
Sparse Oblique Decision Trees: A Tool to Understand and Manipulate Neural Net Features
The widespread deployment of deep nets in practical applications has lea...
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Counterfactual Explanations for Oblique Decision Trees: Exact, Efficient Algorithms
We consider counterfactual explanations, the problem of minimally adjust...
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A flexible, extensible software framework for model compression based on the LC algorithm
We propose a software framework based on the ideas of the LearningCompr...
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Structured MultiHashing for Model Compression
Despite the success of deep neural networks (DNNs), stateoftheart mod...
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An Experimental Comparison of Old and New Decision Tree Algorithms
This paper presents a detailed comparison of a recently proposed algorit...
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Style Transfer by Rigid Alignment in Neural Net Feature Space
Arbitrary style transfer is an important problem in computer vision that...
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Model compression as constrained optimization, with application to neural nets. Part II: quantization
We consider the problem of deep neural net compression by quantization: ...
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Model compression as constrained optimization, with application to neural nets. Part I: general framework
Compressing neural nets is an active research problem, given the large s...
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ParMAC: distributed optimisation of nested functions, with application to learning binary autoencoders
Many powerful machine learning models are based on the composition of mu...
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An ensemble diversity approach to supervised binary hashing
Binary hashing is a wellknown approach for fast approximate nearestnei...
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A review of meanshift algorithms for clustering
A natural way to characterize the cluster structure of a dataset is by f...
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Optimizing affinitybased binary hashing using auxiliary coordinates
In supervised binary hashing, one wants to learn a function that maps a ...
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Hashing with binary autoencoders
An attractive approach for fast search in image databases is binary hash...
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An ADMM algorithm for solving a proximal boundconstrained quadratic program
We consider a proximal operator given by a quadratic function subject to...
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The role of dimensionality reduction in linear classification
Dimensionality reduction (DR) is often used as a preprocessing step in c...
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LASS: a simple assignment model with Laplacian smoothing
We consider the problem of learning soft assignments of N items to K cat...
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Projection onto the probability simplex: An efficient algorithm with a simple proof, and an application
We provide an elementary proof of a simple, efficient algorithm for comp...
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The Kmodes algorithm for clustering
Many clustering algorithms exist that estimate a cluster centroid, such ...
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Distributed optimization of deeply nested systems
In science and engineering, intelligent processing of complex signals su...
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Reconstruction of sequential data with density models
We introduce the problem of reconstructing a sequence of multidimensiona...
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Generalised elastic nets
The elastic net was introduced as a heuristic algorithm for combinatoria...
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Miguel Á. CarreiraPerpiñán
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Professor of Electrical Engineering and Computer Science at University of California, Merced