2026 Miguel Á. Carreira-Perpiñán: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	31	13373	12971	5354	5097	153	7757

Overview

Miguel Á. Carreira-Perpiñán is affiliated with the University of California, Merced in the United States. Their research spans multiple areas within computer science, with a primary focus on artificial intelligence and machine learning.

The scientist's work covers several main fields of study including:

Computer Science

Within this broad discipline, the subfields that feature prominently in their publications are:

Artificial Intelligence
Computer Vision and Pattern Recognition
Computational Theory and Mathematics
Computer Networks and Communications
Signal Processing

Key topics addressed in their research include:

Explainable Artificial Intelligence (XAI)
Machine Learning and Data Classification
Neural Networks and Applications
Adversarial Robustness in Machine Learning
Anomaly Detection Techniques and Applications
Formal Methods in Verification
Advanced Neural Network Applications

Some of the recent papers authored or coauthored by Miguel Á. Carreira-Perpiñán are:

"Counterfactual Explanations for Oblique Decision Trees: Exact, Efficient Algorithms," 2021, Proceedings of the AAAI Conference on Artificial Intelligence
"Optimal Interpretable Clustering Using Oblique Decision Trees," 2022, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
"Pushing the Envelope of Gradient Boosting Forests via Globally-Optimized Oblique Trees," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
"Improved Multiclass AdaBoost Using Sparse Oblique Decision Trees," 2022, 2022 International Joint Conference on Neural Networks (IJCNN)
"Sparse oblique decision trees: a tool to understand and manipulate neural net features," 2023, Data Mining and Knowledge Discovery

The scientist has frequently collaborated with several coauthors, including:

Suryabhan Singh Hada
Magzhan Gabidolla
Yerlan Idelbayev
Arman Zharmagambetov
Alberto Cerpa

Their publications have appeared in venues such as:

arXiv (Cornell University)
Proceedings of the AAAI Conference on Artificial Intelligence
2022 International Joint Conference on Neural Networks (IJCNN)
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Best Publications

Multiscale conditional random fields for image labeling

Xuming He;R.S. Zemel;M.A. Carreira-Perpinan

1296
Citations
On Contrastive Divergence Learning.

Miguel Á. Carreira-Perpiñán;Geoffrey E. Hinton

869
Citations
A Review of Dimension Reduction Techniques

Miguel Á. Carreira-Perpiñán

426
Citations
Non-rigid point set registration: Coherent Point Drift

Andriy Myronenko;Xubo Song;Miguel Á. Carreira-Perpiñán

394
Citations
OBSERVE: Occupancy-based system for efficient reduction of HVAC energy

Varick L. Erickson;Miguel A. Carreira-Perpinan;Alberto E. Cerpa

371
Citations
Projection onto the probability simplex: An efficient algorithm with a simple proof, and an application

Weiran Wang;Miguel Á. Carreira-Perpiñán

298
Citations
Mode-finding for mixtures of Gaussian distributions

M.A. Carreira-Perpinan

287
Citations
Gaussian Mean-Shift Is an EM Algorithm

M.A. Carreira-Perpinan

233
Citations
Constrained spectral clustering through affinity propagation

Zhengdong Lu;M.A. Carreira-Perpinan

217
Citations
"Learning-Compression" Algorithms for Neural Net Pruning

Miguel A. Carreira-Perpinan;Yerlan Idelbayev

217
Citations
Hashing with binary autoencoders

Miguel A. Carreira-Perpinan;Ramin Raziperchikolaei

195
Citations
Occupancy Modeling and Prediction for Building Energy Management

Varick L. Erickson;Miguel Á. Carreira-Perpiñán;Alberto E. Cerpa

187
Citations
Proximity Graphs for Clustering and Manifold Learning

Richard S. Zemel;Miguel Á. Carreira-Perpiñán

175
Citations
Distributed optimization of deeply nested systems

Miguel Á. Carreira-Perpiñán;Weiran Wang

171
Citations
Fast nonparametric clustering with Gaussian blurring mean-shift

Miguel Á. Carreira-Perpiñán

149
Citations
The elastic embedding algorithm for dimensionality reduction

Miguel Á. Carreira-Perpiñan

143
Citations
Acceleration Strategies for Gaussian Mean-Shift Image Segmentation

M.A. Carreira-Perpinan

119
Citations
On the number of modes of a Gaussian mixture

Miguel Á. Carreira-Perpiñán;Christopher K. I. Williams

115
Citations
A review of mean-shift algorithms for clustering.

Miguel Á. Carreira-Perpiñán

112
Citations
Practical Identifiability of Finite Mixtures of Multivariate Bernoulli Distributions

Miguel Á. Carreira-Perpiñán;Steve Á. Renals

108
Citations
Low-Rank Compression of Neural Nets: Learning the Rank of Each Layer

Yerlan Idelbayev;Miguel A. Carreira-Perpinan

103
Citations

Frequent Co-Authors

Zhengdong Lu Huawei Technologies (China)

Geoffrey J. Goodhill Washington University in St. Louis

Steve Renals University of Edinburgh

Robert Wang Chinese Academy of Sciences

Mark Sandler Google (United States)

Richard S. Zemel University of Toronto

Deniz Erdogmus Northeastern University

Dominic W. Massaro University of California, Santa Cruz

Cristian Sminchisescu Google (United States)

Geoffrey E. Hinton University of Toronto

External Links

Personal website of Miguel Á. Carreira-Perpiñán

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