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Miguel Á. Carreira-Perpiñán

University of California, Merced
Oregon Health & Science University

132

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More General and Effective Model Compression via an Additive Combination of Compressions

2021 PKDD | European Conference on Principles of Data Mining and Knowledge Discovery
- Yerlan Idelbayev
- Miguel Á. Carreira-Perpiñán
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Optimal Quantization Using Scaled Codebook.

2021 CVPR | Computer Vision and Pattern Recognition
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Counterfactual Explanations for Oblique Decision Trees: Exact, Efficient Algorithms

2021 arXiv: Learning
- Miguel Á. Carreira-Perpiñán
- Suryabhan Singh Hada
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An Empirical Comparison of Quantization, Pruning and Low-rank Neural Network Compression using the LC Toolkit

2021 IJCNN | International Joint Conference on Neural Network
- Yerlan Idelbayev
- Miguel Á. Carreira-Perpiñán
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Improved Multiclass Adaboost For Image Classification: The Role Of Tree Optimization

2021 ICIP | International Conference on Image Processing
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Neural Network Compression via Additive Combination of Reshaped, Low-Rank Matrices

2021 DCC | Data Compression Conference
- Yerlan Idelbayev
- Miguel Á. Carreira-Perpiñán
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Softmax Tree: An Accurate, Fast Classifier When the Number of Classes Is Large

2021 EMNLP | Empirical Methods in Natural Language Processing
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Improved Boosted Regression Forests Through Non-Greedy Tree Optimization

2021 IJCNN | International Joint Conference on Neural Network
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Understanding And Manipulating Neural Net Features Using Sparse Oblique Classification Trees

2021 ICIP | International Conference on Image Processing
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A Simple, Effective Way To Improve Neural Net Classification: Ensembling Unit Activations With A Sparse Oblique Decision Tree

2021 ICIP | International Conference on Image Processing
- Arman Zharmagambetov
- Miguel Á. Carreira-Perpiñán
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