:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Rao, Yang
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2509.22766
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning the Model While Learning Q: Finite-Time Sample Complexity of Online SyncMBQ
by: Lim, Han-Dong, et al.
Published: (2024)

Adaptive auditing of AI systems with anytime-valid guarantees
by: Zhou, Siyu, et al.
Published: (2026)

A universal policy wrapper with guarantees
by: Bolychev, Anton, et al.
Published: (2025)

Finding Kissing Numbers with Game-theoretic Reinforcement Learning
by: Ma, Chengdong, et al.
Published: (2025)

SyncMapV2: Robust and Adaptive Unsupervised Segmentation
by: Zhang, Heng, et al.
Published: (2025)

Information-theoretic Distinctions Between Deception and Confusion
by: Young, Robin
Published: (2025)

A Shared Low-Rank Adaptation Approach to Personalized RLHF
by: Liu, Renpu, et al.
Published: (2025)

Ranking-aware Reinforcement Learning for Ordinal Ranking
by: Hao, Aiming, et al.
Published: (2026)

A Pre-training Framework for Relational Data with Information-theoretic Principles
by: Truong, Quang, et al.
Published: (2025)

Game-theoretic Counterfactual Explanation for Graph Neural Networks
by: Chhablani, Chirag, et al.
Published: (2024)

AROMA: Autonomous Rank-one Matrix Adaptation
by: Sheng, Hao Nan, et al.
Published: (2025)

SPD: Sync-Point Drop for Efficient Tensor Parallelism of Large Language Models
by: Kim, Han-Byul, et al.
Published: (2025)

StyleLipSync: Style-based Personalized Lip-sync Video Generation
by: Ki, Taekyung, et al.
Published: (2023)

SparseRL-Sync: Lossless Weight Synchronization with ~100x Less Communication
by: Hu, Lucas, et al.
Published: (2026)

A theoretical framework for self-supervised contrastive learning for continuous dependent data
by: Marusov, Alexander, et al.
Published: (2025)

AR1-ZO: Topology-Aware Rank-1 Zeroth-Order Queries for High-Rank LoRA Fine-Tuning
by: Chen, Ziye, et al.
Published: (2026)

Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning
by: Zhao, Ziyu, et al.
Published: (2025)

Low-Rank Compression of Language Models via Differentiable Rank Selection
by: Sundrani, Sidhant, et al.
Published: (2025)

Performance of Small Language Model Pretraining on FABRIC: An Empirical Study
by: Rao, Praveen
Published: (2026)

Confident Feature Ranking
by: Neuhof, Bitya, et al.
Published: (2023)

Global Low-Rank, Local Full-Rank: The Holographic Encoding of Learned Algorithms
by: Xu, Yongzhong
Published: (2026)

Using Synthetic Data to estimate the True Error is theoretically and practically doable
by: Thanh, Hai Hoang, et al.
Published: (2025)

The geometry of invariant learning: an information-theoretic analysis of data augmentation and generalization
by: Bouyahia, Abdelali, et al.
Published: (2026)

An information theoretic approach to quantify the stability of feature selection and ranking algorithms
by: Alaiz-Rodriguez, et al.
Published: (2024)

Training Acceleration of Low-Rank Decomposed Networks using Sequential Freezing and Rank Quantization
by: Hajimolahoseini, Habib, et al.
Published: (2023)

Graph Ranking Contrastive Learning: A Extremely Simple yet Efficient Method
by: Hu, Yulan, et al.
Published: (2023)

Visual Sync: Multi-Camera Synchronization via Cross-View Object Motion
by: Liu, Shaowei, et al.
Published: (2025)

Networks of Causal Abstractions: A Sheaf-theoretic Framework
by: D'Acunto, Gabriele, et al.
Published: (2025)

Unbiased Gradient Low-Rank Projection
by: Pan, Rui, et al.
Published: (2025)

Decomposed Trust: Privacy, Adversarial Robustness, Ethics, and Fairness in Low-Rank LLMs
by: Asante, Daniel Agyei, et al.
Published: (2025)

Sparse High Rank Adapters
by: Bhardwaj, Kartikeya, et al.
Published: (2024)

Clustered Policy Decision Ranking
by: Levin, Mark, et al.
Published: (2023)

A Statistical Framework for Ranking LLM-Based Chatbots
by: Ameli, Siavash, et al.
Published: (2024)

Polynomial Expansion Rank Adaptation: Enhancing Low-Rank Fine-Tuning with High-Order Interactions
by: Zhang, Wenhao, et al.
Published: (2026)

L2R: Low-Rank and Lipschitz-Controlled Routing for Mixture-of-Experts
by: Yang, Minghao, et al.
Published: (2026)

Enhancing Parameter Efficiency and Generalization in Large-Scale Models: A Regularized and Masked Low-Rank Adaptation Approach
by: Mao, Yuzhu, et al.
Published: (2024)

Joint Tensor-Train Parameterization for Efficient and Expressive Low-Rank Adaptation
by: Qi, Jun, et al.
Published: (2025)

Fundamental Components of Deep Learning: A category-theoretic approach
by: Gavranović, Bruno
Published: (2024)

On minimizers and convolutional filters: theoretical connections and applications to genome analysis
by: Yu, Yun William
Published: (2021)

Rank Also Matters: Hierarchical Configuration for Mixture of Adapter Experts in LLM Fine-Tuning
by: Cong, Peizhuang, et al.
Published: (2025)