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Generalization Bounds
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이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Algorithmic Stability of Stochastic Gradient Descent with Momentum under Heavy-Tailed Noise
From Low Intrinsic Dimensionality to Non-Vacuous Generalization Bounds in Deep Multi-Task Learning
Towards the Generalization of Multi-view Learning: An Information-theoretical Analysis
Towards Sharper Information-theoretic Generalization Bounds for Meta-Learning
Generalization Performance of Hypergraph Neural Networks
Stability and Generalization of Quantum Neural Networks
Regularized Proportional Fairness Mechanism for Resource Allocation Without Money
Understanding Difficult-to-learn Examples in Contrastive Learning: A Theoretical Framework for Spectral Contrastive Learning
Explainable Neural Networks with Guarantees: A Sparse Estimation Approach
Data-Dependent Generalization Bounds for Parameterized Quantum Models Under Noise
Generalization Analysis for Deep Contrastive Representation Learning
The Complexity Dynamics of Grokking
Deep Distributed Optimization for Large-Scale Quadratic Programming
Representation and Regression Problems in Neural Networks: Relaxation, Generalization, and Numerics
On Generalization Bounds for Neural Networks with Low Rank Layers
Smart Predict-then-Optimize Method with Dependent Data: Risk Bounds and Calibration of Autoregression
Multi-View Majority Vote Learning Algorithms: Direct Minimization of PAC-Bayesian Bounds
Generalization, Expressivity, and Universality of Graph Neural Networks on Attributed Graphs
A Convex Relaxation Approach to Generalization Analysis for Parallel Positively Homogeneous Networks
Generalization Bounds via Conditional $f$-Information
Robust Model Evaluation over Large-scale Federated Networks
On the Geometry of Regularization in Adversarial Training: High-Dimensional Asymptotics and Generalization Bounds
On Cold Posteriors of Probabilistic Neural Networks: Understanding the Cold Posterior Effect and A New Way to Learn Cold Posteriors with Tight Generalization Guarantees
Sample Compression Hypernetworks: From Generalization Bounds to Meta-Learning
On Rank-Dependent Generalisation Error Bounds for Transformers
Towards Sharper Risk Bounds for Minimax Problems
Online-to-PAC generalization bounds under graph-mixing dependencies
Understanding Adversarially Robust Generalization via Weight-Curvature Index
Generalization Bounds and Model Complexity for Kolmogorov-Arnold Networks
Theoretical Insights into Fine-Tuning Attention Mechanism: Generalization and Optimization
Large Language Models as Markov Chains
Equivariant score-based generative models provably learn distributions with symmetries efficiently
Which Algorithms Have Tight Generalization Bounds?
Sample Compression Unleashed: New Generalization Bounds for Real Valued Losses
Learning to Classify Quantum Phases of Matter with a Few Measurements
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