Shift Aggregate Extract Networks
Fuente:
arXiv
Saved in:
| Main Authors: | Orsini, Francesco, Baracchi, Daniele, Frasconi, Paolo |
|---|---|
| Format: | Preprint |
| Published: |
2017
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
The Hidden Cost of an Image: Quantifying the Energy Consumption of AI Image Generation
by: Bertazzini, Giulia, et al.
Published: (2025)
by: Bertazzini, Giulia, et al.
Published: (2025)
DRAGON: A Large-Scale Dataset of Realistic Images Generated by Diffusion Models
by: Bertazzini, Giulia, et al.
Published: (2025)
by: Bertazzini, Giulia, et al.
Published: (2025)
MARS: Sound Generation via Multi-Channel Autoregression on Spectrograms
by: Ristori, Eleonora, et al.
Published: (2025)
by: Ristori, Eleonora, et al.
Published: (2025)
Dealing with Uncertainty in Contextual Anomaly Detection
by: Bindini, Luca, et al.
Published: (2025)
by: Bindini, Luca, et al.
Published: (2025)
FedShift: Robust Federated Learning Aggregation Scheme in Resource Constrained Environment via Weight Shifting
by: Seo, Jungwon, et al.
Published: (2024)
by: Seo, Jungwon, et al.
Published: (2024)
Hyperparameter Optimization in Machine Learning
by: Franceschi, Luca, et al.
Published: (2024)
by: Franceschi, Luca, et al.
Published: (2024)
Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift
by: Ge, Jiawei, et al.
Published: (2024)
by: Ge, Jiawei, et al.
Published: (2024)
Sequential Harmful Shift Detection Without Labels
by: Amoukou, Salim I., et al.
Published: (2024)
by: Amoukou, Salim I., et al.
Published: (2024)
Interpetable Target-Feature Aggregation for Multi-Task Learning based on Bias-Variance Analysis
by: Bonetti, Paolo, et al.
Published: (2024)
by: Bonetti, Paolo, et al.
Published: (2024)
Sample-wise Constrained Learning via a Sequential Penalty Approach with Applications in Image Processing
by: Lanzillotta, Francesca, et al.
Published: (2026)
by: Lanzillotta, Francesca, et al.
Published: (2026)
Enhanced Water Leak Detection with Convolutional Neural Networks and One-Class Support Vector Machine
by: Leonzio, Daniele Ugo, et al.
Published: (2025)
by: Leonzio, Daniele Ugo, et al.
Published: (2025)
Explainable Detection of Depression Status Shifts from User Digital Traces
by: Belcastro, Loris, et al.
Published: (2026)
by: Belcastro, Loris, et al.
Published: (2026)
FRESH: Information-Geometric Calibration of Patient-Level Models to Aggregate Evidence
by: Fuller, Franklin, et al.
Published: (2026)
by: Fuller, Franklin, et al.
Published: (2026)
Robust Graph Neural Networks via Unbiased Aggregation
by: Hou, Zhichao, et al.
Published: (2023)
by: Hou, Zhichao, et al.
Published: (2023)
Separate Aggregation of Split Network for Personalized Federated Learning
by: Kang, Yunseok, et al.
Published: (2026)
by: Kang, Yunseok, et al.
Published: (2026)
HAGNN: Hybrid Aggregation for Heterogeneous Graph Neural Networks
by: Zhu, Guanghui, et al.
Published: (2023)
by: Zhu, Guanghui, et al.
Published: (2023)
Feature Shift Localization Network
by: Barrabés, Míriam, et al.
Published: (2025)
by: Barrabés, Míriam, et al.
Published: (2025)
Accurate generation of stochastic dynamics based on multi-model Generative Adversarial Networks
by: Lanzoni, Daniele, et al.
Published: (2023)
by: Lanzoni, Daniele, et al.
Published: (2023)
Improving Generalization of Deep Neural Networks by Optimum Shifting
by: Zhou, Yuyan, et al.
Published: (2024)
by: Zhou, Yuyan, et al.
Published: (2024)
Network Traffic Analysis with Process Mining: The UPSIDE Case Study
by: Vitale, Francesco, et al.
Published: (2025)
by: Vitale, Francesco, et al.
Published: (2025)
On the Lipschitz Continuity of Set Aggregation Functions and Neural Networks for Sets
by: Nikolentzos, Giannis, et al.
Published: (2025)
by: Nikolentzos, Giannis, et al.
Published: (2025)
Causal Estimation of Exposure Shifts with Neural Networks
by: Tec, Mauricio, et al.
Published: (2023)
by: Tec, Mauricio, et al.
Published: (2023)
ShiftAddNet: A Hardware-Inspired Deep Network
by: You, Haoran, et al.
Published: (2020)
by: You, Haoran, et al.
Published: (2020)
Not Eliminate but Aggregate: Post-Hoc Control over Mixture-of-Experts to Address Shortcut Shifts in Natural Language Understanding
by: Honda, Ukyo, et al.
Published: (2024)
by: Honda, Ukyo, et al.
Published: (2024)
Structure-Aware E(3)-Invariant Molecular Conformer Aggregation Networks
by: Nguyen, Duy M. H., et al.
Published: (2024)
by: Nguyen, Duy M. H., et al.
Published: (2024)
A Comparison of Methods for Neural Network Aggregation
by: Pomerat, John, et al.
Published: (2023)
by: Pomerat, John, et al.
Published: (2023)
Deep Neural Network Calibration by Reducing Classifier Shift with Stochastic Masking
by: Ni, Jiani, et al.
Published: (2025)
by: Ni, Jiani, et al.
Published: (2025)
An Axiomatic Approach to Loss Aggregation and an Adapted Aggregating Algorithm
by: Pacheco, Armando J. Cabrera, et al.
Published: (2024)
by: Pacheco, Armando J. Cabrera, et al.
Published: (2024)
HyperAggregation: Aggregating over Graph Edges with Hypernetworks
by: Lell, Nicolas, et al.
Published: (2024)
by: Lell, Nicolas, et al.
Published: (2024)
Shift Detection and Adaptation for Network Intrusion Detection
by: Mousavipour, Ehssan, et al.
Published: (2025)
by: Mousavipour, Ehssan, et al.
Published: (2025)
Identifying General Mechanism Shifts in Linear Causal Representations
by: Chen, Tianyu, et al.
Published: (2024)
by: Chen, Tianyu, et al.
Published: (2024)
Understanding Pooling in Graph Neural Networks
by: Grattarola, Daniele, et al.
Published: (2021)
by: Grattarola, Daniele, et al.
Published: (2021)
Partial Fusion of Neural Networks: Efficient Tradeoffs Between Ensembles and Weight Aggregation
by: Morelli, Fabian, et al.
Published: (2026)
by: Morelli, Fabian, et al.
Published: (2026)
LAYA: Layer-wise Attention Aggregation for Interpretable Depth-Aware Neural Networks
by: Vessio, Gennaro
Published: (2025)
by: Vessio, Gennaro
Published: (2025)
Exact Certification of Neural Networks and Partition Aggregation Ensembles against Label Poisoning
by: Mohgaonkar, Ajinkya, et al.
Published: (2026)
by: Mohgaonkar, Ajinkya, et al.
Published: (2026)
Fast and Effective GNN Training through Sequences of Random Path Graphs
by: Bonchi, Francesco, et al.
Published: (2023)
by: Bonchi, Francesco, et al.
Published: (2023)
Benchmarking Distribution Shift in Tabular Data with TableShift
by: Gardner, Josh, et al.
Published: (2023)
by: Gardner, Josh, et al.
Published: (2023)
Anytime PAC-Bayes for Constrained Density-Ratio Networks under Covariate Shift
by: Enabe, Paulo Akira F.
Published: (2026)
by: Enabe, Paulo Akira F.
Published: (2026)
Enhancing Model Fairness and Accuracy with Similarity Networks: A Methodological Approach
by: Maghool, Samira, et al.
Published: (2024)
by: Maghool, Samira, et al.
Published: (2024)
Extracting the Multiscale Causal Backbone of Brain Dynamics
by: D'Acunto, Gabriele, et al.
Published: (2023)
by: D'Acunto, Gabriele, et al.
Published: (2023)
Similar Items
-
The Hidden Cost of an Image: Quantifying the Energy Consumption of AI Image Generation
by: Bertazzini, Giulia, et al.
Published: (2025) -
DRAGON: A Large-Scale Dataset of Realistic Images Generated by Diffusion Models
by: Bertazzini, Giulia, et al.
Published: (2025) -
MARS: Sound Generation via Multi-Channel Autoregression on Spectrograms
by: Ristori, Eleonora, et al.
Published: (2025) -
Dealing with Uncertainty in Contextual Anomaly Detection
by: Bindini, Luca, et al.
Published: (2025) -
FedShift: Robust Federated Learning Aggregation Scheme in Resource Constrained Environment via Weight Shifting
by: Seo, Jungwon, et al.
Published: (2024)