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Found 34 papers, 3 papers with code
Self-Contextualized Attention for Abusive Language Identification
The use of attention mechanisms in deep learning approaches has become popular in natural language processing due to its outstanding performance.
Unified Physical-Digital Attack Detection Challenge
Based on this dataset, we organized a Unified Physical-Digital Face Attack Detection Challenge to boost the research in Unified Attack Detections.
Analysis of Systems' Performance in Natural Language Processing Competitions
Collaborative competitions have gained popularity in the scientific and technological fields.
Academic competitions
Academic challenges comprise effective means for (i) advancing the state of the art, (ii) putting in the spotlight of a scientific community specific topics and problems, as well as (iii) closing the gap for under represented communities in terms of accessing and participating in the shaping of research fields.
TurboGP: A flexible and advanced python based GP library
We introduce TurboGP, a Genetic Programming (GP) library fully written in Python and specifically designed for machine learning tasks.
Continuous Cartesian Genetic Programming based representation for Multi-Objective Neural Architecture Search
Our approach combines real-based and block-chained CNNs representations based on CGP for optimization in the continuous domain using multi-objective evolutionary algorithms (MOEAs).
Comparison of classifiers in challenge scheme
For the challenges settings, it is vital to establish the scientific question, the dataset (with adequate quality, quantity, diversity, and complexity), performance metrics, as well as a way to authenticate the participants' results (Gold Standard).
Surveillance Face Presentation Attack Detection Challenge
Based on this dataset and protocol-$3$ for evaluating the robustness of the algorithm under quality changes, we organized a face presentation attack detection challenge in surveillance scenarios.
Wild Face Anti-Spoofing Challenge 2023: Benchmark and Results
Leveraging the WFAS dataset and Protocol 1 (Known-Type), we host the Wild Face Anti-Spoofing Challenge at the CVPR2023 workshop.
Multi-Branch Deep Radial Basis Function Networks for Facial Emotion Recognition
Initial efforts on ER relied on handcrafted features that were used to characterize facial images and then feed to standard predictive models.
Predicting students' performance in online courses using multiple data sources
Data-driven decision making is serving and transforming education.
3D High-Fidelity Mask Face Presentation Attack Detection Challenge
The threat of 3D masks to face recognition systems is increasingly serious and has been widely concerned by researchers.
ChaLearn Looking at People: Inpainting and Denoising challenges
Dealing with incomplete information is a well studied problem in the context of machine learning and computational intelligence.
Automated Machine Learning -- a brief review at the end of the early years
Automated machine learning (AutoML) is the sub-field of machine learning that aims at automating, to some extend, all stages of the design of a machine learning system.
Cross-ethnicity Face Anti-spoofing Recognition Challenge: A Review
Although ethnic bias has been verified to severely affect the performance of face recognition systems, it still remains an open research problem in face anti-spoofing.
CASIA-SURF: A Large-scale Multi-modal Benchmark for Face Anti-spoofing
To facilitate face anti-spoofing research, we introduce a large-scale multi-modal dataset, namely CASIA-SURF, which is the largest publicly available dataset for face anti-spoofing in terms of both subjects and modalities.
Towards AutoML in the presence of Drift: first results
We extendAuto-Sklearn with sound and intuitive mechanisms that allow it to cope with this sort ofproblems.
Meta-learning of textual representations
Recent progress in AutoML has lead to state-of-the-art methods (e. g., AutoSKLearn) that can be readily used by non-experts to approach any supervised learning problem.
Analysis of the AutoML Challenge Series 2015–2018
The solutions of the winners are systematically benchmarked over all datasets of all rounds and compared with canonical machine learning algorithms available in scikit-learn.
Ranked #1 on
AutoML
on Chalearn-AutoML-1
AutoML @ NeurIPS 2018 challenge: Design and Results
We organized a competition on Autonomous Lifelong Machine Learning with Drift that was part of the competition program of NeurIPS 2018.
Early Text Classification Using Multi-Resolution Concept Representations
The intensive use of e-communications in everyday life has given rise to new threats and risks.
A visual approach for age and gender identification on Twitter
The goal of Author Profiling (AP) is to identify demographic aspects (e. g., age, gender) from a given set of authors by analyzing their written texts.
First Impressions: A Survey on Vision-Based Apparent Personality Trait Analysis
However, recently there has been an increasing interest from the computer vision community in analyzing personality from visual data.
Towards Deep Representation Learning with Genetic Programming
Genetic Programming (GP) is an evolutionary algorithm commonly used for machine learning tasks.
Explaining First Impressions: Modeling, Recognizing, and Explaining Apparent Personality from Videos
Explainability and interpretability are two critical aspects of decision support systems.
Fractal dimension analysis for automatic morphological galaxy classification
In this report we present experimental results using \emph{Haussdorf-Besicovich} fractal dimension for performing morphological galaxy classification.
ChaLearn Looking at People: A Review of Events and Resources
This paper reviews associated events, and introduces the ChaLearn LAP platform where public resources (including code, data and preprints of papers) related to the organized events are available.
ChaLearn Looking at People and Faces of the World: Face Analysis Workshop and Challenge 2016
A custom-build application was used to collect and label data about the apparent age of people (as opposed to the real age).
Ranked #2 on
Gender Prediction
on FotW Gender
Early text classification: a Naive solution
A document is processed as a sequence of terms, and the goal is to devise a method that can make predictions as fast as possible.
Term-Weighting Learning via Genetic Programming for Text Classification
We propose in this article a genetic program that aims at learning effective TWSs that can improve the performance of current schemes in text classification.
Principal motion components for gesture recognition using a single-example
In the considered scenario a single training-video is available for each gesture to be recognized, which limits the application of traditional techniques (e. g., HMMs).
An estimation of distribution algorithm with adaptive Gibbs sampling for unconstrained global optimization
The main framework of the proposed method is an estimation of distribution algorithm, in which an adaptive Gibbs sampling is used to generate new promising solutions and, in combination with a local search strategy, it improves the individual solutions produced in each iteration.
