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Randomized Smoothing for Stochastic Optimization

SIAM Journal on Optimization (SIOPT), 2011

22 March 2011

Papers citing "Randomized Smoothing for Stochastic Optimization"

50 / 137 papers shown

Title
Stable Coresets via Posterior Sampling: Aligning Induced and Full Loss Landscapes Wei-Kai Chang Rajiv Khanna 173 0 0 21 Nov 2025
LOTION: Smoothing the Optimization Landscape for Quantized Training Mujin Kwun Depen Morwani Chloe Huangyuan Su Stephanie Gil Nikhil Anand Sham Kakade MQ 169 1 0 09 Oct 2025
Flatness-Aware Stochastic Gradient Langevin Dynamics Stefano Bruno Youngsik Hwang Jaehyeon An Sotirios Sabanis Dong-Young Lim 140 0 0 02 Oct 2025
Linearly Convergent Algorithms for Nonsmooth Problems with Unknown Smooth Pieces Zhe Zhang S. Sra 106 0 0 25 Jul 2025
Direct Fisher Score Estimation for Likelihood Maximization Sherman Khoo Yakun Wang Song Liu Mark Beaumont 133 0 0 06 Jun 2025
A Randomized Zeroth-Order Hierarchical Framework for Heterogeneous Federated Learning Yuyang Qiu Kibaek Kim Farzad Yousefian FedML 412 0 0 02 Apr 2025
Constructive approximate transport maps with normalizing flows Antonio Álvarez-López Borjan Geshkovski Domènec Ruiz-Balet OT 270 0 0 26 Dec 2024
Explicit and Implicit Graduated Optimization in Deep Neural NetworksAAAI Conference on Artificial Intelligence (AAAI), 2024 Naoki Sato Hideaki Iiduka 148 1 0 16 Dec 2024
Faster Algorithms for User-Level Private Stochastic Convex OptimizationNeural Information Processing Systems (NeurIPS), 2024 Andrew Lowy Daogao Liu Hilal Asi 153 1 0 24 Oct 2024
Generalizing Stochastic Smoothing for Differentiation and Gradient Estimation Felix Petersen Christian Borgelt Aashwin Mishra Stefano Ermon 179 2 0 10 Oct 2024
Improved Sample Complexity for Private Nonsmooth Nonconvex Optimization Guy Kornowski Daogao Liu Kunal Talwar 217 2 0 08 Oct 2024
Improved Sample Complexity of Imitation Learning for Barrier Model Predictive Control Daniel Pfrommer Swati Padmanabhan Kwangjun Ahn Jack Umenberger Tobia Marcucci Zakaria Mhammedi Ali Jadbabaie 138 0 0 01 Oct 2024
Tight Lower Bounds under Asymmetric High-Order Hölder Smoothness and Uniform ConvexityInternational Conference on Learning Representations (ICLR), 2024 Site Bai Brian Bullins 225 2 0 16 Sep 2024
Zeroth-Order Stochastic Mirror Descent Algorithms for Minimax Excess Risk Optimization Zhihao Gu Zi Xu 264 1 0 22 Aug 2024
Faster Stochastic Optimization with Arbitrary Delays via Asynchronous Mini-Batching Amit Attia Ofir Gaash Tomer Koren 238 0 0 14 Aug 2024
Private Zeroth-Order Nonsmooth Nonconvex Optimization Qinzi Zhang Hoang Tran Ashok Cutkosky 248 5 0 27 Jun 2024
Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization A. Jambulapati Aaron Sidford Kevin Tian 196 4 0 11 Jun 2024
Demystifying SGD with Doubly Stochastic Gradients Kyurae Kim Joohwan Ko Yian Ma Jacob R. Gardner 350 2 0 03 Jun 2024
Verifiably Robust Conformal Prediction Linus Jeary Tom Kuipers Mehran Hosseini Nicola Paoletti AAML 253 9 0 29 May 2024
Lower Bounds and Optimal Algorithms for Non-Smooth Convex Decentralized Optimization over Time-Varying Networks D. Kovalev Ekaterina Borodich Alexander Gasnikov Dmitrii Feoktistov 173 2 0 28 May 2024
Adaptive Horizon Actor-Critic for Policy Learning in Contact-Rich Differentiable Simulation Ignat Georgiev K. Srinivasan Jie Xu Eric Heiden Animesh Garg 324 20 0 28 May 2024
A New Formulation for Zeroth-Order Optimization of Adversarial EXEmples in Malware Detection Marco Rando Christian Scano Lorenzo Rosasco Fabio Roli AAML 188 3 0 23 May 2024
Provably Robust Conformal Prediction with Improved Efficiency Ge Yan Yaniv Romano Tsui-Wei Weng 474 24 0 30 Apr 2024
Revisiting Random Weight Perturbation for Efficiently Improving Generalization Tao Li Qinghua Tao Weihao Yan Zehao Lei Yingwen Wu Kun Fang Mingzhen He Xiaolin Huang AAML 305 10 0 30 Mar 2024
Optimization on a Finer Scale: Bounded Local Subgradient Variation Perspective Jelena Diakonikolas Cristóbal Guzmán 825 3 0 24 Mar 2024
Efficient Combinatorial Optimization via Heat DiffusionNeural Information Processing Systems (NeurIPS), 2024 He Ma Wenlian Lu Jianfeng Feng 211 2 0 13 Mar 2024
Model-Free $μ$ -Synthesis: A Nonsmooth Optimization Perspective Darioush Keivan Xing-ming Guo Peter M. Seiler Geir Dullerud Bin Hu 151 0 0 18 Feb 2024
RAW: A Robust and Agile Plug-and-Play Watermark Framework for AI-Generated Images with Provable GuaranteesNeural Information Processing Systems (NeurIPS), 2024 Xun Xian Ganghua Wang Xuan Bi Jayanth Srinivasa Jayanth Srinivasa Mingyi Hong Jie Ding WIGM 150 6 0 23 Jan 2024
Transfer Attacks and Defenses for Large Language Models on Coding Tasks Chi Zhang Zifan Wang Ravi Mangal Matt Fredrikson Limin Jia Corina S. Pasareanu AAML SILM 156 2 0 22 Nov 2023
Nonsmooth Projection-Free Optimization with Functional Constraints Kamiar Asgari Michael J. Neely 164 0 0 18 Nov 2023
Breaking Boundaries: Balancing Performance and Robustness in Deep Wireless Traffic Forecasting Romain Ilbert Thai V. Hoang Zonghua Zhang Themis Palpanas OOD AAML 320 1 0 16 Nov 2023
Using Stochastic Gradient Descent to Smooth Nonconvex Functions: Analysis of Implicit Graduated Optimization with Optimal Noise Scheduling Naoki Sato Hideaki Iiduka 312 4 0 15 Nov 2023
User-level Differentially Private Stochastic Convex Optimization: Efficient Algorithms with Optimal RatesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 Hilal Asi Daogao Liu 209 13 0 07 Nov 2023
Compression with Exact Error Distribution for Federated LearningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 Mahmoud Hegazy Rémi Leluc Cheuk Ting Li Hadrien Hendrikx FedML 174 17 0 31 Oct 2023
DPZero: Private Fine-Tuning of Language Models without Backpropagation Liang Zhang Bingcong Li K. K. Thekumparampil Sewoong Oh Niao He 369 20 0 14 Oct 2023
Zero Grads: Learning Local Surrogate Losses for Non-Differentiable GraphicsACM Transactions on Graphics (TOG), 2023 Michael Fischer Tobias Ritschel 226 7 0 10 Aug 2023
Fighting Uncertainty with Gradients: Offline Reinforcement Learning via Diffusion Score MatchingConference on Robot Learning (CoRL), 2023 H.J. Terry Suh Glen Chou Hongkai Dai Lujie Yang Abhishek Gupta Russ Tedrake DiffM OffRL 212 14 0 24 Jun 2023
Memory-Query Tradeoffs for Randomized Convex OptimizationIEEE Annual Symposium on Foundations of Computer Science (FOCS), 2023 Xinyu Chen Binghui Peng 180 8 0 21 Jun 2023
How to escape sharp minima with random perturbationsInternational Conference on Machine Learning (ICML), 2023 Kwangjun Ahn Ali Jadbabaie S. Sra ODL 336 12 0 25 May 2023
Computationally Efficient and Statistically Optimal Robust High-Dimensional Linear Regression Yinan Shen Jingyang Li Jian-Feng Cai Dong Xia 217 2 0 10 May 2023
ELF: Federated Langevin Algorithms with Primal, Dual and Bidirectional CompressionConference on Uncertainty in Artificial Intelligence (UAI), 2023 Avetik G. Karagulyan Peter Richtárik FedML 215 6 0 08 Mar 2023
Stochastic Approximation Beyond Gradient for Signal Processing and Machine LearningIEEE Transactions on Signal Processing (IEEE TSP), 2023 Hadrien Hendrikx G. Fort Eric Moulines Hoi-To Wai 200 15 0 22 Feb 2023
Deterministic Nonsmooth Nonconvex OptimizationAnnual Conference Computational Learning Theory (COLT), 2023 Michael I. Jordan Guy Kornowski Tianyi Lin Ohad Shamir Manolis Zampetakis 389 31 0 16 Feb 2023
Mithridates: Auditing and Boosting Backdoor Resistance of Machine Learning PipelinesConference on Computer and Communications Security (CCS), 2023 Eugene Bagdasaryan Vitaly Shmatikov AAML 259 3 0 09 Feb 2023
Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex ConversionInternational Conference on Machine Learning (ICML), 2023 Ashok Cutkosky Harsh Mehta Francesco Orabona 340 47 0 07 Feb 2023
Gradient Descent with Linearly Correlated Noise: Theory and Applications to Differential PrivacyNeural Information Processing Systems (NeurIPS), 2023 Anastasia Koloskova Ryan McKenna Zachary B. Charles Keith Rush Brendan McMahan 481 14 0 02 Feb 2023
Smoothed Online Learning for Prediction in Piecewise Affine SystemsNeural Information Processing Systems (NeurIPS), 2023 Adam Block Max Simchowitz Russ Tedrake 203 13 0 26 Jan 2023
ApproxED: Approximate exploitability descent via learned best responsesAdaptive Agents and Multi-Agent Systems (AAMAS), 2023 Carlos Martin Tuomas Sandholm 330 1 0 20 Jan 2023
Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic OptimizationInternational Conference on Machine Learning (ICML), 2023 Le‐Yu Chen Jing Xu Luo Luo 205 22 0 16 Jan 2023
ReSQueing Parallel and Private Stochastic Convex OptimizationIEEE Annual Symposium on Foundations of Computer Science (FOCS), 2023 Y. Carmon A. Jambulapati Yujia Jin Y. Lee Daogao Liu Aaron Sidford Kevin Tian FedML 330 18 0 01 Jan 2023