Generalization Bounds

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Greatest papers with code

Bridging Theory and Algorithm for Domain Adaptation

thuml/Transfer-Learning-Library 11 Apr 2019

We introduce Margin Disparity Discrepancy, a novel measurement with rigorous generalization bounds, tailored to the distribution comparison with the asymmetric margin loss, and to the minimax optimization for easier training.

Domain Adaptation Generalization Bounds

Debiased Contrastive Learning

chingyaoc/DCL NeurIPS 2020

A prominent technique for self-supervised representation learning has been to contrast semantically similar and dissimilar pairs of samples.

Generalization Bounds Representation Learning

Estimating individual treatment effect: generalization bounds and algorithms

clinicalml/cfrnet ICML 2017

We give a novel, simple and intuitive generalization-error bound showing that the expected ITE estimation error of a representation is bounded by a sum of the standard generalization-error of that representation and the distance between the treated and control distributions induced by the representation.

Causal Inference Generalization Bounds

Learning Robust State Abstractions for Hidden-Parameter Block MDPs

facebookresearch/mtrl ICLR 2021

Further, we provide transfer and generalization bounds based on task and state similarity, along with sample complexity bounds that depend on the aggregate number of samples across tasks, rather than the number of tasks, a significant improvement over prior work that use the same environment assumptions.

Generalization Bounds Meta Reinforcement Learning

Optimal Auctions through Deep Learning

saisrivatsan/deep-opt-auctions 12 Jun 2017

Designing an incentive compatible auction that maximizes expected revenue is an intricate task.

Generalization Bounds

GraphMix: Improved Training of GNNs for Semi-Supervised Learning

vikasverma1077/GraphMix 25 Sep 2019

We present GraphMix, a regularization method for Graph Neural Network based semi-supervised object classification, whereby we propose to train a fully-connected network jointly with the graph neural network via parameter sharing and interpolation-based regularization.

Generalization Bounds Node Classification +1

Sorting out Lipschitz function approximation

cemanil/LNets 13 Nov 2018

We identify a necessary property for such an architecture: each of the layers must preserve the gradient norm during backpropagation.

Generalization Bounds

Improving Generalization by Controlling Label-Noise Information in Neural Network Weights

hrayrhar/limit-label-memorization ICML 2020

In the presence of noisy or incorrect labels, neural networks have the undesirable tendency to memorize information about the noise.

Data Augmentation Generalization Bounds +1

Towards a Learning Theory of Cause-Effect Inference

lopezpaz/causation_learning_theory 9 Feb 2015

We pose causal inference as the problem of learning to classify probability distributions.

Causal Inference Generalization Bounds