research
∙
12/07/2021
Multinational Address Parsing: A Zero-Shot Evaluation
Address parsing consists of identifying the segments that make up an add...
share
research
∙
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...
research
∙
07/26/2021
How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review
Context: Machine Learning (ML) has been at the heart of many innovations...
research
∙
10/24/2020
Implicit Variational Inference: the Parameter and the Predictor Space
Having access to accurate confidence levels along with the predictions a...
research
∙
06/29/2020
Leveraging Subword Embeddings for Multinational Address Parsing
Address parsing consists of identifying the segments that make up an add...
research
∙
04/24/2020
General Cops and Robbers Games with randomness
Cops and Robbers games have been studied for the last few decades in com...
research
∙
01/29/2020
The Indian Chefs Process
This paper introduces the Indian Chefs Process (ICP), a Bayesian nonpara...
research
∙
12/21/2019
Unsupervised Domain Adversarial Self-Calibration for Electromyographic-based Gesture Recognition
Surface electromyography (sEMG) provides an intuitive and non-invasive i...
research
∙
12/16/2019
Virtual Reality to Study the Gap Between Offline and Real-Time EMG-based Gesture Recognition
Within sEMG-based gesture recognition, a chasm exists in the literature ...
research
∙
11/30/2019
Interpreting Deep Learning Features for Myoelectric Control: A Comparison with Handcrafted Features
The research in myoelectric control systems primarily focuses on extract...
research
∙
05/28/2019
Adaptive Deep Kernel Learning
Deep kernel learning provides an elegant and principled framework for co...
research
∙
05/24/2019
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks
We present a comprehensive study of multilayer neural networks with bina...
research
∙
01/10/2018
Deep Learning for Electromyographic Hand Gesture Signal Classification by Leveraging Transfer Learning
In recent years, the use of deep learning algorithms has become increasi...
research
∙
10/11/2017
Maximum Margin Interval Trees
Learning a regression function using censored or interval-valued output ...
research
∙
07/17/2017
PAC-Bayes and Domain Adaptation
We provide two main contributions in PAC-Bayesian theory for domain adap...
research
∙
06/15/2015
A New PAC-Bayesian Perspective on Domain Adaptation
We study the issue of PAC-Bayesian domain adaptation: We want to learn, ...
research
∙
05/28/2015
Domain-Adversarial Training of Neural Networks
We introduce a new representation learning approach for domain adaptatio...
research
∙
05/22/2015
Greedy Biomarker Discovery in the Genome with Applications to Antimicrobial Resistance
The Set Covering Machine (SCM) is a greedy learning algorithm that produ...
research
∙
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...
research
∙
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 ...
research
∙
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...
research
∙
01/13/2015
On Generalizing the C-Bound to the Multiclass and Multi-label Settings
The C-bound, introduced in Lacasse et al., gives a tight upper bound on ...
research
∙
12/15/2014
Domain-Adversarial Neural Networks
We introduce a new representation learning algorithm suited to the conte...
research
∙
12/02/2014
Learning interpretable models of phenotypes from whole genome sequences with the Set Covering Machine
The increased affordability of whole genome sequencing has motivated its...
research
∙
08/06/2014
On the Generalization of the C-Bound to Structured Output Ensemble Methods
This paper generalizes an important result from the PAC-Bayesian literat...
research
∙
02/04/2014
Sequential Model-Based Ensemble Optimization
One of the most tedious tasks in the application of machine learning is ...
research
∙
12/11/2012
PAC-Bayesian Learning and Domain Adaptation
In machine learning, Domain Adaptation (DA) arises when the distribution...
research
∙
07/31/2012
Learning a peptide-protein binding affinity predictor with kernel ridge regression
We propose a specialized string kernel for small bio-molecules, peptides...
research
∙
10/31/2011
PAC-Bayesian Inequalities for Martingales
We present a set of high-probability inequalities that control the conce...
research
∙
05/23/2011
PAC-Bayesian Analysis of the Exploration-Exploitation Trade-off
We develop a coherent framework for integrative simultaneous analysis of...
research
∙
05/12/2011
