conftrace_

generalization error

285 papers

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Also known as

GE

Co-occurring keywords

generalization bound (652) stochastic gradient descent (1091) neural network (6616) learning theory (519) double descent (52) sample complexity (1169) active learning (1301) gradient descent (1144) support vector machine (978) neural network optimization (1293)

Papers

On the Generalization Power of Overfitted Two-Layer Neural Tangent Kernel Models ICML 2021
On the Inherent Regularization Effects of Noise Injection During Training ICML 2021
How rotational invariance of common kernels prevents generalization in high dimensions ICML 2021
MMIM: An Interpretable Regularization Method for Neural Networks (Student Abstract) AAAI 2021
Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection NIPS 2021
How Tight Can PAC-Bayes be in the Small Data Regime? NIPS 2021
On the Algorithmic Stability of Adversarial Training NIPS 2021
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Sparse Neural Networks NIPS 2021
Model, sample, and epoch-wise descents: exact solution of gradient flow in the random feature model NIPS 2021
The curious case of adversarially robust models: More data can help, double descend, or hurt generalization UAI 2021
Statistical mechanical analysis of neural network pruning UAI 2021
Good Classifiers are Abundant in the Interpolating Regime AISTATS 2021
Classification vs regression in overparameterized regimes: Does the loss function matter? JMLR 2021
Training Data Subset Selection for Regression with Controlled Generalization Error ICML 2021
How Does Loss Function Affect Generalization Performance of Deep Learning? Application to Human Age Estimation ICML 2021
An Exact Characterization of the Generalization Error for the Gibbs Algorithm NIPS 2021
Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms NIPS 2021
Never Go Full Batch (in Stochastic Convex Optimization) NIPS 2021
Loss function based second-order Jensen inequality and its application to particle variational inference NIPS 2021
On Linear Stability of SGD and Input-Smoothness of Neural Networks NIPS 2021
On the Role of Optimization in Double Descent: A Least Squares Study NIPS 2021
Generalization Bounds for Graph Embedding Using Negative Sampling: Linear vs Hyperbolic NIPS 2021
Generalization Error Rates in Kernel Regression: The Crossover from the Noiseless to Noisy Regime NIPS 2021
Towards Understanding Why Lookahead Generalizes Better Than SGD and Beyond NIPS 2021
Learning curves of generic features maps for realistic datasets with a teacher-student model NIPS 2021