François Fleuret

Unsupervised clustering of series using dynamic programming and neural processes

Following the work of arXiv:2101.09512, we are interested in clustering ...
01/26/2021 ∙ by Karthigan Sinnathamby, et al. ∙ 11 ∙ share

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Unsupervised clustering of series using dynamic programming

We are interested in clustering parts of a given single multi-variate se...
01/23/2021 ∙ by Karthigan Sinnathamby, et al. ∙ 11 ∙ share

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On the importance of pre-training data volume for compact language models

Recent advances in language modeling have led to computationally intensi...
10/08/2020 ∙ by Vincent Micheli, et al. ∙ 0 ∙ share

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Fast Transformers with Clustered Attention

Transformers have been proven a successful model for a variety of tasks ...
07/09/2020 ∙ by Apoorv Vyas, et al. ∙ 34 ∙ share

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Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention

Transformers achieve remarkable performance in several tasks but due to ...
06/29/2020 ∙ by Angelos Katharopoulos, et al. ∙ 35 ∙ share

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Taming GANs with Lookahead

Generative Adversarial Networks are notoriously challenging to train. Th...
06/25/2020 ∙ by Tatjana Chavdarova, et al. ∙ 12 ∙ share

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Gradient Alignment in Deep Neural Networks

One cornerstone of interpretable deep learning is the high degree of vis...
06/16/2020 ∙ by Suraj Srinivas, et al. ∙ 17 ∙ share

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Fair Latency-Aware Metric for real-time video segmentation networks

As supervised semantic segmentation is reaching satisfying results, many...
04/06/2020 ∙ by Evann Courdier, et al. ∙ 4 ∙ share

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Multi-task Reinforcement Learning with a Planning Quasi-Metric

We introduce a new reinforcement learning approach combining a planning ...
02/08/2020 ∙ by Vincent Micheli, et al. ∙ 55 ∙ share

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On the Tunability of Optimizers in Deep Learning

There is no consensus yet on the question whether adaptive gradient meth...
10/25/2019 ∙ by Prabhu Teja Sivaprasad, et al. ∙ 8 ∙ share

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Processing Megapixel Images with Deep Attention-Sampling Models

Existing deep architectures cannot operate on very large signals such as...
05/03/2019 ∙ by Angelos Katharopoulos, et al. ∙ 26 ∙ share

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Full-Jacobian Representation of Neural Networks

Non-linear functions such as neural networks can be locally approximated...
05/02/2019 ∙ by Suraj Srinivas, et al. ∙ 70 ∙ share

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Reducing Noise in GAN Training with Variance Reduced Extragradient

Using large mini-batches when training generative adversarial networks (...
04/18/2019 ∙ by Tatjana Chavdarova, et al. ∙ 38 ∙ share

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Practical Deep Stereo (PDS): Toward applications-friendly deep stereo matching

End-to-end deep-learning networks recently demonstrated extremely good p...
06/05/2018 ∙ by Stepan Tulyakov, et al. ∙ 10 ∙ share

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Not All Samples Are Created Equal: Deep Learning with Importance Sampling

Deep neural network training spends most of the computation on examples ...
03/02/2018 ∙ by Angelos Katharopoulos, et al. ∙ 0 ∙ share

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Knowledge Transfer with Jacobian Matching

Classical distillation methods transfer representations from a "teacher"...
03/01/2018 ∙ by Suraj Srinivas, et al. ∙ 0 ∙ share

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Geodesic Convolutional Shape Optimization

Aerodynamic shape optimization has many industrial applications. Existin...
02/12/2018 ∙ by Pierre Baqué, et al. ∙ 0 ∙ share

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SGAN: An Alternative Training of Generative Adversarial Networks

The Generative Adversarial Networks (GANs) have demonstrated impressive ...
12/06/2017 ∙ by Tatjana Chavdarova, et al. ∙ 0 ∙ share

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The WILDTRACK Multi-Camera Person Dataset

People detection methods are highly sensitive to the perpetual occlusion...
07/28/2017 ∙ by Tatjana Chavdarova, et al. ∙ 0 ∙ share

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Geometric calibration of Colour and Stereo Surface Imaging System of ESA's Trace Gas Orbiter

There are many geometric calibration methods for "standard" cameras. The...
07/03/2017 ∙ by Stepan Tulyakov, et al. ∙ 0 ∙ share

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Semi-supervised learning of deep metrics for stereo reconstruction

Deep-learning metrics have recently demonstrated extremely good performa...
12/03/2016 ∙ by Stepan Tulyakov, et al. ∙ 0 ∙ share

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Globally Consistent Multi-People Tracking using Motion Patterns

Many state-of-the-art approaches to people tracking rely on detecting th...
12/02/2016 ∙ by Andrii Maksai, et al. ∙ 0 ∙ share

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Social Scene Understanding: End-to-End Multi-Person Action Localization and Collective Activity Recognition

We present a unified framework for understanding human social behaviors ...
11/28/2016 ∙ by Timur Bagautdinov, et al. ∙ 0 ∙ share

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Multi-Modal Mean-Fields via Cardinality-Based Clamping

Mean Field inference is central to statistical physics. It has attracted...
11/23/2016 ∙ by Pierre Baqué, et al. ∙ 0 ∙ share

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Predicting the dynamics of 2d objects with a deep residual network

We investigate how a residual network can learn to predict the dynamics ...
10/13/2016 ∙ by François Fleuret, et al. ∙ 0 ∙ share

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A Sub-Quadratic Exact Medoid Algorithm

We present a new algorithm, trimed, for obtaining the medoid of a set, t...
05/23/2016 ∙ by James Newling, et al. ∙ 0 ∙ share

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Scalable Metric Learning via Weighted Approximate Rank Component Analysis

We are interested in the large-scale learning of Mahalanobis distances, ...
03/01/2016 ∙ by Cijo Jose, et al. ∙ 0 ∙ share

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Nested Mini-Batch K-Means

A new algorithm is proposed which accelerates the mini-batch k-means alg...
02/09/2016 ∙ by James Newling, et al. ∙ 0 ∙ share

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Fast K-Means with Accurate Bounds

We propose a novel accelerated exact k-means algorithm, which performs b...
02/08/2016 ∙ by James Newling, et al. ∙ 0 ∙ share

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François Fleuret

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