Poster "convergence guarantees" Papers
12 papers found
Conference
Absorb and Converge: Provable Convergence Guarantee for Absorbing Discrete Diffusion Models
Yuchen Liang, Renxiang Huang, Lifeng LAI et al.
NEURIPS 2025arXiv:2506.02318
6
citations
AdaGrad under Anisotropic Smoothness
Yuxing Liu, Rui Pan, Tong Zhang
ICLR 2025arXiv:2406.15244
14
citations
A Difference-of-Convex Functions Approach to Energy-Based Iterative Reasoning
Daniel Tschernutter, David Diego Castro, Maciej Kasiński
NEURIPS 2025
A Stochastic Approach to the Subset Selection Problem via Mirror Descent
Dan Greenstein, Elazar Gershuni, Ilan Ben-Bassat et al.
ICLR 2025
Discrete Diffusion Models: Novel Analysis and New Sampler Guarantees
Yuchen Liang, Yingbin Liang, Lifeng LAI et al.
NEURIPS 2025arXiv:2509.16756
3
citations
Extragradient Method for $(L_0, L_1)$-Lipschitz Root-finding Problems
Sayantan Choudhury, Nicolas Loizou
NEURIPS 2025arXiv:2510.22421
Globally Optimal Policy Gradient Algorithms for Reinforcement Learning with PID Control Policies
Vipul Sharma, Wesley Suttle, S Sivaranjani
NEURIPS 2025
Understanding outer learning rates in Local SGD
Ahmed Khaled, Satyen Kale, Arthur Douillard et al.
NEURIPS 2025
Detecting Influence Structures in Multi-Agent Reinforcement Learning
Fabian Raoul Pieroth, Katherine Fitch, Lenz Belzner
ICML 2024
Fair Classification with Partial Feedback: An Exploration-Based Data Collection Approach
Vijay Keswani, Anay Mehrotra, L. Elisa Celis
ICML 2024arXiv:2402.11338
3
citations
FedBAT: Communication-Efficient Federated Learning via Learnable Binarization
Shiwei Li, Wenchao Xu, Haozhao Wang et al.
ICML 2024arXiv:2408.03215
12
citations
FedLMT: Tackling System Heterogeneity of Federated Learning via Low-Rank Model Training with Theoretical Guarantees
Jiahao Liu, Yipeng Zhou, Di Wu et al.
ICML 2024