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06/07/2023
Invariant Causal Set Covering Machines
Rule-based models, such as decision trees, appeal to practitioners due t...
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02/17/2023
PAC-Bayesian Generalization Bounds for Adversarial Generative Models
We extend PAC-Bayesian theory to generative models and develop generaliz...
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09/07/2022
A Greedy Algorithm for Building Compact Binary Activated Neural Networks
We study binary activated neural networks in the context of regression t...
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10/28/2021
Learning Aggregations of Binary Activated Neural Networks with Probabilities over Representations
Considering a probability distribution over parameters is known as an ef...
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06/23/2021
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound
We investigate a stochastic counterpart of majority votes over finite en...
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04/28/2021
Self-Bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound
In the PAC-Bayesian literature, the C-Bound refers to an insightful rela...
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02/17/2021
A General Framework for the Derandomization of PAC-Bayesian Bounds
PAC-Bayesian bounds are known to be tight and informative when studying ...
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10/24/2020
Implicit Variational Inference: the Parameter and the Predictor Space
Having access to accurate confidence levels along with the predictions a...
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12/06/2019
Improved PAC-Bayesian Bounds for Linear Regression
In this paper, we improve the PAC-Bayesian error bound for linear regres...
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10/10/2019
PAC-Bayesian Contrastive Unsupervised Representation Learning
Contrastive unsupervised representation learning (CURL) is the state-of-...
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06/14/2019
Learning Landmark-Based Ensembles with Random Fourier Features and Gradient Boosting
We propose a Gradient Boosting algorithm for learning an ensemble of ker...
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05/24/2019
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks
We present a comprehensive study of multilayer neural networks with bina...
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10/30/2018
Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior
We revisit Rahimi and Recht (2007)'s kernel random Fourier features (RFF...
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08/17/2018
Multiview Boosting by Controlling the Diversity and the Accuracy of View-specific Voters
In this paper we propose a boosting based multiview learning algorithm, ...
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07/17/2017
PAC-Bayes and Domain Adaptation
We provide two main contributions in PAC-Bayesian theory for domain adap...
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06/23/2016
PAC-Bayesian Analysis for a two-step Hierarchical Multiview Learning Approach
We study a two-level multiview learning with more than two views under t...
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05/27/2016
PAC-Bayesian Theory Meets Bayesian Inference
We exhibit a strong link between frequentist PAC-Bayesian risk bounds an...
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06/15/2015
A New PAC-Bayesian Perspective on Domain Adaptation
We study the issue of PAC-Bayesian domain adaptation: We want to learn, ...
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05/28/2015
Domain-Adversarial Training of Neural Networks
We introduce a new representation learning approach for domain adaptatio...
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03/28/2015
Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm
We propose an extensive analysis of the behavior of majority votes in bi...
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03/24/2015
PAC-Bayesian Theorems for Domain Adaptation with Specialization to Linear Classifiers
In this paper, we provide two main contributions in PAC-Bayesian theory ...
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01/13/2015
An Improvement to the Domain Adaptation Bound in a PAC-Bayesian context
This paper provides a theoretical analysis of domain adaptation based on...
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12/15/2014
Domain-Adversarial Neural Networks
We introduce a new representation learning algorithm suited to the conte...
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12/11/2012