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Unsupervised clustering of series using dynamic programming and neural processes
Following the work of arXiv:2101.09512, we are interested in clustering ...
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Unsupervised clustering of series using dynamic programming
We are interested in clustering parts of a given single multi-variate se...
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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...
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Fast Transformers with Clustered Attention
Transformers have been proven a successful model for a variety of tasks ...
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Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention
Transformers achieve remarkable performance in several tasks but due to ...
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Taming GANs with Lookahead
Generative Adversarial Networks are notoriously challenging to train. Th...
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Gradient Alignment in Deep Neural Networks
One cornerstone of interpretable deep learning is the high degree of vis...
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Fair Latency-Aware Metric for real-time video segmentation networks
As supervised semantic segmentation is reaching satisfying results, many...
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Multi-task Reinforcement Learning with a Planning Quasi-Metric
We introduce a new reinforcement learning approach combining a planning ...
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On the Tunability of Optimizers in Deep Learning
There is no consensus yet on the question whether adaptive gradient meth...
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Processing Megapixel Images with Deep Attention-Sampling Models
Existing deep architectures cannot operate on very large signals such as...
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Full-Jacobian Representation of Neural Networks
Non-linear functions such as neural networks can be locally approximated...
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Reducing Noise in GAN Training with Variance Reduced Extragradient
Using large mini-batches when training generative adversarial networks (...
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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...
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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 ...
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Knowledge Transfer with Jacobian Matching
Classical distillation methods transfer representations from a "teacher"...
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Geodesic Convolutional Shape Optimization
Aerodynamic shape optimization has many industrial applications. Existin...
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SGAN: An Alternative Training of Generative Adversarial Networks
The Generative Adversarial Networks (GANs) have demonstrated impressive ...
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The WILDTRACK Multi-Camera Person Dataset
People detection methods are highly sensitive to the perpetual occlusion...
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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...
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Semi-supervised learning of deep metrics for stereo reconstruction
Deep-learning metrics have recently demonstrated extremely good performa...
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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...
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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 ...
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Multi-Modal Mean-Fields via Cardinality-Based Clamping
Mean Field inference is central to statistical physics. It has attracted...
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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 ...
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A Sub-Quadratic Exact Medoid Algorithm
We present a new algorithm, trimed, for obtaining the medoid of a set, t...
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Scalable Metric Learning via Weighted Approximate Rank Component Analysis
We are interested in the large-scale learning of Mahalanobis distances, ...
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Nested Mini-Batch K-Means
A new algorithm is proposed which accelerates the mini-batch k-means alg...
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Fast K-Means with Accurate Bounds
We propose a novel accelerated exact k-means algorithm, which performs b...
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