ICML "nonconvex optimization" Papers
11 papers found
A Doubly Recursive Stochastic Compositional Gradient Descent Method for Federated Multi-Level Compositional Optimization
Hongchang Gao
ICML 2024poster
A Study of First-Order Methods with a Deterministic Relative-Error Gradient Oracle
Nadav Hallak, Kfir Levy
ICML 2024poster
Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms
Yuchen Li, Laura Balzano, Deanna Needell et al.
ICML 2024poster
Convergence Guarantees for the DeepWalk Embedding on Block Models
Christopher Harker, Aditya Bhaskara
ICML 2024poster
Gradient Compressed Sensing: A Query-Efficient Gradient Estimator for High-Dimensional Zeroth-Order Optimization
Ruizhong Qiu, Hanghang Tong
ICML 2024poster
Quantum Algorithms and Lower Bounds for Finite-Sum Optimization
Yexin Zhang, Chenyi Zhang, Cong Fang et al.
ICML 2024poster
SPABA: A Single-Loop and Probabilistic Stochastic Bilevel Algorithm Achieving Optimal Sample Complexity
Tianshu Chu, Dachuan Xu, Wei Yao et al.
ICML 2024poster
Towards Certified Unlearning for Deep Neural Networks
Binchi Zhang, Yushun Dong, Tianhao Wang et al.
ICML 2024poster
Transformers Learn Nonlinear Features In Context: Nonconvex Mean-field Dynamics on the Attention Landscape
Juno Kim, Taiji Suzuki
ICML 2024poster
Tuning-Free Stochastic Optimization
Ahmed Khaled, Chi Jin
ICML 2024spotlight
Zeroth-Order Methods for Constrained Nonconvex Nonsmooth Stochastic Optimization
Zhuanghua Liu, Cheng Chen, Luo Luo et al.
ICML 2024poster