Search Results - "Ledent, Antoine"

Context-Aware REpresentation: Jointly Learning Item Features and Selection From Triplets by Alves, Rodrigo, Ledent, Antoine

“…In areas of machine learning such as cognitive modeling or recommendation, user feedback is usually context-dependent. For instance, a website might provide a…”
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Uncertainty-Adjusted Recommendation via Matrix Factorization With Weighted Losses by Alves, Rodrigo, Ledent, Antoine, Kloft, Marius

“…In a recommender systems (RSs) dataset, observed ratings are subject to unequal amounts of noise. Some users might be consistently more conscientious in…”
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Orthogonal Inductive Matrix Completion by Ledent, Antoine, Alves, Rodrigo, Kloft, Marius

“…We propose orthogonal inductive matrix completion (OMIC), an interpretable approach to matrix completion based on a sum of multiple orthonormal side…”
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Recommendations with minimum exposure guarantees: A post-processing framework by Lopes, Ramon, Alves, Rodrigo, Ledent, Antoine, Santos, Rodrygo L.T., Kloft, Marius

“…Relevance-based ranking is a popular ingredient in recommenders, but it frequently struggles to meet fairness criteria because social and cultural norms may…”
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Beyond Smoothness: Incorporating Low-Rank Analysis into Nonparametric Density Estimation by Vandermeulen, Robert A, Ledent, Antoine

“…The construction and theoretical analysis of the most popular universally consistent nonparametric density estimators hinge on one functional property:…”
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Orthogonal Inductive Matrix Completion by Ledent, Antoine, Alves, Rodrigo, Kloft, Marius

“…We propose orthogonal inductive matrix completion (OMIC), an interpretable approach to matrix completion based on a sum of multiple orthonormal side…”
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Generalization Bounds for Inductive Matrix Completion in Low-noise Settings by Ledent, Antoine, Alves, Rodrigo, Lei, Yunwen, Guermeur, Yann, Kloft, Marius

“…AAAI 2023 We study inductive matrix completion (matrix completion with side information) under an i.i.d. subgaussian noise assumption at a low noise regime,…”
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Interpretable Tensor Fusion by Varshneya, Saurabh, Ledent, Antoine, Liznerski, Philipp, Balinskyy, Andriy, Mehta, Purvanshi, Mustafa, Waleed, Kloft, Marius

“…Conventional machine learning methods are predominantly designed to predict outcomes based on a single data type. However, practical applications may encompass…”
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Fine-grained Generalization Analysis of Structured Output Prediction by Mustafa, Waleed, Lei, Yunwen, Ledent, Antoine, Kloft, Marius

“…In machine learning we often encounter structured output prediction problems (SOPPs), i.e. problems where the output space admits a rich internal structure…”
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Fine-grained Generalization Analysis of Vector-valued Learning by Wu, Liang, Ledent, Antoine, Lei, Yunwen, Kloft, Marius

“…Many fundamental machine learning tasks can be formulated as a problem of learning with vector-valued functions, where we learn multiple scalar-valued…”
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Norm-based generalisation bounds for multi-class convolutional neural networks by Ledent, Antoine, Mustafa, Waleed, Lei, Yunwen, Kloft, Marius

“…We show generalisation error bounds for deep learning with two main improvements over the state of the art. (1) Our bounds have no explicit dependence on the…”
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Learning Interpretable Concept Groups in CNNs by Varshneya, Saurabh, Ledent, Antoine, Vandermeulen, Robert A, Lei, Yunwen, Enders, Matthias, Borth, Damian, Kloft, Marius

“…We propose a novel training methodology -- Concept Group Learning (CGL) -- that encourages training of interpretable CNN filters by partitioning filters in…”
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