:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Fiorini, Cosimo, Mosconi, Matteo, Buzzega, Pietro, Salami, Riccardo, Calderara, Simone
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2507.06813
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Closed-form merging of parameter-efficient modules for Federated Continual Learning
by: Salami, Riccardo, et al.
Published: (2024)

Federated Class-Incremental Learning with Hierarchical Generative Prototypes
by: Salami, Riccardo, et al.
Published: (2024)

Rethinking Layer-wise Model Merging through Chain of Merges
by: Buzzega, Pietro, et al.
Published: (2025)

STAER: Temporal Aligned Rehearsal for Continual Spiking Neural Network
by: Gianferrari, Matteo, et al.
Published: (2026)

Trajectory Forecasting through Low-Rank Adaptation of Discrete Latent Codes
by: Benaglia, Riccardo, et al.
Published: (2024)

A Second-Order Perspective on Model Compositionality and Incremental Learning
by: Porrello, Angelo, et al.
Published: (2024)

CLIP with Generative Latent Replay: a Strong Baseline for Incremental Learning
by: Frascaroli, Emanuele, et al.
Published: (2024)

Towards Robust Knowledge Removal in Federated Learning with High Data Heterogeneity
by: Santi, Riccardo, et al.
Published: (2025)

DOLFIN: Balancing Stability and Plasticity in Federated Continual Learning
by: Moussadek, Omayma, et al.
Published: (2025)

Dataless Weight Disentanglement in Task Arithmetic via Kronecker-Factored Approximate Curvature
by: Porrello, Angelo, et al.
Published: (2026)

Latent Spectral Regularization for Continual Learning
by: Frascaroli, Emanuele, et al.
Published: (2023)

Modular Embedding Recomposition for Incremental Learning
by: Panariello, Aniello, et al.
Published: (2025)

Distilling Linearized Behavior into Non-Linear Fine-Tuning for Effective Task Arithmetic
by: Sommariva, Thomas, et al.
Published: (2026)

Transporting Task Vectors across Different Architectures without Training
by: Rinaldi, Filippo, et al.
Published: (2026)

Gradient-Sign Masking for Task Vector Transport Across Pre-Trained Models
by: Rinaldi, Filippo, et al.
Published: (2025)

QuAIL: Quality-Aware Inertial Learning for Robust Training under Data Corruption
by: Sabella, Mattia, et al.
Published: (2026)

DitHub: A Modular Framework for Incremental Open-Vocabulary Object Detection
by: Cappellino, Chiara, et al.
Published: (2025)

Self-Labeling the Job Shop Scheduling Problem
by: Corsini, Andrea, et al.
Published: (2024)

May the Forgetting Be with You: Alternate Replay for Learning with Noisy Labels
by: Millunzi, Monica, et al.
Published: (2024)

Federated Learning with Graph-Based Aggregation for Traffic Forecasting
by: Banik, Audri, et al.
Published: (2025)

Byzantine-Robust Aggregation for Securing Decentralized Federated Learning
by: Cajaraville-Aboy, Diego, et al.
Published: (2024)

BESplit: Bias-Compensated Split Federated Learning with Evidential Aggregation
by: Xie, Yuhan, et al.
Published: (2026)

Coding-Enforced Resilient and Secure Aggregation for Hierarchical Federated Learning
by: Weng, Shudi, et al.
Published: (2026)

An Interpretable Client Decision Tree Aggregation process for Federated Learning
by: Argente-Garrido, Alberto, et al.
Published: (2024)

Sheaves Reloaded: A Directional Awakening
by: Fiorini, Stefano, et al.
Published: (2025)

EASTER: Embedding Aggregation-based Heterogeneous Models Training in Vertical Federated Learning
by: Wang, Shuo, et al.
Published: (2023)

Enhancing Federated Learning Through Secure Cluster-Weighted Client Aggregation
by: Ranaweera, Kanishka, et al.
Published: (2025)

Aggregation Alignment for Federated Learning with Mixture-of-Experts under Data Heterogeneity
by: Fang, Zihan, et al.
Published: (2026)

Algebraic Priors for Approximately Equivariant Networks
by: Ali, Riccardo, et al.
Published: (2025)

Bayesian Federated Learning for Continual Training
by: Milasheuski, Usevalad, et al.
Published: (2025)

SIRI: Self-Internalizing Reinforcement Learning with Intrinsic Skills for LLM Agent Training
by: He, Zhongyu, et al.
Published: (2026)

Towards Batch-to-Streaming Deep Reinforcement Learning for Continuous Control
by: De Monte, Riccardo, et al.
Published: (2026)

Enhancing Federated Class-Incremental Learning via Spatial-Temporal Statistics Aggregation
by: Guan, Zenghao, et al.
Published: (2025)

Mixed-Precision Federated Learning via Multi-Precision Over-The-Air Aggregation
by: Yuan, Jinsheng, et al.
Published: (2024)

Revisiting Gradient Staleness: Evaluating Distance Metrics for Asynchronous Federated Learning Aggregation
by: Wilhelm, Patrick, et al.
Published: (2026)

FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation
by: Liu, Xiang, et al.
Published: (2023)

Metric Learning for Clifford Group Equivariant Neural Networks
by: Ali, Riccardo, et al.
Published: (2024)

Over-the-Air Federated Learning via Weighted Aggregation
by: Azimi-Abarghouyi, Seyed Mohammad, et al.
Published: (2024)

Efficient Reinforcement Learning from Human Feedback via Bayesian Preference Inference
by: Cercola, Matteo, et al.
Published: (2025)

Intrinsically Interpretable Attention via Sparse Post-Training
by: Draye, Florent, et al.
Published: (2025)