2024 "convex optimization" Papers

19 papers found

Adaptive Proximal Gradient Methods Are Universal Without Approximation

Konstantinos Oikonomidis, Emanuel Laude, Puya Latafat et al.

ICML 2024spotlight

A New Branch-and-Bound Pruning Framework for $\ell_0$-Regularized Problems

Guyard Theo, Cédric Herzet, Clément Elvira et al.

ICML 2024poster

A Universal Transfer Theorem for Convex Optimization Algorithms Using Inexact First-order Oracles

Phillip Kerger, Marco Molinaro, Hongyi Jiang et al.

ICML 2024poster

Convex and Bilevel Optimization for Neural-Symbolic Inference and Learning

Charles Dickens, Changyu Gao, Connor Pryor et al.

ICML 2024poster

Differentially Private Domain Adaptation with Theoretical Guarantees

Raef Bassily, Corinna Cortes, Anqi Mao et al.

ICML 2024poster

Gaussian Process Neural Additive Models

Wei Zhang, Brian Barr, John Paisley

AAAI 2024paperarXiv:2402.12518
11
citations

How Free is Parameter-Free Stochastic Optimization?

Amit Attia, Tomer Koren

ICML 2024spotlight

Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm

Batiste Le Bars, Aurélien Bellet, Marc Tommasi et al.

ICML 2024poster

Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value

Young Wu, Jeremy McMahan, Yiding Chen et al.

ICML 2024poster

MoMo: Momentum Models for Adaptive Learning Rates

Fabian Schaipp, Ruben Ohana, Michael Eickenberg et al.

ICML 2024poster

New Sample Complexity Bounds for Sample Average Approximation in Heavy-Tailed Stochastic Programming

Hongcheng Liu, Jindong Tong

ICML 2024poster

On the Last-Iterate Convergence of Shuffling Gradient Methods

Zijian Liu, Zhengyuan Zhou

ICML 2024poster

Performative Prediction with Bandit Feedback: Learning through Reparameterization

Yatong Chen, Wei Tang, Chien-Ju Ho et al.

ICML 2024poster

Privacy Amplification by Iteration for ADMM with (Strongly) Convex Objective Functions

T-H. Hubert Chan, Hao Xie, Mengshi ZHAO

AAAI 2024paperarXiv:2312.08685
1
citations

Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization

Wei Jiang, Sifan Yang, Wenhao Yang et al.

ICML 2024poster

Quantum Algorithms and Lower Bounds for Finite-Sum Optimization

Yexin Zhang, Chenyi Zhang, Cong Fang et al.

ICML 2024poster

Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features

Aleksandr Beznosikov, David Dobre, Gauthier Gidel

ICML 2024poster

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.

ICML 2024poster

Tuning-Free Stochastic Optimization

Ahmed Khaled, Chi Jin

ICML 2024spotlight