:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhang, Chen, Bu, Weixin, Ren, Zeyi, Liu, Zhengwu, Wu, Yik-Chung, Wong, Ngai
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2505.14170
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Nonparametric Teaching of Attention Learners
di: Zhang, Chen, et al.
Pubblicazione: (2026)

Fighter: Unveiling the Graph Convolutional Nature of Transformers in Time Series Modeling
di: Zhang, Chen, et al.
Pubblicazione: (2025)

Nonparametric Teaching of Implicit Neural Representations
di: Zhang, Chen, et al.
Pubblicazione: (2024)

Binary Weight Multi-Bit Activation Quantization for Compute-in-Memory CNN Accelerators
di: Zhou, Wenyong, et al.
Pubblicazione: (2025)

NTK-Guided Implicit Neural Teaching
di: Zhang, Chen, et al.
Pubblicazione: (2025)

Mixture of Experts-augmented Deep Unfolding for Activity Detection in IRS-aided Systems
di: Ren, Zeyi, et al.
Pubblicazione: (2025)

Deep Unfolding with Kernel-based Quantization in MIMO Detection
di: Ren, Zeyi, et al.
Pubblicazione: (2025)

LLM-NEO: Parameter Efficient Knowledge Distillation for Large Language Models
di: Yang, Runming, et al.
Pubblicazione: (2024)

Model Evolution Under Zeroth-Order Optimization: A Neural Tangent Kernel Perspective
di: Zhang, Chen, et al.
Pubblicazione: (2026)

Extending Straight-Through Estimation for Robust Neural Networks on Analog CIM Hardware
di: Feng, Yuannuo, et al.
Pubblicazione: (2025)

HPD: Hybrid Projection Decomposition for Robust State Space Models on Analog CIM Hardware
di: Feng, Yuannuo, et al.
Pubblicazione: (2025)

ROMER: Expert Replacement and Router Calibration for Robust MoE LLMs on Analog Compute-in-Memory Systems
di: Zhou, Wenyong, et al.
Pubblicazione: (2026)

PTQTP: Post-Training Quantization to Trit-Planes for Large Language Models
di: Xiao, He, et al.
Pubblicazione: (2025)

Transformers are Minimax Optimal Nonparametric In-Context Learners
di: Kim, Juno, et al.
Pubblicazione: (2024)

To Fold or Not to Fold: Graph Regularized Tensor Train for Visual Data Completion
di: Xu, Le, et al.
Pubblicazione: (2023)

Exploring Layer-wise Information Effectiveness for Post-Training Quantization in Small Language Models
di: Xiao, He, et al.
Pubblicazione: (2025)

Efficient Generative Modeling with Unitary Matrix Product States Using Riemannian Optimization
di: Duan, Haotong, et al.
Pubblicazione: (2026)

Attention-Based Variational Framework for Joint and Individual Components Learning with Applications in Brain Network Analysis
di: Zhang, Yifei, et al.
Pubblicazione: (2026)

A General Deep Learning Framework for Wireless Resource Allocation under Discrete Constraints
di: Wang, Yikun, et al.
Pubblicazione: (2026)

Decomposing Densification in Gaussian Splatting for Faster 3D Scene Reconstruction
di: Huang, Binxiao, et al.
Pubblicazione: (2025)

NeuroPMD: Neural Fields for Density Estimation on Product Manifolds
di: Consagra, William, et al.
Pubblicazione: (2025)

Nonparametric Bayesian Optimization for General Rewards
di: Zhang, Zishi, et al.
Pubblicazione: (2026)

Revisiting Trace Norm Minimization for Tensor Tucker Completion: A Direct Multilinear Rank Learning Approach
di: Tong, Xueke, et al.
Pubblicazione: (2024)

Are Large Language Models In-Context Graph Learners?
di: Li, Jintang, et al.
Pubblicazione: (2025)

Revisiting Graph Autoencoders as Implicit Contrastive Learners
di: Li, Jintang, et al.
Pubblicazione: (2024)

Mixture-of-Subspaces in Low-Rank Adaptation
di: Wu, Taiqiang, et al.
Pubblicazione: (2024)

GraphLearner: Graph Node Clustering with Fully Learnable Augmentation
di: Yang, Xihong, et al.
Pubblicazione: (2022)

FedDSR: Federated Deep Supervision and Regularization Towards Autonomous Driving
di: Kou, Wei-Bin, et al.
Pubblicazione: (2025)

Activity Detection for Massive Connectivity in Cell-free Networks with Unknown Large-scale Fading, Channel Statistics, Noise Variance, and Activity Probability: A Bayesian Approach
di: Zhang, Hao, et al.
Pubblicazione: (2024)

Large-Scale Bayesian Tensor Reconstruction: An Approximate Message Passing Solution
di: Cheng, Bingyang, et al.
Pubblicazione: (2025)

On the Effect of Regularization on Nonparametric Mean-Variance Regression
di: Wong-Toi, Eliot, et al.
Pubblicazione: (2025)

OptiMind: Teaching LLMs to Think Like Optimization Experts
di: Zhang, Xinzhi, et al.
Pubblicazione: (2025)

LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models
di: Yang, Yifan, et al.
Pubblicazione: (2024)

Graph Positional Autoencoders as Self-supervised Learners
di: Liu, Yang, et al.
Pubblicazione: (2025)

ERASE: Error-Resilient Representation Learning on Graphs for Label Noise Tolerance
di: Chen, Ling-Hao, et al.
Pubblicazione: (2023)

BN-Pool: Bayesian Nonparametric Pooling for Graphs
di: Castellana, Daniele, et al.
Pubblicazione: (2025)

Likelihood-Free Adaptive Bayesian Inference via Nonparametric Distribution Matching
di: Lu, Wenhui Sophia, et al.
Pubblicazione: (2025)

Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator
di: Kou, Wei-Bin, et al.
Pubblicazione: (2025)

FedEMA: Federated Exponential Moving Averaging with Negative Entropy Regularizer in Autonomous Driving
di: Kou, Wei-Bin, et al.
Pubblicazione: (2025)

Understanding and Improving Adversarial Robustness of Neural Probabilistic Circuits
di: Chen, Weixin, et al.
Pubblicazione: (2025)