Miguel Á. Carreira-Perpiñán | DeepAI

DeepAI AI Chat

Featured Co-authors

Hao Wu
145 publications
Mark Sandler
43 publications
Weiran Wang
42 publications
Elad Eban
11 publications
Pedro Lopez-Garcia
10 publications
Yair Movshovitz-Attias
8 publications
Ramin Raziperchikolaei
8 publications
Maximiliano Klemen
7 publications
Suryabhan Singh Hada
6 publications
Yerlan Idelbayev
4 publications
Arman Zharmagambetov
3 publications

∙ 09/16/2023

Inverse classification with logistic and softmax classifiers: efficient optimization

In recent years, a certain type of problems have become of interest wher...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

∙ 08/30/2023

Solving Recurrence Relations using Machine Learning, with Application to Cost Analysis

Automatic static cost analysis infers information about the resources us...

0 Maximiliano Klemen, et al. ∙

∙ 03/06/2023

Very fast, approximate counterfactual explanations for decision forests

We consider finding a counterfactual explanation for a classification or...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

∙ 07/09/2021

Model compression as constrained optimization, with application to neural nets. Part V: combining compressions

Model compression is generally performed by using quantization, low-rank...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

∙ 04/07/2021

Sparse Oblique Decision Trees: A Tool to Understand and Manipulate Neural Net Features

The widespread deployment of deep nets in practical applications has lea...

16 Suryabhan Singh Hada, et al. ∙

∙ 03/01/2021

Counterfactual Explanations for Oblique Decision Trees: Exact, Efficient Algorithms

We consider counterfactual explanations, the problem of minimally adjust...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

∙ 05/15/2020

A flexible, extensible software framework for model compression based on the LC algorithm

We propose a software framework based on the ideas of the Learning-Compr...

0 Yerlan Idelbayev, et al. ∙

∙ 11/25/2019

Structured Multi-Hashing for Model Compression

Despite the success of deep neural networks (DNNs), state-of-the-art mod...

19 Elad Eban, et al. ∙

∙ 11/08/2019

An Experimental Comparison of Old and New Decision Tree Algorithms

This paper presents a detailed comparison of a recently proposed algorit...

0 Arman Zharmagambetov, et al. ∙

∙ 09/27/2019

Style Transfer by Rigid Alignment in Neural Net Feature Space

Arbitrary style transfer is an important problem in computer vision that...

16 Suryabhan Singh Hada, et al. ∙

∙ 07/13/2017

Model compression as constrained optimization, with application to neural nets. Part II: quantization

We consider the problem of deep neural net compression by quantization: ...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

∙ 07/05/2017

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...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

∙ 05/30/2016

ParMAC: distributed optimisation of nested functions, with application to learning binary autoencoders

Many powerful machine learning models are based on the composition of mu...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

∙ 02/04/2016

An ensemble diversity approach to supervised binary hashing

Binary hashing is a well-known approach for fast approximate nearest-nei...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

∙ 03/02/2015

A review of mean-shift algorithms for clustering

A natural way to characterize the cluster structure of a dataset is by f...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

∙ 01/21/2015

Optimizing affinity-based binary hashing using auxiliary coordinates

In supervised binary hashing, one wants to learn a function that maps a ...

0 Ramin Raziperchikolaei, et al. ∙

∙ 01/05/2015

Hashing with binary autoencoders

An attractive approach for fast search in image databases is binary hash...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

∙ 12/29/2014

An ADMM algorithm for solving a proximal bound-constrained quadratic program

We consider a proximal operator given by a quadratic function subject to...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

∙ 05/26/2014

The role of dimensionality reduction in linear classification

Dimensionality reduction (DR) is often used as a preprocessing step in c...

0 Weiran Wang, et al. ∙

∙ 05/23/2014

LASS: a simple assignment model with Laplacian smoothing

We consider the problem of learning soft assignments of N items to K cat...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

∙ 09/06/2013

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...

0 Weiran Wang, et al. ∙

∙ 04/24/2013

The K-modes algorithm for clustering

Many clustering algorithms exist that estimate a cluster centroid, such ...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

∙ 12/24/2012

Distributed optimization of deeply nested systems

In science and engineering, intelligent processing of complex signals su...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

∙ 09/15/2011

Reconstruction of sequential data with density models

We introduce the problem of reconstructing a sequence of multidimensiona...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

∙ 08/14/2011

Generalised elastic nets

The elastic net was introduced as a heuristic algorithm for combinatoria...

0 Miguel Á. Carreira-Perpiñán, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world