Keywords:
- accelerated exact k-means
- Adaboost
- adaptive exploration/exploitation trade-off
- algorithm
- Annulus
- Automatic Speech Recognition
- batch
- Bayesian framework
- Benchmarking
- BERT
- bioinformatics
- boosting
- Bootstrapping
- clustering
- computational efficiency
- Computer Vision
- content-based image retrieval
- Convolutional Neural Networks
- cue integration
- Deep Generative Models
- deep learning
- Elkan
- exact
- exact k-means
- Exponion
- feature combination
- feature selection
- Gaussian Mixture Model
- Gaussian Mixture Models (GMM)
- Generative Adversarial Networks
- genomics
- Greedy Edge Expectation Maximization (GEEM)
- Hamerly
- Hard Mining
- Hyperparameter optimization
- Image classification
- Importance Sampling
- Initialisation
- interactive
- iterative
- iterative relevance feedback
- K-means
- k-medoids
- k-nearest neighbors
- large-scale
- large-scale iterative relevance feedback
- localization
- log-based similarity learning
- lookahead
- machine learning
- medoid
- Metric learning
- Mini-batch
- minimax
- multimodal textual-based and visual content-based features
- nested
- nesting
- object detection
- Off-target effect
- optimization
- orthonormal regularizer
- parallel
- pattern classification
- person re-identifcation
- premature fine-tuning
- query-free
- query-free interactive content-based image retrieval
- query-free interactive image retrieval
- Random forest
- ranking
- redundancy
- relevance feedback
- Sampling
- scalable
- Seeding
- self-attention
- semantic segmentation
- sparsity
- Stochastic Variance Reduced Gradient
- sub-quadratic
- SVM
- tensorial operations
- tracking
- trajectories
- Transformer
- Tree
- user-based evaluation
- Variance Reduced Gradient
- Vector quantization
- visual content-based features
- Wind Speed Nowcasting
- Yinyany
Publications of Francois Fleuret
2010
| Joint Cascade Optimization Using a Product Of Boosted Classifiers, and , in: Proceedings of the Neural Information Processing Systems Conference, pages 1315–1323, 2010 |
2009
| Evaluation of Probabilistic Occupancy Map People Detection for Surveillance Systems, , , , and , in: Proceedings of the IEEE International Workshop on Performance Evaluation of Tracking and Surveillance, 2009 |
| Joint Pose Estimator and Feature Learning for Object Detection, , , and , in: Proceedings of the IEEE International Conference on Computer Vision, 2009 |
| Learning Rotational Features for Filament Detection, , and , in: Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition, 2009 |
| Multi-layer Boosting for Pattern Recognition, , in: Pattern Recognition Letter, 30, 2009 |
| Multiple Object Tracking using Flow Linear Programming, , and , Idiap-RR-10-2009 |
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| Steerable Features for Statistical 3D Dendrite Detection, , , , and , in: Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention, 2009 |
2008
| Automated Delineation of Dendritic Networks in Noisy Image Stacks, , and , in: proceedings of the European Conference on Computer Vision, 2008 |
| Classification-based Probabilistic Modeling of Texture Transition for Fast Line Search Tracking and Delineation, , , and , in: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008 |
| Multi-Camera People Tracking with a Probabilistic Occupancy Map, , , and , in: IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(2), 2008 |
| Multi-Camera Tracking and Atypical Motion Detection with Behavioral Maps, , and , in: proceedings of the European Conference on Computer Vision, 2008 |
| Multi-layer Boosting for Pattern Recognition, , Idiap-RR-76-2008 |
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| Principled Detection-by-classification from Multiple Views, , and , in: proceedings of the International Conference on Computer Vision Theory and Applications, 2008 |
| Stationary Features and Cat Detection, and , in: Journal of Machine Learning Research, 9, 2008 |
2007
| Stationary Features and Cat Detection, and , Idiap-RR-56-2007 |
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