Poster "stochastic optimization" Papers
33 papers found
Conference
Bi-Directional Communication-Efficient Stochastic FL via Remote Source Generation
Maximilian Egger, Rawad Bitar, Antonia Wachter-Zeh et al.
Conditional Gradient Methods with Standard LMO for Stochastic Simple Bilevel Optimization
Khanh-Hung (Bruce) Giang-Tran, Soroosh Shafiee, Nam Ho-Nguyen
Differentially Private Bilevel Optimization: Efficient Algorithms with Near-Optimal Rates
Andrew Lowy, Daogao Liu
Enforcing Hard Linear Constraints in Deep Learning Models with Decision Rules
Gonzalo E. Constante, Hao Chen, Can Li
Enhancing Optimizer Stability: Momentum Adaptation of The NGN Step-size
Rustem Islamov, Niccolò Ajroldi, Antonio Orvieto et al.
Faster Stochastic Optimization with Arbitrary Delays via Adaptive Asynchronous Mini-Batching
Amit Attia, Ofir Gaash, Tomer Koren
Finite-Time Analysis of Stochastic Nonconvex Nonsmooth Optimization on the Riemannian Manifolds
Emre Sahinoglu, Youbang Sun, Shahin Shahrampour
Learning-Augmented Online Bidding in Stochastic Settings
Spyros Angelopoulos, Bertrand Simon
New Perspectives on the Polyak Stepsize: Surrogate Functions and Negative Results
Francesco Orabona, Ryan D'Orazio
Nonconvex Stochastic Optimization under Heavy-Tailed Noises: Optimal Convergence without Gradient Clipping
Zijian Liu, Zhengyuan Zhou
Optimization with Access to Auxiliary Information
EL MAHDI CHAYTI, Sai Karimireddy
Sharpness-Aware Minimization: General Analysis and Improved Rates
Dimitris Oikonomou, Nicolas Loizou
Stochastic-Constrained Stochastic Optimization with Markovian Data
Yeongjong Kim, Dabeen Lee
Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold
Hoang Phuc Hau Luu, Hanlin Yu, Bernardo Williams et al.
Accelerated Policy Gradient for s-rectangular Robust MDPs with Large State Spaces
Ziyi Chen, Heng Huang
A Federated Stochastic Multi-level Compositional Minimax Algorithm for Deep AUC Maximization
Xinwen Zhang, Ali Payani, Myungjin Lee et al.
Dealing With Unbounded Gradients in Stochastic Saddle-point Optimization
Gergely Neu, Nneka Okolo
High-Probability Bound for Non-Smooth Non-Convex Stochastic Optimization with Heavy Tails
Langqi Liu, Yibo Wang, Lijun Zhang
High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise
Eduard Gorbunov, Abdurakhmon Sadiev, Marina Danilova et al.
Locally Differentially Private Decentralized Stochastic Bilevel Optimization with Guaranteed Convergence Accuracy
Ziqin Chen, Yongqiang Wang
Nonlinear Filtering with Brenier Optimal Transport Maps
Mohammad Al-Jarrah, Niyizhen Jin, Bamdad Hosseini et al.
No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths
Charles Guille-Escuret, Hiroki Naganuma, Kilian Fatras et al.
On The Complexity of First-Order Methods in Stochastic Bilevel Optimization
Jeongyeol Kwon, Dohyun Kwon, Hanbaek Lyu
PASOA- PArticle baSed Bayesian Optimal Adaptive design
Jacopo Iollo, Christophe Heinkelé, Pierre Alliez et al.
Position: Future Directions in the Theory of Graph Machine Learning
Christopher Morris, Fabrizio Frasca, Nadav Dym et al.
Revisiting Inexact Fixed-Point Iterations for Min-Max Problems: Stochasticity and Structured Nonconvexity
Ahmet Alacaoglu, Donghwan Kim, Stephen Wright
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features
Aleksandr Beznosikov, David Dobre, Gauthier Gidel
Stability and Generalization for Stochastic Recursive Momentum-based Algorithms for (Strongly-)Convex One to $K$-Level Stochastic Optimizations
Xiaokang Pan, Xingyu Li, Jin Liu et al.
Stochastic Optimization with Arbitrary Recurrent Data Sampling
William Powell, Hanbaek Lyu
Stochastic Weakly Convex Optimization beyond Lipschitz Continuity
Wenzhi Gao, Qi Deng
Understanding Stochastic Natural Gradient Variational Inference
Kaiwen Wu, Jacob Gardner
Variational Linearized Laplace Approximation for Bayesian Deep Learning
Luis A. Ortega, Simon Rodriguez Santana, Daniel Hernández-Lobato
Zeroth-Order Methods for Constrained Nonconvex Nonsmooth Stochastic Optimization
Zhuanghua Liu, Cheng Chen, Luo Luo et al.