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06/23/2023
Neural Algorithmic Reasoning Without Intermediate Supervision
Neural Algorithmic Reasoning is an emerging area of machine learning foc...
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02/27/2023
Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts
In reliable decision-making systems based on machine learning, models ha...
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02/22/2023
A critical look at the evaluation of GNNs under heterophily: are we really making progress?
Node classification is a classical graph representation learning task on...
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09/13/2022
Characterizing Graph Datasets for Node Classification: Beyond Homophily-Heterophily Dichotomy
Homophily is a graph property describing the tendency of edges to connec...
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06/11/2022
Gradient Boosting Performs Low-Rank Gaussian Process Inference
This paper shows that gradient boosting based on symmetric decision tree...
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04/04/2022
Which Tricks are Important for Learning to Rank?
Nowadays, state-of-the-art learning-to-rank (LTR) methods are based on g...
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01/22/2022
Good Classification Measures and How to Find Them
Several performance measures can be used for evaluating classification r...
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07/15/2021
Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks
There has been significant research done on developing methods for impro...
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01/21/2021
Boost then Convolve: Gradient Boosting Meets Graph Neural Networks
Graph neural networks (GNNs) are powerful models that have been successf...
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10/06/2020
Embedding Words in Non-Vector Space with Unsupervised Graph Learning
It has become a de-facto standard to represent words as elements of a ve...
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07/05/2020
Overlaying Spaces and Practical Applicability of Complex Geometries
Recently, non-Euclidean spaces became popular for embedding structured d...
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06/18/2020
Uncertainty in Gradient Boosting via Ensembles
Gradient boosting is a powerful machine learning technique that is parti...
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03/04/2020
StochasticRank: Global Optimization of Scale-Free Discrete Functions
In this paper, we introduce a powerful and efficient framework for the d...
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01/20/2020
SGLB: Stochastic Gradient Langevin Boosting
In this paper, we introduce Stochastic Gradient Langevin Boosting (SGLB)...
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11/12/2019
Systematic Analysis of Cluster Similarity Indices: Towards Bias-free Cluster Validation
There are many cluster similarity indices used to evaluate clustering al...
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07/01/2019
