Non-convex Optimization for Machine Learning

21 December 2017

Papers citing "Non-convex Optimization for Machine Learning"

50 / 58 papers shown

Title
Unveiling and Mitigating Adversarial Vulnerabilities in Iterative Optimizers Elad Sofer Tomer Shaked Caroline Chaux Nir Shlezinger AAML 45 0 0 26 Apr 2025
A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression Yixuan Zhang Dongyan Yudong Chen Qiaomin Xie 24 0 0 11 Apr 2025
Semiparametric Counterfactual Regression Kwangho Kim OffRL 33 0 0 03 Apr 2025
Understanding Generalization of Federated Learning: the Trade-off between Model Stability and Optimization Dun Zeng Zheshun Wu Shiyu Liu Yu Pan Xiaoying Tang Zenglin Xu MLT FedML 89 1 0 25 Nov 2024
BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning Ning Wang Shanghao Shi Yang Xiao Yimin Chen Y. T. Hou W. Lou FedML AAML 36 1 0 12 Jul 2024
Towards Efficient Risk-Sensitive Policy Gradient: An Iteration Complexity Analysis Rui Liu Erfaun Noorani Pratap Tokekar John S. Baras 23 1 0 13 Mar 2024
VideoPrism: A Foundational Visual Encoder for Video Understanding Long Zhao N. B. Gundavarapu Liangzhe Yuan Hao Zhou Shen Yan ... Huisheng Wang Hartwig Adam Mikhail Sirotenko Ting Liu Boqing Gong VGen 41 29 0 20 Feb 2024
Quantum Langevin Dynamics for Optimization Zherui Chen Yuchen Lu Hao Wang Yizhou Liu Tongyang Li AI4CE 21 9 0 27 Nov 2023
IW-GAE: Importance Weighted Group Accuracy Estimation for Improved Calibration and Model Selection in Unsupervised Domain Adaptation Taejong Joo Diego Klabjan 43 1 0 16 Oct 2023
Provably Accelerating Ill-Conditioned Low-rank Estimation via Scaled Gradient Descent, Even with Overparameterization Cong Ma Xingyu Xu Tian Tong Yuejie Chi 18 9 0 09 Oct 2023
Newton Method-based Subspace Support Vector Data Description Fahad Sohrab Firas Laakom Moncef Gabbouj 11 5 0 25 Sep 2023
Massively Parallel Continuous Local Search for Hybrid SAT Solving on GPUs Yunuo Cen Zhiwei Zhang Xuanyao Fong 14 1 0 29 Aug 2023
Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability Usha Bhalla Suraj Srinivas Himabindu Lakkaraju FAtt CML 29 6 0 27 Jul 2023
ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional Compression Avetik G. Karagulyan Peter Richtárik FedML 31 6 0 08 Mar 2023
Maximum Optimality Margin: A Unified Approach for Contextual Linear Programming and Inverse Linear Programming Chunlin Sun Shang Liu Xiaocheng Li 19 9 0 26 Jan 2023
Optimal Algorithms for Latent Bandits with Cluster Structure S. Pal A. Suggala Karthikeyan Shanmugam Prateek Jain 31 9 0 17 Jan 2023
Global Optimization with Parametric Function Approximation Chong Liu Yu-Xiang Wang 28 7 0 16 Nov 2022
Stochastic noise can be helpful for variational quantum algorithms Junyu Liu Frederik Wilde A. A. Mele Liang Jiang Jens Eisert Jens Eisert 24 34 0 13 Oct 2022
Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation Shinsaku Sakaue Taihei Oki 19 3 0 17 Sep 2022
Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization Tianyi Lin Zeyu Zheng Michael I. Jordan 51 51 0 12 Sep 2022
Online Low Rank Matrix Completion Prateek Jain S. Pal 42 9 0 08 Sep 2022
Large-displacement 3D Object Tracking with Hybrid Non-local Optimization Xuhui Tian Xinran Lin Fan Zhong Xueying Qin 31 7 0 26 Jul 2022
Metric Optimization in Penner Coordinates Ryan Capouellez Denis Zorin 11 3 0 23 Jun 2022
Efficient Minimax Optimal Global Optimization of Lipschitz Continuous Multivariate Functions Kaan Gokcesu Hakan Gokcesu 15 2 0 06 Jun 2022
Randomized Policy Optimization for Optimal Stopping Xinyi Guan V. Mišić 11 2 0 25 Mar 2022
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning Wei Huang Chunrui Liu Yilan Chen Tianyu Liu R. Xu BDL MLT 19 2 0 04 Feb 2022
Federated Optimization of Smooth Loss Functions Ali Jadbabaie A. Makur Devavrat Shah FedML 21 7 0 06 Jan 2022
On Asymptotic Linear Convergence of Projected Gradient Descent for Constrained Least Squares Trung Vu Raviv Raich 15 13 0 22 Dec 2021
Variance Reduction based Experience Replay for Policy Optimization Hua Zheng Wei Xie M. Feng OffRL 31 2 0 17 Oct 2021
Optimization with Constraint Learning: A Framework and Survey Adejuyigbe O. Fajemisin Donato Maragno D. Hertog 58 46 0 05 Oct 2021
Sinkhorn Distributionally Robust Optimization Jie Wang Rui Gao Yao Xie 46 35 0 24 Sep 2021
Towards Robustness Against Natural Language Word Substitutions Xinshuai Dong A. Luu Rongrong Ji Hong Liu SILM AAML 29 113 0 28 Jul 2021
Point-Cloud Deep Learning of Porous Media for Permeability Prediction Ali Kashefi T. Mukerji 3DPC AI4CE 15 34 0 18 Jul 2021
Data-informed Deep Optimization Lulu Zhang Z. Xu Yaoyu Zhang AI4CE 27 3 0 17 Jul 2021
Counterfactual Explanations for Arbitrary Regression Models Thomas Spooner Danial Dervovic Jason Long Jon Shepard Jiahao Chen Daniele Magazzeni 24 26 0 29 Jun 2021
Accelerating variational quantum algorithms with multiple quantum processors Yuxuan Du Yan Qian Dacheng Tao 9 8 0 24 Jun 2021
A Survey on Fault-tolerance in Distributed Optimization and Machine Learning Shuo Liu AI4CE OOD 47 13 0 16 Jun 2021
HePPCAT: Probabilistic PCA for Data with Heteroscedastic Noise David Hong Kyle Gilman Laura Balzano Jeffrey A. Fessler 32 18 0 10 Jan 2021
First-Order Methods for Convex Optimization Pavel Dvurechensky Mathias Staudigl Shimrit Shtern ODL 23 25 0 04 Jan 2021
Spectral Methods for Data Science: A Statistical Perspective Yuxin Chen Yuejie Chi Jianqing Fan Cong Ma 34 165 0 15 Dec 2020
Locally Linear Embedding and its Variants: Tutorial and Survey Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley 14 28 0 22 Nov 2020
GPU Accelerated Convex Approximations for Fast Multi-Agent Trajectory Optimization Fatemeh Rastgar Houman Masnavi Jatan Shrestha Karl Kruusamäe A. Aabloo A. K. Singh 16 8 0 09 Nov 2020
Gradient-Based Empirical Risk Minimization using Local Polynomial Regression Ali Jadbabaie A. Makur Devavrat Shah 28 6 0 04 Nov 2020
Accurate and Lightweight Image Super-Resolution with Model-Guided Deep Unfolding Network Qiang Ning W. Dong Guangming Shi Leida Li Xin Li 21 44 0 14 Sep 2020
PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization Zhize Li Hongyan Bao Xiangliang Zhang Peter Richtárik ODL 31 125 0 25 Aug 2020
An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias Lu Yu Krishnakumar Balasubramanian S. Volgushev Murat A. Erdogdu 35 50 0 14 Jun 2020
Scalable Thompson Sampling using Sparse Gaussian Process Models Sattar Vakili Henry B. Moss A. Artemev Vincent Dutordoir Victor Picheny 8 34 0 09 Jun 2020
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent Tian Tong Cong Ma Yuejie Chi 19 113 0 18 May 2020
On the Sample Complexity and Optimization Landscape for Quadratic Feasibility Problems Parth Thaker Gautam Dasarathy Angelia Nedić 16 5 0 04 Feb 2020
State Space Emulation and Annealed Sequential Monte Carlo for High Dimensional Optimization Chencheng Cai Rong Chen 11 0 0 17 Nov 2019