:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zheng, Amber Yijia, He, Tong, Qiu, Yixuan, Wang, Minjie, Wipf, David
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2403.04763
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

AutoRDF2GML: Facilitating RDF Integration in Graph Machine Learning
by: Färber, Michael, et al.
Published: (2024)

Robust Angular Synchronization via Directed Graph Neural Networks
by: He, Yixuan, et al.
Published: (2023)

Explicit Preference Optimization: No Need for an Implicit Reward Model
by: Hu, Xiangkun, et al.
Published: (2025)

Functional Bilevel Optimization for Machine Learning
by: Petrulionyte, Ieva, et al.
Published: (2024)

Griffin: Towards a Graph-Centric Relational Database Foundation Model
by: Wang, Yanbo, et al.
Published: (2025)

RDBLearn: Simple In-Context Prediction Over Relational Databases
by: Zhang, Yanlin, et al.
Published: (2026)

No Need to Train Your RDB Foundation Model
by: Xu, Linjie, et al.
Published: (2026)

Rethinking Graph Generalization through the Lens of Sharpness-Aware Minimization
by: Qiu, Yang, et al.
Published: (2026)

FreshGNN: Reducing Memory Access via Stable Historical Embeddings for Graph Neural Network Training
by: Huang, Kezhao, et al.
Published: (2023)

Bloom Filter Encoding for Machine Learning
by: Cartmell, John, et al.
Published: (2025)

Sparse Autoencoders, Again?
by: Lu, Yin, et al.
Published: (2025)

ELF-Gym: Evaluating Large Language Models Generated Features for Tabular Prediction
by: Zhang, Yanlin, et al.
Published: (2024)

Synthesize, Retrieve, and Propagate: A Unified Predictive Modeling Framework for Relational Databases
by: Li, Ning, et al.
Published: (2025)

Learning to Fuse Temporal Proximity Networks: A Case Study in Chimpanzee Social Interactions
by: He, Yixuan, et al.
Published: (2025)

MuseGNN: Forming Scalable, Convergent GNN Layers that Minimize a Sampling-Based Energy
by: Jiang, Haitian, et al.
Published: (2023)

How Graph Neural Networks Learn: Lessons from Training Dynamics
by: Yang, Chenxiao, et al.
Published: (2023)

Learning Theory for Kernel Bilevel Optimization
by: Khoury, Fares El, et al.
Published: (2025)

Safe Multi-Agent Reinforcement Learning with Bilevel Optimization in Autonomous Driving
by: Zheng, Zhi, et al.
Published: (2024)

Implicit vs Unfolded Graph Neural Networks
by: Yang, Yongyi, et al.
Published: (2021)

A Quasi-Wasserstein Loss for Learning Graph Neural Networks
by: Cheng, Minjie, et al.
Published: (2023)

CoBo: Collaborative Learning via Bilevel Optimization
by: Hashemi, Diba, et al.
Published: (2024)

Knowledge Distillation Detection for Open-weights Models
by: Shi, Qin, et al.
Published: (2025)

Handling Distribution Shifts on Graphs: An Invariance Perspective
by: Wu, Qitian, et al.
Published: (2022)

Decentralized Gossip Mutual Learning (GML) for automatic head and neck tumor segmentation
by: Chen, Jingyun, et al.
Published: (2024)

Fast and Accurate Graph Learning for Huge Data via Minipatch Ensembles
by: Yao, Tianyi, et al.
Published: (2021)

Generalization of Graph Neural Networks through the Lens of Homomorphism
by: Li, Shouheng, et al.
Published: (2024)

Model Immunization from a Condition Number Perspective
by: Zheng, Amber Yijia, et al.
Published: (2025)

Decentralized Gossip Mutual Learning (GML) for brain tumor segmentation on multi-parametric MRI
by: Chen, Jingyun, et al.
Published: (2024)

Modeling Edge-Specific Node Features through Co-Representation Neural Hypergraph Diffusion
by: Zheng, Yijia, et al.
Published: (2024)

Efficient Link Prediction via GNN Layers Induced by Negative Sampling
by: Wang, Yuxin, et al.
Published: (2023)

Robust Ante-hoc Graph Explainer using Bilevel Optimization
by: Luong, Kha-Dinh, et al.
Published: (2023)

Online Nonconvex Bilevel Optimization with Bregman Divergences
by: Bohne, Jason, et al.
Published: (2024)

LossLens: Diagnostics for Machine Learning through Loss Landscape Visual Analytics
by: Xie, Tiankai, et al.
Published: (2024)

ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting
by: Pan, Rui, et al.
Published: (2024)

Non-Stationary Functional Bilevel Optimization
by: Bohne, Jason, et al.
Published: (2026)

Low-Resource Machine Translation through the Lens of Personalized Federated Learning
by: Moskvoretskii, Viktor, et al.
Published: (2024)

Your Offline Policy is Not Trustworthy: Bilevel Reinforcement Learning for Sequential Portfolio Optimization
by: Yuan, Haochen, et al.
Published: (2025)

Riemannian Bilevel Optimization
by: Dutta, Sanchayan, et al.
Published: (2024)

Balancing Knowledge Distillation for Imbalance Learning with Bilevel Optimization
by: Nguyen, Anh B. H., et al.
Published: (2026)

SGFormer: Single-Layer Graph Transformers with Approximation-Free Linear Complexity
by: Wu, Qitian, et al.
Published: (2024)