Miguel Á. Carreira-Perpiñán

ORCID

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 63

Top Venues

University of Sheffield, UK (PHD)

Education History

University of Sheffield, UK

PHD

Publications

Rasul Kairgeldin, Miguel Á. Carreira-Perpiñán
Bivariate Decision Trees: Smaller, Interpretable, More Accurate. KDD (2024)
Louis Rustenholz, Maximiliano Klemen, Miguel Á. Carreira-Perpiñán, Pedro López-García
A Machine Learning-based Approach for Solving Recurrence Relations and its use in Cost Analysis of Logic Programs. CoRR (2024)
Miguel Á. Carreira-Perpiñán, Magzhan Gabidolla, Arman Zharmagambetov
Towards Better Decision Forests: Forest Alternating Optimization. CVPR (2023)
Maximiliano Klemen, Miguel Á. Carreira-Perpiñán, Pedro López-García
Solving Recurrence Relations using Machine Learning, with Application to Cost Analysis. ICLP (2023)
Miguel Á. Carreira-Perpiñán, Suryabhan Singh Hada
Inverse classification with logistic and softmax classifiers: efficient optimization. CoRR (2023)
Miguel Á. Carreira-Perpiñán, Suryabhan Singh Hada
Very fast, approximate counterfactual explanations for decision forests. CoRR (2023)
Miguel Á. Carreira-Perpiñán, Suryabhan Singh Hada
Very Fast, Approximate Counterfactual Explanations for Decision Forests. AAAI (2023)
Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán
Interpretable Image Classification Using Sparse Oblique Decision Trees. ICASSP (2022)
Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán
Sparse Oblique Decision Trees: A Tool to Interpret Natural Language Processing Datasets. IJCNN (2022)
Arman S. Zharmagambetov, Miguel Á. Carreira-Perpiñán
Learning Interpretable, Tree-Based Projection Mappings for Nonlinear Embeddings. AISTATS (2022)
Magzhan Gabidolla, Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán
Improved Multiclass AdaBoost Using Sparse Oblique Decision Trees. IJCNN (2022)
Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán
Semi-Supervised Learning with Decision Trees: Graph Laplacian Tree Alternating Optimization. NeurIPS (2022)
Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán
Pushing the Envelope of Gradient Boosting Forests via Globally-Optimized Oblique Trees. CVPR (2022)
Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán
Optimal Interpretable Clustering Using Oblique Decision Trees. KDD (2022)
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
Exploring the Effect of ℓ0/ℓ2 Regularization in Neural Network Pruning using the LC Toolkit. ICASSP (2022)
Arman Zharmagambetov, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán
Improved Multiclass Adaboost For Image Classification: The Role Of Tree Optimization. ICIP (2021)
Miguel Á. Carreira-Perpiñán, Suryabhan Singh Hada
Counterfactual Explanations for Oblique Decision Trees: Exact, Efficient Algorithms. CoRR (2021)
Arman Zharmagambetov, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán
Improved Boosted Regression Forests Through Non-Greedy Tree Optimization. IJCNN (2021)
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
Neural Network Compression via Additive Combination of Reshaped, Low-Rank Matrices. DCC (2021)
Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán
Exploring Counterfactual Explanations for Classification and Regression Trees. PKDD/ECML Workshops (1) (2021)
Miguel Á. Carreira-Perpiñán, Suryabhan Singh Hada
Counterfactual Explanations for Oblique Decision Trees: Exact, Efficient Algorithms. AAAI (2021)
Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán
A Simple, Effective Way To Improve Neural Net Classification: Ensembling Unit Activations With A Sparse Oblique Decision Tree. ICIP (2021)
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
Beyond Flops In Low-Rank Compression Of Neural Networks: Optimizing Device-Specific Inference Runtime. ICIP (2021)
Arman Zharmagambetov, Suryabhan Singh Hada, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán
Non-Greedy Algorithms for Decision Tree Optimization: An Experimental Comparison. IJCNN (2021)
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
An Empirical Comparison of Quantization, Pruning and Low-rank Neural Network Compression using the LC Toolkit. IJCNN (2021)
Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán
Learning a Tree of Neural Nets. ICASSP (2021)
Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov
Sparse Oblique Decision Trees: A Tool to Understand and Manipulate Neural Net Features. CoRR (2021)
Yerlan Idelbayev, Pavlo Molchanov, Maying Shen, Hongxu Yin, Miguel Á. Carreira-Perpiñán, Jose M. Alvarez
Optimal Quantization Using Scaled Codebook. CVPR (2021)
Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov
Understanding And Manipulating Neural Net Features Using Sparse Oblique Classification Trees. ICIP (2021)
Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán
Sampling The "Inverse Set" of a Neuron. ICIP (2021)
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
Optimal Selection of Matrix Shape and Decomposition Scheme for Neural Network Compression. ICASSP (2021)
Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán
Style Transfer by Rigid Alignment in Neural Net Feature Space. WACV (2021)
Miguel Á. Carreira-Perpiñán, Yerlan Idelbayev
Model compression as constrained optimization, with application to neural nets. Part V: combining compressions. CoRR (2021)
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
More General and Effective Model Compression via an Additive Combination of Compressions. ECML/PKDD (3) (2021)
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
LC: A Flexible, Extensible Open-Source Toolkit for Model Compression. CIKM (2021)
Arman Zharmagambetov, Magzhan Gabidolla, Miguel Á. Carreira-Perpiñán
Softmax Tree: An Accurate, Fast Classifier When the Number of Classes Is Large. EMNLP (1) (2021)
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
Low-Rank Compression of Neural Nets: Learning the Rank of Each Layer. CVPR (2020)
Arman Zharmagambetov, Miguel Á. Carreira-Perpiñán
Smaller, more accurate regression forests using tree alternating optimization. ICML (2020)
Elad Eban, Yair Movshovitz-Attias, Hao Wu, Mark Sandler, Andrew Poon, Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
Structured Multi-Hashing for Model Compression. CVPR (2020)
Daniel A. Winkler, Miguel Á. Carreira-Perpiñán, Alberto E. Cerpa
OPTICS: OPTimizing Irrigation Control at Scale. ACM Trans. Sens. Networks 16 (3) (2020)
Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
A flexible, extensible software framework for model compression based on the LC algorithm. CoRR (2020)
Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov
Ensembles of Bagged TAO Trees Consistently Improve over Random Forests, AdaBoost and Gradient Boosting. FODS (2020)
Miguel Á. Carreira-Perpiñán, Mehdi Alizadeh
Parmac: Distributed Optimisation Of Nested Functions, With Application To Learning Binary Autoencoders. MLSys (2019)
Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán
Sampling the "Inverse Set" of a Neuron: An Approach to Understanding Neural Nets. CoRR (2019)
Arman Zharmagambetov, Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán
An Experimental Comparison of Old and New Decision Tree Algorithms. CoRR (2019)
Suryabhan Singh Hada, Miguel Á. Carreira-Perpiñán
Style Transfer by Rigid Alignment in Neural Net Feature Space. CoRR (2019)
Daniel A. Winkler, Robert Wang, François Blanchette, Miguel Á. Carreira-Perpiñán, Alberto E. Cerpa
DICTUM: Distributed Irrigation aCtuation with Turf hUmidity Modeling. ACM Trans. Sens. Networks 15 (4) (2019)
Elad Eban, Yair Movshovitz-Attias, Hao Wu, Mark Sandler, Andrew Poon, Yerlan Idelbayev, Miguel Á. Carreira-Perpiñán
Structured Multi-Hashing for Model Compression. CoRR (2019)
Miguel Á. Carreira-Perpiñán, Yerlan Idelbayev
"Learning-Compression" Algorithms for Neural Net Pruning. CVPR (2018)
Daniel A. Winkler, Miguel Á. Carreira-Perpiñán, Alberto E. Cerpa
Plug-and-play irrigation control at scale. IPSN (2018)
Miguel Á. Carreira-Perpiñán, Pooya Tavallali
Alternating optimization of decision trees, with application to learning sparse oblique trees. NeurIPS (2018)
Miguel Á. Carreira-Perpiñán, Yerlan Idelbayev
Model compression as constrained optimization, with application to neural nets. Part II: quantization. CoRR (2017)
Ramin Raziperchikolaei, Miguel Á. Carreira-Perpiñán
Learning circulant support vector machines for fast image search. ICIP (2017)
Miguel Á. Carreira-Perpiñán
Model compression as constrained optimization, with application to neural nets. Part I: general framework. CoRR (2017)
Max Vladymyrov, Miguel Á. Carreira-Perpiñán
Fast, accurate spectral clustering using locally linear landmarks. IJCNN (2017)
Ramin Raziperchikolaei, Miguel Á. Carreira-Perpiñán
Learning supervised binary hashing: Optimization vs diversity. ICIP (2017)
Daniel A. Winkler, Robert Wang, François Blanchette, Miguel Á. Carreira-Perpiñán, Alberto E. Cerpa
MAGIC: Model-Based Actuation for Ground Irrigation Control. IPSN (2016)
Miguel Á. Carreira-Perpiñán, Ramin Raziperchikolaei
An ensemble diversity approach to supervised binary hashing. NIPS (2016)
Ramin Raziperchikolaei, Miguel Á. Carreira-Perpiñán
Learning Independent, Diverse Binary Hash Functions: Pruning and Locality. ICDM (2016)
Miguel Á. Carreira-Perpiñán, Mehdi Alizadeh
ParMAC: distributed optimisation of nested functions, with application to learning binary autoencoders. CoRR (2016)
Miguel Á. Carreira-Perpiñán, Ramin Raziperchikolaei
An ensemble diversity approach to supervised binary hashing. CoRR (2016)
Ramin Raziperchikolaei, Miguel Á. Carreira-Perpiñán
Optimizing affinity-based binary hashing using auxiliary coordinates. NIPS (2016)
Max Vladymyrov, Miguel Á. Carreira-Perpiñán
The Variational Nystrom method for large-scale spectral problems. ICML (2016)
Daniel A. Winkler, Robert Wang, François Blanchette, Miguel Á. Carreira-Perpiñán, Alberto E. Cerpa
Poster: MICO: Model-Based Irrigation Control Optimization. SenSys (2015)
Miguel Á. Carreira-Perpiñán
A review of mean-shift algorithms for clustering. CoRR (2015)
Ramin Raziperchikolaei, Miguel Á. Carreira-Perpiñán
Learning hashing with affinity-based loss functions using auxiliary coordinates. CoRR (2015)
Miguel Á. Carreira-Perpiñán, Max Vladymyrov
A fast, universal algorithm to learn parametric nonlinear embeddings. NIPS (2015)
Miguel Á. Carreira-Perpiñán, Ramin Raziperchikolaei
Hashing with binary autoencoders. CVPR (2015)
Miguel Á. Carreira-Perpiñán, Ramin Raziperchikolaei
Hashing with binary autoencoders. CoRR (2015)
Weiran Wang, Miguel Á. Carreira-Perpiñán
The Laplacian K-modes algorithm for clustering. CoRR (2014)
Miguel Á. Carreira-Perpiñán, Weiran Wang
LASS: A Simple Assignment Model with Laplacian Smoothing. AAAI (2014)
Max Vladymyrov, Miguel Á. Carreira-Perpiñán
Linear-time training of nonlinear low-dimensional embeddings. AISTATS (2014)
Varick L. Erickson, Miguel Á. Carreira-Perpiñán, Alberto Cerpa
Occupancy Modeling and Prediction for Building Energy Management. ACM Trans. Sens. Networks 10 (3) (2014)
Miguel Á. Carreira-Perpiñán, Weiran Wang
LASS: a simple assignment model with Laplacian smoothing. CoRR (2014)
Miguel Á. Carreira-Perpiñán, Weiran Wang
Distributed optimization of deeply nested systems. AISTATS (2014)
Miguel Á. Carreira-Perpiñán
An ADMM algorithm for solving a proximal bound-constrained quadratic program. CoRR (2014)
Weiran Wang, Miguel Á. Carreira-Perpiñán
The role of dimensionality reduction in linear classification. CoRR (2014)
Weiran Wang, Miguel Á. Carreira-Perpiñán
The Role of Dimensionality Reduction in Classification. AAAI (2014)
Max Vladymyrov, Miguel Á. Carreira-Perpiñán
Locally Linear Landmarks for Large-Scale Manifold Learning. ECML/PKDD (3) (2013)
Ankur Kamthe, Miguel Á. Carreira-Perpiñán, Alberto Cerpa
Improving wireless link simulation using multilevel markov models. ACM Trans. Sens. Networks 10 (1) (2013)
Miguel Á. Carreira-Perpiñán, Weiran Wang
The K-modes algorithm for clustering CoRR (2013)
Ankur Kamthe, Miguel Á. Carreira-Perpiñán, Alberto Cerpa
Quick construction of data-driven models of the short-term behavior of wireless links. INFOCOM (2013)
Max Vladymyrov, Miguel Á. Carreira-Perpiñán
Entropic Affinities: Properties and Efficient Numerical Computation. ICML (3) (2013)
Weiran Wang, Miguel Á. Carreira-Perpiñán
Projection onto the probability simplex: An efficient algorithm with a simple proof, and an application. CoRR (2013)
Max Vladymyrov, Miguel Á. Carreira-Perpiñán
Partial-Hessian Strategies for Fast Learning of Nonlinear Embeddings CoRR (2012)
Max Vladymyrov, Miguel Á. Carreira-Perpiñán
Fast Training of Nonlinear Embedding Algorithms. ICML (2012)
Weiran Wang, Miguel Á. Carreira-Perpiñán
Nonlinear low-dimensional regression using auxiliary coordinates. AISTATS (2012)
Mohsen Farhadloo, Miguel Á. Carreira-Perpiñán
Learning and adaptation of a tongue shape modelwith missing data. ICASSP (2012)
Miguel Á. Carreira-Perpiñán, Weiran Wang
Distributed optimization of deeply nested systems CoRR (2012)
Mohsen Farhadloo, Miguel Á. Carreira-Perpiñán
Regularising an adaptation algorithm for tongue shape models. ICASSP (2012)
Miguel Á. Carreira-Perpiñán
Reconstruction of sequential data with density models CoRR (2011)
Weiran Wang, Miguel Á. Carreira-Perpiñán, Zhengdong Lu
A Denoising View of Matrix Completion. NIPS (2011)
Miguel Á. Carreira-Perpiñán, Zhengdong Lu
Manifold Learning and Missing Data Recovery through Unsupervised Regression. ICDM (2011)
Ankur Kamthe, Varick L. Erickson, Miguel Á. Carreira-Perpiñán, Alberto Cerpa
Enabling building energy auditing using adapted occupancy models. BuildSys@SenSys (2011)
Varick L. Erickson, Miguel Á. Carreira-Perpiñán, Alberto Cerpa
OBSERVE: Occupancy-based system for efficient reduction of HVAC energy. IPSN (2011)
Ankur Kamthe, Miguel Á. Carreira-Perpiñán, Alberto Cerpa
Adaptation of a Mixture of Multivariate Bernoulli Distributions. IJCAI (2011)
Miguel Á. Carreira-Perpiñán, Geoffrey J. Goodhill
Generalised elastic nets CoRR (2011)
Chao Qin, Miguel Á. Carreira-Perpiñán, Mohsen Farhadloo
Adaptation of a tongue shape model by local feature transformations. INTERSPEECH (2010)
Weiran Wang, Miguel Á. Carreira-Perpiñán
Manifold blurring mean shift algorithms for manifold denoising. CVPR (2010)
Miguel Á. Carreira-Perpiñán, Zhengdong Lu
Parametric dimensionality reduction by unsupervised regression. CVPR (2010)

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Publication Activity (10 Years)

Top Topics

Top Venues

Miguel Á. Carreira-Perpiñán