Search Results - "Dumoulin, Vincent"

Birds, bats and beyond: evaluating generalization in bioacoustics models by van Merriënboer, Bart, Hamer, Jenny, Dumoulin, Vincent, Triantafillou, Eleni, Denton, Tom

“…In the context of passive acoustic monitoring (PAM) better models are needed to reliably gain insights from large amounts of raw, unlabeled data. Bioacoustics…”
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On the Response Entropy of APUFs by Dumoulin, Vincent, Rao, Wenjing, Devroye, Natasha

“…A physically unclonable function (PUF) is a hardware security primitive used for authentication and key generation. It takes an input bit-vector challenge and…”
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Proper Reuse of Image Classification Features Improves Object Detection by Vasconcelos, Cristina, Birodkar, Vighnesh, Dumoulin, Vincent

“…A common practice in transfer learning is to initialize the downstream model weights by pre-training on a data-abundant upstream task. In object detection…”
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Impact of Aliasing on Generalization in Deep Convolutional Networks by Vasconcelos, Cristina, Larochelle, Hugo, Dumoulin, Vincent, Romijnders, Rob, Le Roux, Nicolas, Goroshin, Ross

“…We investigate the impact of aliasing on generalization in Deep Convolutional Networks and show that data augmentation schemes alone are unable to prevent it…”
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APUF Faults: Impact, Testing, and Diagnosis by Wei, Yeqi, Fox, Tim, Dumoulin, Vincent, Rao, Wenjing, Devroye, Natasha

“…Arbiter Physically Unclonable Functions (APUFs) are hardware security primitives that exploit manufacturing random-ness to generate unique digital fingerprints…”
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On the Response Entropy of APUFs by Dumoulin, Vincent, Rao, Wenjing, Devroye, Natasha

“…A Physically Unclonable Function (PUF) is a hardware security primitive used for authentication and key generation. It takes an input bit-vector challenge and…”
Get full text

Active learning for fast and slow modeling attacks on Arbiter PUFs by Dumoulin, Vincent, Rao, Wenjing, Devroye, Natasha

“…Modeling attacks, in which an adversary uses machine learning techniques to model a hardware-based Physically Unclonable Function (PUF) pose a great threat to…”
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Data Selection for Transfer Unlearning by Sepahvand, Nazanin Mohammadi, Dumoulin, Vincent, Triantafillou, Eleni, Dziugaite, Gintare Karolina

“…As deep learning models are becoming larger and data-hungrier, there are growing ethical, legal and technical concerns over use of data: in practice,…”
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Proper Reuse of Image Classification Features Improves Object Detection by Vasconcelos, Cristina, Birodkar, Vighnesh, Dumoulin, Vincent

“…CVPR 2022 A common practice in transfer learning is to initialize the downstream model weights by pre-training on a data-abundant upstream task. In object…”
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BIRB: A Generalization Benchmark for Information Retrieval in Bioacoustics by Hamer, Jenny, Triantafillou, Eleni, van Merriënboer, Bart, Kahl, Stefan, Klinck, Holger, Denton, Tom, Dumoulin, Vincent

“…The ability for a machine learning model to cope with differences in training and deployment conditions--e.g. in the presence of distribution shift or the…”
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A density estimation perspective on learning from pairwise human preferences by Dumoulin, Vincent, Johnson, Daniel D, Castro, Pablo Samuel, Larochelle, Hugo, Dauphin, Yann

“…Learning from human feedback (LHF) -- and in particular learning from pairwise preferences -- has recently become a crucial ingredient in training large…”
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Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning by Evci, Utku, Dumoulin, Vincent, Larochelle, Hugo, Mozer, Michael C

“…ICML 2022, Proceedings of the 39th International Conference on Machine Learning Transfer-learning methods aim to improve performance in a data-scarce target…”
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Active learning for fast and slow modeling attacks on Arbiter PUFs by Dumoulin, Vincent, Rao, Wenjing, Devroye, N atasha

“…Modeling attacks, in which an adversary uses machine learning techniques to model a hardware-based Physically Unclonable Function (PUF) pose a great threat to…”
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In Search for a Generalizable Method for Source Free Domain Adaptation by Boudiaf, Malik, Denton, Tom, van Merriënboer, Bart, Dumoulin, Vincent, Triantafillou, Eleni

“…Source-free domain adaptation (SFDA) is compelling because it allows adapting an off-the-shelf model to a new domain using only unlabelled data. In this work,…”
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Learning a Universal Template for Few-shot Dataset Generalization by Triantafillou, Eleni, Larochelle, Hugo, Zemel, Richard, Dumoulin, Vincent

“…Few-shot dataset generalization is a challenging variant of the well-studied few-shot classification problem where a diverse training set of several datasets…”
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A guide to convolution arithmetic for deep learning by Dumoulin, Vincent, Visin, Francesco

“…We introduce a guide to help deep learning practitioners understand and manipulate convolutional neural network architectures. The guide clarifies the…”
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Cross-Modulation Networks for Few-Shot Learning by Prol, Hugo, Dumoulin, Vincent, Herranz, Luis

“…A family of recent successful approaches to few-shot learning relies on learning an embedding space in which predictions are made by computing similarities…”
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Are we making progress in unlearning? Findings from the first NeurIPS unlearning competition by Triantafillou, Eleni, Kairouz, Peter, Pedregosa, Fabian, Hayes, Jamie, Kurmanji, Meghdad, Zhao, Kairan, Dumoulin, Vincent, Junior, Julio Jacques, Mitliagkas, Ioannis, Wan, Jun, Hosoya, Lisheng Sun, Escalera, Sergio, Dziugaite, Gintare Karolina, Triantafillou, Peter, Guyon, Isabelle

“…We present the findings of the first NeurIPS competition on unlearning, which sought to stimulate the development of novel algorithms and initiate discussions…”
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Leveraging tropical reef, bird and unrelated sounds for superior transfer learning in marine bioacoustics by Williams, Ben, van Merriënboer, Bart, Dumoulin, Vincent, Hamer, Jenny, Triantafillou, Eleni, Fleishman, Abram B, McKown, Matthew, Munger, Jill E, Rice, Aaron N, Lillis, Ashlee, White, Clemency E, Hobbs, Catherine A. D, Razak, Tries B, Jones, Kate E, Denton, Tom

“…Machine learning has the potential to revolutionize passive acoustic monitoring (PAM) for ecological assessments. However, high annotation and compute costs…”
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Impact of Aliasing on Generalization in Deep Convolutional Networks by Vasconcelos, Cristina, Larochelle, Hugo, Dumoulin, Vincent, Romijnders, Rob, Roux, Nicolas Le, Goroshin, Ross

“…We investigate the impact of aliasing on generalization in Deep Convolutional Networks and show that data augmentation schemes alone are unable to prevent it…”
Get full text