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07/28/2023
Is One Epoch All You Need For Multi-Fidelity Hyperparameter Optimization?
Hyperparameter optimization (HPO) is crucial for fine-tuning machine lea...
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02/16/2023
Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification
We introduce Meta-Album, an image classification meta-dataset designed t...
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08/31/2022
NeurIPS'22 Cross-Domain MetaDL competition: Design and baseline results
We present the design and baseline results for a new challenge in the Ch...
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08/04/2022
Meta-learning from Learning Curves Challenge: Lessons learned from the First Round and Design of the Second Round
Meta-learning from learning curves is an important yet often neglected r...
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07/21/2022
Reinforcement learning for Energies of the future and carbon neutrality: a Challenge Design
Current rapid changes in climate increase the urgency to change energy p...
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07/01/2022
Asynchronous Distributed Bayesian Optimization at HPC Scale
Bayesian optimization (BO) is a widely used approach for computationally...
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06/15/2022
Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification
Although deep neural networks are capable of achieving performance super...
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04/06/2022
Bridging the Gap of AutoGraph between Academia and Industry: Analysing AutoGraph Challenge at KDD Cup 2020
Graph structured data is ubiquitous in daily life and scientific areas a...
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03/07/2022
Comparison of Spatio-Temporal Models for Human Motion and Pose Forecasting in Face-to-Face Interaction Scenarios
Human behavior forecasting during human-human interactions is of utmost ...
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03/04/2022
Didn't see that coming: a survey on non-verbal social human behavior forecasting
Non-verbal social human behavior forecasting has increasingly attracted ...
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02/12/2022
Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning
Questions in causality, control, and reinforcement learning go beyond th...
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02/04/2022
LTU Attacker for Membership Inference
We address the problem of defending predictive models, such as machine l...
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02/01/2022
Advances in MetaDL: AAAI 2021 challenge and workshop
To stimulate advances in metalearning using deep learning techniques (Me...
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01/17/2022
OmniPrint: A Configurable Printed Character Synthesizer
We introduce OmniPrint, a synthetic data generator of isolated printed c...
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10/12/2021
Codabench: Flexible, Easy-to-Use and Reproducible Benchmarking for Everyone
Obtaining standardized crowdsourced benchmark of computational methods i...
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07/28/2021
AutoML Meets Time Series Regression Design and Analysis of the AutoSeries Challenge
Analyzing better time series with limited human effort is of interest to...
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06/24/2021
ChaLearn Looking at People: Inpainting and Denoising challenges
Dealing with incomplete information is a well studied problem in the con...
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05/03/2021
The Tracking Machine Learning challenge : Throughput phase
This paper reports on the second "Throughput" phase of the Tracking Mach...
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04/20/2021
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020
This paper presents the results and insights from the black-box optimiza...
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12/14/2020
NeurIPS 2020 Competition: Predicting Generalization in Deep Learning
Understanding generalization in deep learning is arguably one of the mos...
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10/30/2020
AgEBO-Tabular: Joint Neural Architecture and Hyperparameter Search with Autotuned Data-Parallel Training for Tabular Data
Developing high-performing predictive models for large tabular data sets...
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12/05/2019
Learning to run a power network challenge for training topology controllers
For power grid operations, a large body of research focuses on using gen...
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11/14/2019
Synthetic Event Time Series Health Data Generation
Synthetic medical data which preserves privacy while maintaining utility...
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08/22/2019
LEAP nets for power grid perturbations
We propose a novel neural network embedding approach to model power tran...
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07/29/2019
ChaLearn Looking at People: IsoGD and ConGD Large-scale RGB-D Gesture Recognition
The ChaLearn large-scale gesture recognition challenge has been run twic...
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07/24/2019
Towards AutoML in the presence of Drift: first results
Research progress in AutoML has lead to state of the art solutions that ...
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03/12/2019
AutoML @ NeurIPS 2018 challenge: Design and Results
We organized a competition on Autonomous Lifelong Machine Learning with ...
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05/03/2018
Optimization of computational budget for power system risk assessment
We address the problem of maintaining high voltage power transmission ne...
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05/03/2018
Anticipating contingengies in power grids using fast neural net screening
We address the problem of maintaining high voltage power transmission ne...
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04/21/2018
First Impressions: A Survey on Computer Vision-Based Apparent Personality Trait Analysis
Personality analysis has been widely studied in psychology, neuropsychol...
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03/13/2018
SAM: Structural Agnostic Model, Causal Discovery and Penalized Adversarial Learning
We present the Structural Agnostic Model (SAM), a framework to estimate ...
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02/02/2018
Explaining First Impressions: Modeling, Recognizing, and Explaining Apparent Personality from Videos
Explainability and interpretability are two critical aspects of decision...
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01/30/2018
Fast Power system security analysis with Guided Dropout
We propose a new method to efficiently compute load-flows (the steady-st...
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11/24/2017
Causal Generative Neural Networks
We introduce CGNN, a framework to learn functional causal models as gene...
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09/27/2017
Introducing machine learning for power system operation support
We address the problem of assisting human dispatchers in operating power...
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09/15/2017
Learning Functional Causal Models with Generative Neural Networks
We introduce a new approach to functional causal modeling from observati...
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08/31/2017
Design and Analysis of the NIPS 2016 Review Process
Neural Information Processing Systems (NIPS) is a top-tier annual confer...
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01/10/2017
ChaLearn Looking at People: A Review of Events and Resources
This paper reviews the historic of ChaLearn Looking at People (LAP) even...
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10/17/2013