems. However, a crucia... quantum algorithms robustness nonconvex optimization deepai https://openreview.net/forum?id=EDVIHPZhFo Nonconvex-nonconcave min-max optimization on Riemannian manifolds | OpenReview This work studies nonconvex-nonconcave min-max problems on Riemannian manifolds. We first characterize the local optimality of nonconvex-nonconcave problems on... min max optimization riemannian manifolds nonconvex openreview https://openreview.net/forum?id=kak1uJlIZe&referrer=%5Bthe%20profile%20of%20Fan%20Yang%5D(%2Fprofile%3Fid%3D~Fan_Yang51) Multi-View Randomized Kernel Classification via Nonconvex Optimization | OpenReview Multi kernel learning (MKL) is a representative supervised multi-view learning method widely applied in multi-modal and multi-view applications. MKL aims to... multi view randomized kernel classification via https://deepai.org/publication/nonconvex-matrix-factorization-is-geodesically-convex-global-landscape-analysis-for-fixed-rank-matrix-optimization-from-a-riemannian-perspective Nonconvex Matrix Factorization is Geodesically Convex: Global Landscape Analysis for Fixed-rank... Sep 29, 2022 - 09/29/22 - We study a general matrix optimization problem with a fixed-rank positive semidefinite (PSD) constraint. We perform the Burer-Mont... matrix factorization geodesically convex https://arxiv.org/abs/1702.08627 [1702.08627] An Optimization Framework with Flexible Inexact Inner Iterations for Nonconvex and... Abstract page for arXiv paper 1702.08627: An Optimization Framework with Flexible Inexact Inner Iterations for Nonconvex and Nonsmooth Programming https://openreview.net/forum?id=U7vVeHydyR Fast Extra Gradient Methods for Smooth Structured Nonconvex-Nonconcave Minimax Problems | OpenReview We propose a fast extragradient method, with an accelerated O(1/k^2) rate, for smooth structured nonconvex-nonconcave problems. https://openreview.net/forum?id=DHwfECmgKv Online Nonconvex Bilevel Optimization with Bregman Divergences | OpenReview Bilevel optimization methods are increasingly relevant within machine learning, especially for tasks such as hyperparameter optimization and meta-learning.... bilevel optimization online nonconvex bregman divergences https://jmlr.org/papers/v25/23-0371.html A projected semismooth Newton method for a class of nonconvex composite programs with strong... https://stanford.edu/~boyd/papers/qcqp.html General Heuristics for Nonconvex Quadratically Constrained Quadratic Programming general heuristics nonconvex constrained quadratic https://arxiv.org/abs/1510.01518 [1510.01518] DC Decomposition of Nonconvex Polynomials with Algebraic Techniques Abstract page for arXiv paper 1510.01518: DC Decomposition of Nonconvex Polynomials with Algebraic Techniques 1510 01518 dc decomposition nonconvex https://arxiv.org/abs/2403.10547 [2403.10547] Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix... Abstract page for arXiv paper 2403.10547: Robust Second-Order Nonconvex Optimization and Its Application to Low Rank Matrix Sensing https://arxiv.org/abs/2104.09685 [2104.09685] Accelerated Inexact First-Order Methods for Solving Nonconvex Composite Optimization... Abstract page for arXiv paper 2104.09685: Accelerated Inexact First-Order Methods for Solving Nonconvex Composite Optimization Problems first order https://jmlr.org/papers/v24/22-0882.html Preconditioned Gradient Descent for Overparameterized Nonconvex Burer--Monteiro Factorization with... gradient descent nonconvex monteiro factorization https://deepai.org/publication/a-computation-and-communication-efficient-method-for-distributed-nonconvex-problems-in-the-partial-participation-setting A Computation and Communication Efficient Method for Distributed Nonconvex Problems in the Partial... May 31, 2022 - 05/31/22 - We present a new method that includes three key components of distributed optimization and federated learning: variance reduction ... https://arxiv.org/abs/1707.02514 [1707.02514] An Adaptive, Multivariate Partitioning Algorithm for Global Optimization of Nonconvex... Abstract page for arXiv paper 1707.02514: An Adaptive, Multivariate Partitioning Algorithm for Global Optimization of Nonconvex Programs https://openreview.net/forum?id=xqyDqMojMfC Constrained Stochastic Nonconvex Optimization with State-dependent Markov Data | OpenReview We provide a projection-free stochastic algorithm for nonconvex optimization with state-dependent Markov data with applications to strategic classification and... constrained stochastic nonconvex optimization state https://openreview.net/forum?id=IzqZbNMZ0M Private Zeroth-Order Nonsmooth Nonconvex Optimization | OpenReview We introduce a new zeroth-order algorithm for private stochastic optimization on nonconvex and nonsmooth objectives. Given a dataset of size $M$, our algorithm... zeroth order private nonconvex optimization openreview https://openreview.net/forum?id=jj1o2SD3PB Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization | OpenReview Minimax optimization recently is widely applied in many machine learning tasks such as generative adversarial networks, robust learning and reinforcement... enhanced adaptive gradient algorithms nonconvex https://openreview.net/forum?id=GiUpEVQmNx8 SAPD+: An Accelerated Stochastic Method for Nonconvex-Concave Minimax Problems | OpenReview sapd accelerated stochastic method https://jmlr.org/papers/v26/24-0891.html A New Random Reshuffling Method for Nonsmooth Nonconvex Finite-sum Optimization a new finite sum random method https://openreview.net/forum?id=hx2Ckkzdf53 Stochastic Anderson Mixing for Nonconvex Stochastic Optimization | OpenReview We propose a stochastic version of Anderson mixing which has theoretical guarantees and shows promising results in training neural networks. stochastic anderson mixing nonconvex optimization https://openreview.net/forum?id=mHyCz0KHOu&referrer=%5Bthe%20profile%20of%20Francesco%20Orabona%5D(%2Fprofile%3Fid%3D~Francesco_Orabona1) Dual Averaging Converges for Nonconvex Smooth Stochastic Optimization | OpenReview Dual averaging and gradient descent with their stochastic variants stand as the two canonical recipe books for first-order optimization: Every modern variant... stochastic optimization dual averaging converges nonconvex https://www.jmlr.org/papers/v26/24-1991.html Revisiting Gradient Normalization and Clipping for Nonconvex SGD under Heavy-Tailed Noise:... https://openreview.net/forum?id=VA1YpcNr7ul DASHA: Distributed Nonconvex Optimization with Communication Compression and Optimal Oracle... We provide a new method that improves the state-of-the-art theoretical complexity of distributed optimization methods with compressed communication in the... dasha distributed nonconvex optimization communication https://stanford.edu/~boyd/papers/noncvx_mpc_refr.html Nonconvex Model Predictive Control for Commercial Refrigeration model predictive control for commercial nonconvex refrigeration https://jmlr.org/papers/v24/21-0571.html An Inertial Block Majorization Minimization Framework for Nonsmooth Nonconvex Optimization majorization minimization inertial block framework nonconvex https://ideas.repec.org/p/pra/mprapa/17486.html Nonconvex Margins of Output Adjustment and Aggregate Fluctuations Downloadable! In most manufacturing industries output is adjusted in a lumpy way along three margins: shiftwork, weekend work, and closing a plant temporarily... nonconvex margins output adjustment aggregate https://www.frontiersin.org/journals/chemical-engineering/articles/10.3389/fceng.2022.983162/full Frontiers | A feasible path-based branch and bound algorithm for strongly nonconvex MINLP problems branch and bound algorithm https://deepai.org/publication/finding-second-order-stationary-point-for-nonconvex-strongly-concave-minimax-problem Finding Second-Order Stationary Point for Nonconvex-Strongly-Concave Minimax Problem | DeepAI Oct 10, 2021 - 10/10/21 - We study the smooth minimax optimization problem of the form min_ xmax_ y f( x, y), where the objective function is strongly-conca... second order stationary point https://deepai.org/publication/nonconvex-demixing-from-bilinear-measurements Nonconvex Demixing From Bilinear Measurements | DeepAI Sep 18, 2018 - 09/18/18 - We consider the problem of demixing a sequence of source signals from the sum of noisy bilinear measurements. It is a generalized ... nonconvex demixing bilinear measurements deepai https://openreview.net/forum?id=AUeTkSymOq Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with... In practical distributed systems, workers are typically not homogeneous, and due to differences in hardware configurations and network conditions, can have... https://arxiv.org/abs/2404.09438?context=cs.LG [2404.09438] Developing Lagrangian-based Methods for Nonsmooth Nonconvex Optimization Abstract page for arXiv paper 2404.09438: Developing Lagrangian-based Methods for Nonsmooth Nonconvex Optimization 2404 developing lagrangian based methods https://jmlr.org/papers/v21/18-352.html AdaGrad stepsizes: Sharp convergence over nonconvex landscapes adagrad sharp convergence nonconvex landscapes https://openreview.net/forum?id=VqnEAUnfvu Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization | OpenReview gradient free stochastic optimization faster algorithms nonconvex https://arxiv.org/abs/2109.12257v1 [2109.12257v1] Tensor Full Feature Measure and Its Nonconvex Relaxation Applications to Tensor... Abstract page for arXiv paper 2109.12257v1: Tensor Full Feature Measure and Its Nonconvex Relaxation Applications to Tensor Recovery full feature https://arxiv.org/abs/2111.07618 [2111.07618] Inexact proximal DC Newton-type method for nonconvex composite functions Abstract page for arXiv paper 2111.07618: Inexact proximal DC Newton-type method for nonconvex composite functions https://jmlr.org/papers/v26/23-1104.html Near-Optimal Nonconvex-Strongly-Convex Bilevel Optimization with Fully First-Order Oracles bilevel optimization https://openreview.net/forum?id=CvYBvgEUK9 On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation |... In this work, we study first-order algorithms for solving Bilevel Optimization (BO) where the objective functions are smooth but possibly nonconvex in both... penalty methods bilevel optimization https://arxiv.org/abs/2106.09663 [2106.09663] A Short Note of PAGE: Optimal Convergence Rates for Nonconvex Optimization Abstract page for arXiv paper 2106.09663: A Short Note of PAGE: Optimal Convergence Rates for Nonconvex Optimization a short note https://openreview.net/forum?id=LVqWNYhPXR Generalized Smooth Bilevel Optimization with Nonconvex Lower-Level | OpenReview Bilevel optimization is widely applied in many machine learning tasks such as hyper-parameter learning and meta learning. Recently, many algorithms have been... bilevel optimization generalized smooth nonconvex lower https://openreview.net/forum?id=Jk1i_UufoBX TiAda: A Time-scale Adaptive Algorithm for Nonconvex Minimax Optimization | OpenReview Adaptive gradient methods have shown their ability to adjust the stepsizes on the fly in a parameter-agnostic manner, and empirically achieve faster... a time adaptive algorithm scale https://arxiv.org/abs/1905.11982v1 [1905.11982v1] Distributed Optimization of Nonconvex Functions over Time-Varying Graphs Abstract page for arXiv paper 1905.11982v1: Distributed Optimization of Nonconvex Functions over Time-Varying Graphs over time 1905 distributed optimization https://www.umu.se/en/research/projects/trade-offs-in-nonconvex-learning/ Trade-offs in Nonconvex Learning trade offs nonconvex learning https://jmlr.org/papers/v24/22-0522.html Restarted Nonconvex Accelerated Gradient Descent: No More Polylogarithmic Factor in the in the... gradient descent no more restarted nonconvex accelerated https://jmlr.org/papers/v24/22-1518.html Zeroth-Order Alternating Gradient Descent Ascent Algorithms for A Class of Nonconvex-Nonconcave... https://deepai.org/publication/median-truncated-nonconvex-approach-for-phase-retrieval-with-outliers Median-Truncated Nonconvex Approach for Phase Retrieval with Outliers | DeepAI Mar 11, 2016 - 03/11/16 - This paper investigates the phase retrieval problem, which aims to recover a signal from the magnitudes of its linear measurements... phase retrieval median truncated nonconvex approach https://deepai.org/publication/differentially-private-temporal-difference-learning-with-stochastic-nonconvex-strongly-concave-optimization Differentially Private Temporal Difference Learning with Stochastic Nonconvex-Strongly-Concave... Jan 25, 2022 - 01/25/22 - Temporal difference (TD) learning is a widely used method to evaluate policies in reinforcement learning. While many TD learning m... temporal difference learning private stochastic nonconvex strongly https://jmlr.org/papers/v26/24-1991.html Revisiting Gradient Normalization and Clipping for Nonconvex SGD under Heavy-Tailed Noise:...