Cover Image

Novel Kernel Models and Exact Representor Theory for Neural Networks Beyond the Over-Parameterized Regime

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Shilton, Alistair, Gupta, Sunil, Rana, Santu, Venkatesh, Svetha
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Enhanced Bayesian Optimization via Preferential Modeling of Abstract Properties
by: A V, Arun Kumar, et al.
Published: (2024)

Bayesian Optimistic Optimisation with Exponentially Decaying Regret
by: Tran-The, Hung, et al.
Published: (2021)

Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization
by: Tran-The, Hung, et al.
Published: (2019)

Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization
by: Tran-The, Hung, et al.
Published: (2022)

Score-based Integrated Gradient for Root Cause Explanations of Outliers
by: Nguyen, Phuoc, et al.
Published: (2026)

Generating Realistic Tabular Data with Large Language Models
by: Nguyen, Dang, et al.
Published: (2024)

Adaptive Acquisition Selection for Bayesian Optimization with Large Language Models
by: Ngo, Giang, et al.
Published: (2026)

Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces
by: Tran-The, Hung, et al.
Published: (2020)

Large Language Models for Imbalanced Classification: Diversity makes the difference
by: Nguyen, Dang, et al.
Published: (2025)

Efficient Symmetry-Aware Materials Generation via Hierarchical Generative Flow Networks
by: Nguyen, Tri Minh, et al.
Published: (2024)

Federated Domain Generalization with Latent Space Inversion
by: Palakkadavath, Ragja, et al.
Published: (2025)

PINN-BO: A Black-box Optimization Algorithm using Physics-Informed Neural Networks
by: Phan-Trong, Dat, et al.
Published: (2024)

SPaCe: Unlocking Sample-Efficient Large Language Models Training With Self-Pace Curriculum Learning
by: Do, Dai, et al.
Published: (2025)

Variable-Agnostic Causal Exploration for Reinforcement Learning
by: Nguyen, Minh Hoang, et al.
Published: (2024)

Leveraging Human Feedback for Semantically-Relevant Skill Discovery
by: Hussonnois, Maxence, et al.
Published: (2026)

TRUST: Test-time Resource Utilization for Superior Trustworthiness
by: Harikumar, Haripriya, et al.
Published: (2025)

Dynamic Policy Fusion for User Alignment Without Re-Interaction
by: Palattuparambil, Ajsal Shereef, et al.
Published: (2024)

MAGIK: Mapping to Analogous Goals via Imagination-enabled Knowledge Transfer
by: Palattuparambil, Ajsal Shereef, et al.
Published: (2025)

The Malignant Tail: Spectral Segregation of Label Noise in Over-Parameterized Networks
by: Wang, Zice
Published: (2026)

Scalable Neural Network Kernels
by: Sehanobish, Arijit, et al.
Published: (2023)

Strategic Over-Parameterization for Generalizable Low-Rank Adaptation
by: Gao, Jing, et al.
Published: (2026)

Composite Concept Extraction through Backdooring
by: Ghosh, Banibrata, et al.
Published: (2024)

Train Faster, Perform Better: Modular Adaptive Training in Over-Parameterized Models
by: Shi, Yubin, et al.
Published: (2024)

Knoop: Practical Enhancement of Knockoff with Over-Parameterization for Variable Selection
by: Zhang, Xiaochen, et al.
Published: (2025)

Provable Acceleration of Nesterov's Accelerated Gradient Method over Heavy Ball Method in Training Over-Parameterized Neural Networks
by: Liu, Xin, et al.
Published: (2022)

A Unified Kernel for Neural Network Learning
by: Zhang, Shao-Qun, et al.
Published: (2024)

Over-squashing in Spatiotemporal Graph Neural Networks
by: Marisca, Ivan, et al.
Published: (2025)

Rank Collapse Causes Over-Smoothing and Over-Correlation in Graph Neural Networks
by: Roth, Andreas, et al.
Published: (2023)

A Multi-Graph Convolutional Neural Network Model for Short-Term Prediction of Turning Movements at Signalized Intersections
by: Palit, Jewel Rana, et al.
Published: (2024)

MUSO: Achieving Exact Machine Unlearning in Over-Parameterized Regimes
by: Yang, Ruikai, et al.
Published: (2024)

Learning to Execute Graph Algorithms Exactly with Graph Neural Networks
by: Qharabagh, Muhammad Fetrat, et al.
Published: (2026)

Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning
by: Le, Hung, et al.
Published: (2024)

Understanding the Countably Infinite: Neural Network Models of the Successor Function and its Acquisition
by: Gupta, Vima, et al.
Published: (2023)

Beyond the Known: Decision Making with Counterfactual Reasoning Decision Transformer
by: Nguyen, Minh Hoang, et al.
Published: (2025)

Amortized Linear-time Exact Shapley Value for Product-Kernel Methods
by: Mohammadi, Majid, et al.
Published: (2025)

Continual Fine-Tuning of Large Language Models via Program Memory
by: Le, Hung, et al.
Published: (2026)

Exact Computation of Any-Order Shapley Interactions for Graph Neural Networks
by: Muschalik, Maximilian, et al.
Published: (2025)

Unified Kernel-Segregated Transpose Convolution Operation
by: Tida, Vijay Srinivas, et al.
Published: (2025)

Learning Parameterized Skills from Demonstrations
by: Gupta, Vedant, et al.
Published: (2025)

Stock Market Price Prediction using Neural Prophet with Deep Neural Network
by: Chhibber, Navin, et al.
Published: (2026)