Keywords:
- accelerated exact k-means
- Adaboost
- adaptive exploration/exploitation trade-off
- algorithm
- Annulus
- Automatic Speech Recognition
- Autoregressive models
- 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
- Permutations
- person re-identifcation
- premature fine-tuning
- query-free
- query-free interactive content-based image retrieval
- query-free interactive image retrieval
- Random forest
- ranking
- redundancy
- Rejection Sampling
- relevance feedback
- Sampling
- scalable
- Seeding
- self-attention
- semantic segmentation
- sparsity
- Stochastic Variance Reduced Gradient
- sub-quadratic
- SVM
- tensorial operations
- tracking
- trajectories
- Transformer
- transformers
- Tree
- user-based evaluation
- Variance Reduced Gradient
- Vector quantization
- visual content-based features
- Wind Speed Nowcasting
- Yinyany
Publications of Francois Fleuret
2014
| Adaptive Sampling for Large Scale Boosting, and , in: Journal of Machine Learning Research, 15:1431-1453, 2014 |
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| Dynamic Programming Boosting for Discriminative Macro-Action Discovery, and , in: International Conference on Machine Learning, 2014 |
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| Efficient Sample Mining for Object Detection, and , in: Proceedings of the 6th Asian Conference on Machine Learning (ACML), Nha Trang, Vietnam, 2014 |
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| Jointly Informative Feature Selection, and , in: International Conference on Artificial Intelligence and Statistics, pages 567–575, 2014 |
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| LETHA: Learning from High Quality Inputs for 3D Pose Estimation in Low Quality Images, , , and , in: Proceedings of the International Conference on 3D vision, pages 517–524, 2014 |
| LETHA: Learning from High Quality Inputs for 3D Pose Estimation in Low Quality Images., , , and , Idiap-RR-22-2014 |
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| Re-Identification for Improved People Tracking, , and , in: Person Re-Identification, pages 311-336, Springer, 2014 |
| Sample Distillation for Object Detection and Image Classification, , and , in: Proceedings of the 6th Asian Conference on Machine Learning (ACML), Nha Trang, Vietnam, 2014 |
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| Tracking Interacting Objects Optimally Using Integer Programming, , , and , in: Proceedings of the European Conference on Computer Vision, pages 17-32, 2014 |
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2013
| Accelerated Training of Linear Object Detectors, and , in: CVPR 2013 Workshop on Structured Prediction, 2013 |
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| Deformable Part Models with Individual Part Scaling, and , in: British Machine Vision Conference, 2013 |
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| Fast Object Detection with Entropy-Driven Evaluation, , , and , in: Proceedings of the Conference on Computer Vision and Pattern Recognition, 2013 |
| Multi-Commodity Network Flow for Tracking Multiple People, , , and , in: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013 |
| Reservoir Boosting : Between Online and Offline Ensemble Learning, and , in: Proceedings of the international conference on Neural Information Processing Systems, 2013 |
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| treeKL: A distance between high dimension empirical distributions, and , in: Pattern Recognition Letters, 34(2):140-145, 2013 |
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2012
| A real-time deformable detector., , , and , in: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012 |
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| A tree-based distance between distributions: application to classification of neurons, and , in: ICASSP 2012 : IEEE International Conference on Acoustics, Speech and Signal Processing, 2012 |
| Exact Acceleration of Linear Object Detectors, and , in: Proceedings of the European Conference on Computer Vision, 2012 |
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| Improving Object Classification using Pose Information, , , and , Idiap-RR-30-2012 |
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| Iterative Relevance Feedback with Adaptive Exploration/Exploitation Trade-off, and , in: Proceedings of the 21st ACM Conference on Information and Knowledge Management, pages 1323-1331, 2012 |
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| Macro-Action Discovery Based on Change Point Detection and Boosting, and , in: International Conference on Machine Learning and Applications, 2012 |
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2011
| Boosting with Maximum Adaptive Sampling, and , in: Proceedings of the Neural Information Processing Systems Conference, 2011 |
| Comparing machines and humans on a visual categorization test, , , , , and , in: Proceedings of the National Academy of Sciences, 2011 |
| FlowBoost - Appearance Learning from Sparsely Annotated Video, , and , in: Proceedings of the IEEE international conference on Computer Vision and Pattern Recognition, 2011 |
| HEAT: Iterative Relevance Feedback with One Million Images, and , Idiap-RR-33-2011 |
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| HEAT: Iterative Relevance Feedback with One Million Images, and , in: Proceedings of the IEEE International Conference on Computer Vision, pages 2118-2125, 2011 |
| Machine learning techniques to analyse complex, computer vision-extracted, dynamic cellular phenotypes, , , , , and , in: 1st International SystemsX.ch Conference on Systems Biology, 2011 |
| Morphodynamic profiling to explore spatio-temporal signaling networks regulating neurite outgrowth, , , , , , and , in: 1st International SystemsX.ch Conference on Systems Biology, 2011 |
| Multiple Object Tracking using K-Shortest Paths Optimization, , , and , in: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011 |
| Tasting Families of Features for Image Classification, and , in: International Conference on Computer Vision, 2011 |
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| The MASH Project, , , and , in: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2011 |
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| Tracking Multiple Objects under Global Appearance Constraints, , , and , in: Proceedings of the IEEE International Conference on Computer Vision, 2011 |