:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Liu, Xinshun, Xin, He, Hui, Mao, Jing, Liu, Weizhong, Lai, Qingwen, Ye
Natura:	Preprint
Pubblicazione:	2020
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2005.04088
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Unified Transfer Learning Models in High-Dimensional Linear Regression
di: Liu, Shuo Shuo
Pubblicazione: (2023)

Learning Cross-Domain Representations for Transferable Drug Perturbations on Single-Cell Transcriptional Responses
di: Liu, Hui, et al.
Pubblicazione: (2024)

Automated Architecture Synthesis for Arbitrarily Structured Neural Networks
di: Liu, Xinshun, et al.
Pubblicazione: (2023)

Expectation Error Bounds for Transfer Learning in Linear Regression and Linear Neural Networks
di: Liu, Meitong, et al.
Pubblicazione: (2026)

Transfer Learning for Kernel-based Regression
di: Wang, Chao, et al.
Pubblicazione: (2023)

SEARL: Joint Optimization of Policy and Tool Graph Memory for Self-Evolving Agents
di: Feng, Xinshun, et al.
Pubblicazione: (2026)

DIIT: A Domain-Invariant Information Transfer Method for Industrial Cross-Domain Recommendation
di: Huang, Heyuan, et al.
Pubblicazione: (2024)

Automatic Piecewise Linear Regression for Predicting Student Learning Satisfaction
di: Choi, Haemin, et al.
Pubblicazione: (2025)

Coefficient Shape Transfer Learning for Functional Linear Regression
di: Jiao, Shuhao, et al.
Pubblicazione: (2025)

In-context Learning for Mixture of Linear Regressions: Existence, Generalization and Training Dynamics
di: Jin, Yanhao, et al.
Pubblicazione: (2024)

Transfer Learning of CATE with Kernel Ridge Regression
di: Kim, Seok-Jin, et al.
Pubblicazione: (2025)

Transfer Learning for Benign Overfitting in High-Dimensional Linear Regression
di: Kim, Yeichan, et al.
Pubblicazione: (2025)

Attack-Resistant Uniform Fairness for Linear and Smooth Contextual Bandits
di: Zhang, Qingwen, et al.
Pubblicazione: (2026)

Towards Efficient Automatic Self-Pruning of Large Language Models
di: Huang, Weizhong, et al.
Pubblicazione: (2025)

Prompt Transfer for Dual-Aspect Cross Domain Cognitive Diagnosis
di: Liu, Fei, et al.
Pubblicazione: (2024)

Transferability-Guided Cross-Domain Cross-Task Transfer Learning
di: Tan, Yang, et al.
Pubblicazione: (2022)

Behavior Tokens Speak Louder: Disentangled Explainable Recommendation with Behavior Vocabulary
di: Feng, Xinshun, et al.
Pubblicazione: (2025)

The Common Intuition to Transfer Learning Can Win or Lose: Case Studies for Linear Regression
di: Dar, Yehuda, et al.
Pubblicazione: (2021)

Task Shift: From Classification to Regression in Overparameterized Linear Models
di: LaBonte, Tyler, et al.
Pubblicazione: (2025)

Beyond the Node: Clade-level Selection for Efficient MCTS in Automatic Heuristic Design
di: Lai, Kezhao, et al.
Pubblicazione: (2026)

Frequency-Domain Regularized Adversarial Alignment for Transferable Attacks against Closed-Source MLLMs
di: Yuan, Leitao, et al.
Pubblicazione: (2026)

Enhancing Continuous Domain Adaptation with Multi-Path Transfer Curriculum
di: Liu, Hanbing, et al.
Pubblicazione: (2024)

AdaTrans: Feature-wise and Sample-wise Adaptive Transfer Learning for High-dimensional Regression
di: He, Zelin, et al.
Pubblicazione: (2024)

Cross-Domain Pre-training with Language Models for Transferable Time Series Representations
di: Cheng, Mingyue, et al.
Pubblicazione: (2024)

Semi-supervised Domain Adaptation in Graph Transfer Learning
di: Qiao, Ziyue, et al.
Pubblicazione: (2023)

Optimal Transport-Based Domain Adaptation for Rotated Linear Regression
di: Britos, Brian, et al.
Pubblicazione: (2025)

Optimal Cross-Validation for Sparse Linear Regression
di: Cory-Wright, Ryan, et al.
Pubblicazione: (2023)

Transformers Handle Endogeneity in In-Context Linear Regression
di: Liang, Haodong, et al.
Pubblicazione: (2024)

ECAT: A Entire space Continual and Adaptive Transfer Learning Framework for Cross-Domain Recommendation
di: Hou, Chaoqun, et al.
Pubblicazione: (2024)

TransFusion: Covariate-Shift Robust Transfer Learning for High-Dimensional Regression
di: He, Zelin, et al.
Pubblicazione: (2024)

Efficient Sparse Least Absolute Deviation Regression with Differential Privacy
di: Liu, Weidong, et al.
Pubblicazione: (2024)

AVP-Fusion: Adaptive Multi-Modal Fusion and Contrastive Learning for Two-Stage Antiviral Peptide Identification
di: Wen, Xinru, et al.
Pubblicazione: (2025)

Learning a Class of Mixed Linear Regressions: Global Convergence under General Data Conditions
di: Liu, Yujing, et al.
Pubblicazione: (2025)

One for All: A Non-Linear Transformer can Enable Cross-Domain Generalization for In-Context Reinforcement Learning
di: He, Bowen, et al.
Pubblicazione: (2026)

Automatic Self-supervised Learning for Social Recommendations
di: He, Xin, et al.
Pubblicazione: (2024)

A Centralized-Distributed Transfer Model for Cross-Domain Recommendation Based on Multi-Source Heterogeneous Transfer Learning
di: Xu, Ke, et al.
Pubblicazione: (2024)

ParaGate: Parasitic-Driven Domain Adaptation Transfer Learning for Netlist Performance Prediction
di: Sun, Bin, et al.
Pubblicazione: (2025)

Automatic Domain Adaptation by Transformers in In-Context Learning
di: Hataya, Ryuichiro, et al.
Pubblicazione: (2024)

Cross-Architecture Transfer Learning for Linear-Cost Inference Transformers
di: Choi, Sehyun
Pubblicazione: (2024)

Understanding Forgetting in Continual Learning with Linear Regression
di: Ding, Meng, et al.
Pubblicazione: (2024)