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06/20/2023
Open Problem: Learning with Variational Objectives on Measures
The theory of statistical learning has focused on variational objectives...
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06/01/2023
Birth of a Transformer: A Memory Viewpoint
Large language models based on transformers have achieved great empirica...
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06/01/2023
Going Deeper with Spectral Embeddings
To make sense of millions of raw data and represent them efficiently, pr...
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05/25/2023
How many samples are needed to leverage smoothness?
A core principle in statistical learning is that smoothness of target fu...
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03/27/2023
Active Self-Supervised Learning: A Few Low-Cost Relationships Are All You Need
Self-Supervised Learning (SSL) has emerged as the solution of choice to ...
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02/06/2023
The SSL Interplay: Augmentations, Inductive Bias, and Generalization
Self-supervised learning (SSL) has emerged as a powerful framework to le...
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11/07/2022
On minimal variations for unsupervised representation learning
Unsupervised representation learning aims at describing raw data efficie...
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09/23/2022
From Weakly Supervised Learning to Active Learning
Applied mathematics and machine computations have raised a lot of hope s...
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05/26/2022
Active Labeling: Streaming Stochastic Gradients
The workhorse of machine learning is stochastic gradient descent. To acc...
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05/20/2022
A Case of Exponential Convergence Rates for SVM
Classification is often the first problem described in introductory mach...
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02/04/2021
Disambiguation of weak supervision with exponential convergence rates
Machine learning approached through supervised learning requires expensi...
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02/01/2021
Fast rates in structured prediction
Discrete supervised learning problems such as classification are often t...
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10/12/2020
Diptychs of human and machine perceptions
We propose visual creations that put differences in algorithms and human...
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09/09/2020
Consistency and Regression with Laplacian regularization in Reproducing Kernel Hilbert Space
This note explains a way to look at reproducing kernel Hilbert space for...
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03/02/2020
Structured Prediction with Partial Labelling through the Infimum Loss
Annotating datasets is one of the main costs in nowadays supervised lear...
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10/10/2019
