Search Results for author:
Found 8 papers, 4 papers with code
Novel Applications for VAE-based Anomaly Detection Systems
Research also indicates different biases affect deep learning models, leading to social issues such as misrepresentation.
Bayes Point Rule Set Learning
The produced DNF is a set of conjunctive rules, each corresponding to the most specific rule consistent with a part of positive and all negative examples.
MKLpy: a python-based framework for Multiple Kernel Learning
Multiple Kernel Learning is a recent and powerful paradigm to learn the kernel function from data.
DecOp: A Multilingual and Multi-domain Corpus For Detecting Deception In Typed Text
For filling this gap, in this paper we introduce DecOp (Deceptive Opinions), a new language resource developed for automatic deception detection in cross-domain and cross-language scenarios.
Conditioned Variational Autoencoder for top-N item recommendation
In this paper, we propose a Conditioned Variational Autoencoder (C-VAE) for constrained top-N item recommendation where the recommended items must satisfy a given condition.
Interpretable preference learning: a game theoretic framework for large margin on-line feature and rule learning
A large body of research is currently investigating on the connection between machine learning and game theory.
Boolean kernels for collaborative filtering in top-N item recommendation
Recent analysis show that collaborative filtering (CF) datasets have peculiar characteristics such as high sparsity and a long tailed distribution of the ratings.
Exploiting sparsity to build efficient kernel based collaborative filtering for top-N item recommendation
The increasing availability of implicit feedback datasets has raised the interest in developing effective collaborative filtering techniques able to deal asymmetrically with unambiguous positive feedback and ambiguous negative feedback.
