Guardado en:
| Autores principales: | Ewen, Nicolas, Diaz-Rodriguez, Jairo, Ramsay, Kelly |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2602.06245 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Structured Output Regularization: a framework for few-shot transfer learning
por: Ewen, Nicolas, et al.
Publicado: (2025)
por: Ewen, Nicolas, et al.
Publicado: (2025)
Differentially Private Boxplots
por: Ramsay, Kelly, et al.
Publicado: (2024)
por: Ramsay, Kelly, et al.
Publicado: (2024)
Parallel Unlearning in Inherited Model Networks
por: Liu, Xiao, et al.
Publicado: (2024)
por: Liu, Xiao, et al.
Publicado: (2024)
Position: Ideas Should be the Center of Machine Learning Research
por: Diaz-Rodriguez, Jairo
Publicado: (2026)
por: Diaz-Rodriguez, Jairo
Publicado: (2026)
Improved subsample-and-aggregate via the private modified winsorized mean
por: Ramsay, Kelly, et al.
Publicado: (2025)
por: Ramsay, Kelly, et al.
Publicado: (2025)
Unsupervised Text Segmentation via Kernel Change-Point Detection on Sentence Embeddings
por: Jia, Mumin, et al.
Publicado: (2026)
por: Jia, Mumin, et al.
Publicado: (2026)
Summaries as Centroids for Interpretable and Scalable Text Clustering
por: Diaz-Rodriguez, Jairo
Publicado: (2025)
por: Diaz-Rodriguez, Jairo
Publicado: (2025)
Optimizing Performance of Feedforward and Convolutional Neural Networks through Dynamic Activation Functions
por: Rane, Chinmay, et al.
Publicado: (2023)
por: Rane, Chinmay, et al.
Publicado: (2023)
Differentially private projection-depth-based medians
por: Ramsay, Kelly, et al.
Publicado: (2023)
por: Ramsay, Kelly, et al.
Publicado: (2023)
Differentially private scale testing via rank transformations and percentile modifications
por: Levine, Joshua, et al.
Publicado: (2025)
por: Levine, Joshua, et al.
Publicado: (2025)
Training Feedforward Neural Networks with Bayesian Hyper-Heuristics
por: Schreuder, Arné, et al.
Publicado: (2023)
por: Schreuder, Arné, et al.
Publicado: (2023)
Approximation Capabilities of Feedforward Neural Networks with GELU Activations
por: Yakovlev, Konstantin, et al.
Publicado: (2025)
por: Yakovlev, Konstantin, et al.
Publicado: (2025)
Beyond Student: An Asymmetric Network for Neural Network Inheritance
por: Zhou, Yiyun, et al.
Publicado: (2026)
por: Zhou, Yiyun, et al.
Publicado: (2026)
Attention Is Not All You Need: The Importance of Feedforward Networks in Transformer Models
por: Gerber, Isaac
Publicado: (2025)
por: Gerber, Isaac
Publicado: (2025)
Compression Repair for Feedforward Neural Networks Based on Model Equivalence Evaluation
por: Mo, Zihao, et al.
Publicado: (2024)
por: Mo, Zihao, et al.
Publicado: (2024)
Consistent Kernel Change-Point Detection under m-Dependence for Text Segmentation
por: Diaz-Rodriguez, Jairo, et al.
Publicado: (2025)
por: Diaz-Rodriguez, Jairo, et al.
Publicado: (2025)
Deriving Equivalent Symbol-Based Decision Models from Feedforward Neural Networks
por: Seidel, Sebastian, et al.
Publicado: (2025)
por: Seidel, Sebastian, et al.
Publicado: (2025)
Symbolic Feedforward Networks for Probabilistic Finite Automata: Exact Simulation and Learnability
por: Dhayalkar, Sahil Rajesh
Publicado: (2025)
por: Dhayalkar, Sahil Rajesh
Publicado: (2025)
Symbolic Branch Networks: Tree-Inherited Neural Models for Interpretable Multiclass Classification
por: Rodríguez-Salas, Dalia
Publicado: (2025)
por: Rodríguez-Salas, Dalia
Publicado: (2025)
A Statistical-Modelling Approach to Feedforward Neural Network Model Selection
por: McInerney, Andrew, et al.
Publicado: (2022)
por: McInerney, Andrew, et al.
Publicado: (2022)
Dynamics of Spontaneous Topic Changes in Next Token Prediction with Self-Attention
por: Jia, Mumin, et al.
Publicado: (2025)
por: Jia, Mumin, et al.
Publicado: (2025)
When Do Transformers Outperform Feedforward and Recurrent Networks? A Statistical Perspective
por: Mousavi-Hosseini, Alireza, et al.
Publicado: (2025)
por: Mousavi-Hosseini, Alireza, et al.
Publicado: (2025)
Activation Functions for "A Feedforward Unitary Equivariant Neural Network"
por: Ma, Pui-Wai
Publicado: (2024)
por: Ma, Pui-Wai
Publicado: (2024)
The Complexity of Verifying Feedforward Neural Networks in Quantised Settings
por: Alsmann, Eric, et al.
Publicado: (2026)
por: Alsmann, Eric, et al.
Publicado: (2026)
Feedforward Controllers from Learned Dynamic Local Model Networks with Application to Excavator Assistance Functions
por: Greiser, Leon, et al.
Publicado: (2024)
por: Greiser, Leon, et al.
Publicado: (2024)
Adaptive Feedforward Gradient Estimation in Neural ODEs
por: Dabounou, Jaouad
Publicado: (2024)
por: Dabounou, Jaouad
Publicado: (2024)
Nested Inheritance Dynamics
por: Moraffah, Bahman
Publicado: (2024)
por: Moraffah, Bahman
Publicado: (2024)
A Constructive Framework for Nondeterministic Automata via Time-Shared, Depth-Unrolled Feedforward Networks
por: Dhayalkar, Sahil Rajesh
Publicado: (2025)
por: Dhayalkar, Sahil Rajesh
Publicado: (2025)
On Catastrophic Inheritance of Large Foundation Models
por: Chen, Hao, et al.
Publicado: (2024)
por: Chen, Hao, et al.
Publicado: (2024)
Controlled Langevin Dynamics for Sampling of Feedforward Neural Networks Trained with Minibatches
por: Zambon, Alessandro, et al.
Publicado: (2026)
por: Zambon, Alessandro, et al.
Publicado: (2026)
Dead Weights, Live Signals: Feedforward Graphs of Frozen Language Models
por: Armstrong, Marcus, et al.
Publicado: (2026)
por: Armstrong, Marcus, et al.
Publicado: (2026)
Network Calculus with Flow Prolongation -- A Feedforward FIFO Analysis enabled by ML
por: Geyer, Fabien, et al.
Publicado: (2022)
por: Geyer, Fabien, et al.
Publicado: (2022)
Probabilistic Classification and Uncertainty Quantification of Sahara Desert Climate Using Feedforward Neural Networks
por: Tivenan, Stephen, et al.
Publicado: (2026)
por: Tivenan, Stephen, et al.
Publicado: (2026)
Towards Arbitrary QUBO Optimization: Analysis of Classical and Quantum-Activated Feedforward Neural Networks
por: Lai, Chia-Tso, et al.
Publicado: (2024)
por: Lai, Chia-Tso, et al.
Publicado: (2024)
Hierarchical Uncertainty Exploration via Feedforward Posterior Trees
por: Nehme, Elias, et al.
Publicado: (2024)
por: Nehme, Elias, et al.
Publicado: (2024)
Differentially private multivariate medians
por: Ramsay, Kelly, et al.
Publicado: (2022)
por: Ramsay, Kelly, et al.
Publicado: (2022)
Diffusion Operator Geometry of Feedforward Representations
por: Reddy, Kanishka
Publicado: (2026)
por: Reddy, Kanishka
Publicado: (2026)
Lossless Compression via Chained Lightweight Neural Predictors with Information Inheritance
por: Kim, Yuriy, et al.
Publicado: (2026)
por: Kim, Yuriy, et al.
Publicado: (2026)
Enhancing Small Dataset Classification Using Projected Quantum Kernels with Convolutional Neural Networks
por: Alagiyawanna, A. M. A. S. D., et al.
Publicado: (2026)
por: Alagiyawanna, A. M. A. S. D., et al.
Publicado: (2026)
3DTV: A Feedforward Interpolation Network for Real-Time View Synthesis
por: Schulz, Stefan, et al.
Publicado: (2026)
por: Schulz, Stefan, et al.
Publicado: (2026)
Ejemplares similares
-
Structured Output Regularization: a framework for few-shot transfer learning
por: Ewen, Nicolas, et al.
Publicado: (2025) -
Differentially Private Boxplots
por: Ramsay, Kelly, et al.
Publicado: (2024) -
Parallel Unlearning in Inherited Model Networks
por: Liu, Xiao, et al.
Publicado: (2024) -
Position: Ideas Should be the Center of Machine Learning Research
por: Diaz-Rodriguez, Jairo
Publicado: (2026) -
Improved subsample-and-aggregate via the private modified winsorized mean
por: Ramsay, Kelly, et al.
Publicado: (2025)