Dimensionality reduction of electropalatographic data using latent variable models. - Miguel Á. Carreira-Perpiñán; Steve Renals (Speech Commun., 1998)

Reconstruction of Sequential Data with Probabilistic Models and Continuity Constraints. - Miguel Á. Carreira-Perpiñán (NIPS, 1999)

Practical Identifiability of Finite Mixtures of Multivariate Bernoulli Distributions. - Miguel Á. Carreira-Perpiñán; Steve Renals (Neural Comput., 2000)

Mode-Finding for Mixtures of Gaussian Distributions. - Miguel Á. Carreira-Perpiñán (IEEE Trans. Pattern Anal. Mach. Intell., 2000)

Continuous latent variable models for dimensionality reduction and sequential data reconstruction. - Miguel Á. Carreira-Perpiñán (2001)

Are Visual Cortex Maps Optimized for Coverage? - Miguel Á. Carreira-Perpiñán; Geoffrey J. Goodhill (Neural Comput., 2002)

On the Number of Modes of a Gaussian Mixture. - Miguel Á. Carreira-Perpiñán; Christopher K. I. Williams (Scale-Space, 2003)

Multiscale Conditional Random Fields for Image Labeling. - Xuming He 001; Richard S. Zemel; Miguel Á. Carreira-Perpiñán (CVPR (2), 2004)

Proximity Graphs for Clustering and Manifold Learning. - Miguel Á. Carreira-Perpiñán; Richard S. Zemel (NIPS, 2004)

On Contrastive Divergence Learning. - Miguel Á. Carreira-Perpiñán; Geoffrey E. Hinton (AISTATS, 2005)

Differential Priors for Elastic Nets. - Miguel Á. Carreira-Perpiñán; Peter Dayan; Geoffrey J. Goodhill (IDEAL, 2005)

Acceleration Strategies for Gaussian Mean-Shift Image Segmentation. - Miguel Á. Carreira-Perpiñán (CVPR (1), 2006)

Kernel Density Estimation, Affinity-Based Clustering, And Typical Cuts. - Deniz Erdogmus; Miguel Á. Carreira-Perpiñán; Umut Ozertem (ICASSP (5), 2006)

Fast nonparametric clustering with Gaussian blurring mean-shift. - Miguel Á. Carreira-Perpiñán (ICML, 2006)

Non-rigid point set registration: Coherent Point Drift. - Andriy Myronenko; Xubo B. Song; Miguel Á. Carreira-Perpiñán (NIPS, 2006)

Free-Form Nonrigid Image Registration Using Generalized Elastic Nets. - Andriy Myronenko; Xubo B. Song; Miguel Á. Carreira-Perpiñán (CVPR, 2007)

An empirical investigation of the nonuniqueness in the acoustic-to-articulatory mapping. - Chao Qin; Miguel Á. Carreira-Perpiñán (INTERSPEECH, 2007)

A comparison of acoustic features for articulatory inversion. - Chao Qin; Miguel Á. Carreira-Perpiñán (INTERSPEECH, 2007)

People Tracking with the Laplacian Eigenmaps Latent Variable Model. - Zhengdong Lu; Miguel Á. Carreira-Perpiñán; Cristian Sminchisescu (NIPS, 2007)

The Laplacian Eigenmaps Latent Variable Model. - Miguel Á. Carreira-Perpiñán; Zhengdong Lu (AISTATS, 2007)

Gaussian Mean-Shift Is an EM Algorithm. - Miguel Á. Carreira-Perpiñán (IEEE Trans. Pattern Anal. Mach. Intell., 2007)

Generalised blurring mean-shift algorithms for nonparametric clustering. - Miguel Á. Carreira-Perpiñán (CVPR, 2008)

Dimensionality reduction by unsupervised regression. - Miguel Á. Carreira-Perpiñán; Zhengdong Lu (CVPR, 2008)

Constrained spectral clustering through affinity propagation. - Zhengdong Lu; Miguel Á. Carreira-Perpiñán (CVPR, 2008)

Density geodesics for similarity clustering. - Umut Ozertem; Deniz Erdogmus; Miguel Á. Carreira-Perpiñán (ICASSP, 2008)

Trajectory inverse kinematics by nonlinear, nongaussian tracking. - Chao Qin; Miguel Á. Carreira-Perpiñán (ICASSP, 2008)

IGlasses: an automatic wearable speech supplementin face-to-face communication and classroom situations. - Dominic W. Massaro; Miguel Á. Carreira-Perpiñán; David J. Merrill; Cass Sterling; Stephanie Bigler; Elise Piazza; Marcus Perlman (ICMI, 2008)

Trajectory inverse kinematics by conditional density modes. - Chao Qin; Miguel Á. Carreira-Perpiñán (ICRA, 2008)

Predicting tongue shapes from a few landmark locations. - Chao Qin; Miguel Á. Carreira-Perpiñán; Korin Richmond; Alan Wrench; Steve Renals (INTERSPEECH, 2008)

Optimizing Visual Feature Perception for an Automatic Wearable Speech Supplement in Face-to-Face Communication and Classroom Situations. - Dominic W. Massaro; Miguel Á. Carreira-Perpiñán; David J. Merrill (HICSS, 2009)

Adaptation of a predictive model of tongue shapes. - Chao Qin; Miguel Á. Carreira-Perpiñán (INTERSPEECH, 2009)

M&M: multi-level Markov model for wireless link simulations. - Ankur Kamthe; Miguel Á. Carreira-Perpiñán; Alberto Cerpa (SenSys, 2009)

Wireless link simulations using multi-level Markov models. - Ankur Kamthe; Miguel Á. Carreira-Perpiñán; Alberto Cerpa (SenSys, 2009)

Parametric dimensionality reduction by unsupervised regression. - Miguel Á. Carreira-Perpiñán; Zhengdong Lu (CVPR, 2010)

Manifold blurring mean shift algorithms for manifold denoising. - Weiran Wang; Miguel Á. Carreira-Perpiñán (CVPR, 2010)

Reconstructing the full tongue contour from EMA/X-ray microbeam. - Chao Qin; Miguel Á. Carreira-Perpiñán (ICASSP, 2010)

Semi-supervised regression with temporal image sequences. - Ling Xie; Miguel Á. Carreira-Perpiñán; Shawn D. Newsam (ICIP, 2010)

The Elastic Embedding Algorithm for Dimensionality Reduction. - Miguel Á. Carreira-Perpiñán (ICML, 2010)

Estimating missing data sequences in x-ray microbeam recordings. - Chao Qin; Miguel Á. Carreira-Perpiñán (INTERSPEECH, 2010)

Articulatory inversion of american English /turnr/ by conditional density modes. - Chao Qin; Miguel Á. Carreira-Perpiñán (INTERSPEECH, 2010)

Adaptation of a tongue shape model by local feature transformations. - Chao Qin; Miguel Á. Carreira-Perpiñán; Mohsen Farhadloo (INTERSPEECH, 2010)

Manifold Learning and Missing Data Recovery through Unsupervised Regression. - Miguel Á. Carreira-Perpiñán; Zhengdong Lu (ICDM, 2011)

Adaptation of a Mixture of Multivariate Bernoulli Distributions. - Ankur Kamthe; Miguel Á. Carreira-Perpiñán; Alberto Cerpa (IJCAI, 2011)

OBSERVE: Occupancy-based system for efficient reduction of HVAC energy. - Varick L. Erickson; Miguel Á. Carreira-Perpiñán; Alberto Cerpa (IPSN, 2011)

A Denoising View of Matrix Completion. - Weiran Wang; Miguel Á. Carreira-Perpiñán; Zhengdong Lu (NIPS, 2011)

Enabling building energy auditing using adapted occupancy models. - Ankur Kamthe; Varick L. Erickson; Miguel Á. Carreira-Perpiñán; Alberto Cerpa (BuildSys@SenSys, 2011)

Generalised elastic nets - Miguel Á. Carreira-Perpiñán; Geoffrey J. Goodhill (CoRR, 2011)

Reconstruction of sequential data with density models - Miguel Á. Carreira-Perpiñán (CoRR, 2011)

Learning and adaptation of a tongue shape modelwith missing data. - Mohsen Farhadloo; Miguel Á. Carreira-Perpiñán (ICASSP, 2012)

Regularising an adaptation algorithm for tongue shape models. - Mohsen Farhadloo; Miguel Á. Carreira-Perpiñán (ICASSP, 2012)

Fast Training of Nonlinear Embedding Algorithms. - Max Vladymyrov; Miguel Á. Carreira-Perpiñán (ICML, 2012)

Partial-Hessian Strategies for Fast Learning of Nonlinear Embeddings - Max Vladymyrov; Miguel Á. Carreira-Perpiñán (CoRR, 2012)

Nonlinear low-dimensional regression using auxiliary coordinates. - Weiran Wang; Miguel Á. Carreira-Perpiñán (AISTATS, 2012)

Entropic Affinities: Properties and Efficient Numerical Computation. - Max Vladymyrov; Miguel Á. Carreira-Perpiñán (ICML (3), 2013)

Quick construction of data-driven models of the short-term behavior of wireless links. - Ankur Kamthe; Miguel Á. Carreira-Perpiñán; Alberto Cerpa (INFOCOM, 2013)

Locally Linear Landmarks for Large-Scale Manifold Learning. - Max Vladymyrov; Miguel Á. Carreira-Perpiñán (ECML/PKDD (3), 2013)

Projection onto the probability simplex: An efficient algorithm with a simple proof, and an application. - Weiran Wang; Miguel Á. Carreira-Perpiñán (CoRR, 2013)

The K-modes algorithm for clustering - Miguel Á. Carreira-Perpiñán; Weiran Wang (CoRR, 2013)

Improving wireless link simulation using multilevel markov models. - Ankur Kamthe; Miguel Á. Carreira-Perpiñán; Alberto Cerpa (ACM Trans. Sens. Networks, 2013)

LASS: A Simple Assignment Model with Laplacian Smoothing. - Miguel Á. Carreira-Perpiñán; Weiran Wang (AAAI, 2014)

The Role of Dimensionality Reduction in Classification. - Weiran Wang; Miguel Á. Carreira-Perpiñán (AAAI, 2014)

Distributed optimization of deeply nested systems. - Miguel Á. Carreira-Perpiñán; Weiran Wang (AISTATS, 2014)

Linear-time training of nonlinear low-dimensional embeddings. - Max Vladymyrov; Miguel Á. Carreira-Perpiñán (AISTATS, 2014)

An ADMM algorithm for solving a proximal bound-constrained quadratic program. - Miguel Á. Carreira-Perpiñán (CoRR, 2014)

The role of dimensionality reduction in linear classification. - Weiran Wang; Miguel Á. Carreira-Perpiñán (CoRR, 2014)

The Laplacian K-modes algorithm for clustering. - Weiran Wang; Miguel Á. Carreira-Perpiñán (CoRR, 2014)

Occupancy Modeling and Prediction for Building Energy Management. - Varick L. Erickson; Miguel Á. Carreira-Perpiñán; Alberto Cerpa (ACM Trans. Sens. Networks, 2014)

Hashing with binary autoencoders. - Miguel Á. Carreira-Perpiñán; Ramin Raziperchikolaei (CVPR, 2015)

A fast, universal algorithm to learn parametric nonlinear embeddings. - Miguel Á. Carreira-Perpiñán; Max Vladymyrov (NIPS, 2015)

Poster: MICO: Model-Based Irrigation Control Optimization. - Daniel A. Winkler; Robert Wang 003; François Blanchette; Miguel Á. Carreira-Perpiñán; Alberto E. Cerpa (SenSys, 2015)

A review of mean-shift algorithms for clustering. - Miguel Á. Carreira-Perpiñán (CoRR, 2015)

Learning hashing with affinity-based loss functions using auxiliary coordinates. - Ramin Raziperchikolaei; Miguel Á. Carreira-Perpiñán (CoRR, 2015)

Learning Independent, Diverse Binary Hash Functions: Pruning and Locality. - Ramin Raziperchikolaei; Miguel Á. Carreira-Perpiñán (ICDM, 2016)

The Variational Nystrom method for large-scale spectral problems. - Max Vladymyrov; Miguel Á. Carreira-Perpiñán (ICML, 2016)

MAGIC: Model-Based Actuation for Ground Irrigation Control. - Daniel A. Winkler; Robert Wang 003; François Blanchette; Miguel Á. Carreira-Perpiñán; Alberto E. Cerpa (IPSN, 2016)

An ensemble diversity approach to supervised binary hashing. - Miguel Á. Carreira-Perpiñán; Ramin Raziperchikolaei (NIPS, 2016)

Optimizing affinity-based binary hashing using auxiliary coordinates. - Ramin Raziperchikolaei; Miguel Á. Carreira-Perpiñán (NIPS, 2016)

Learning circulant support vector machines for fast image search. - Ramin Raziperchikolaei; Miguel Á. Carreira-Perpiñán (ICIP, 2017)

Learning supervised binary hashing: Optimization vs diversity. - Ramin Raziperchikolaei; Miguel Á. Carreira-Perpiñán (ICIP, 2017)

Fast, accurate spectral clustering using locally linear landmarks. - Max Vladymyrov; Miguel Á. Carreira-Perpiñán (IJCNN, 2017)

Model compression as constrained optimization, with application to neural nets. Part I: general framework. - Miguel Á. Carreira-Perpiñán (CoRR, 2017)

Model compression as constrained optimization, with application to neural nets. Part II: quantization. - Miguel Á. Carreira-Perpiñán; Yerlan Idelbayev (CoRR, 2017)

"Learning-Compression" Algorithms for Neural Net Pruning. - Miguel Á. Carreira-Perpiñán; Yerlan Idelbayev (CVPR, 2018)

Plug-and-play irrigation control at scale. - Daniel A. Winkler; Miguel Á. Carreira-Perpiñán; Alberto E. Cerpa (IPSN, 2018)

Alternating optimization of decision trees, with application to learning sparse oblique trees. - Miguel Á. Carreira-Perpiñán; Pooya Tavallali (NeurIPS, 2018)

Parmac: Distributed Optimisation Of Nested Functions, With Application To Learning Binary Autoencoders. - Miguel Á. Carreira-Perpiñán; Mehdi Alizadeh (SysML, 2019)

Sampling the "Inverse Set" of a Neuron: An Approach to Understanding Neural Nets. - Suryabhan Singh Hada; Miguel Á. Carreira-Perpiñán (CoRR, 2019)

An Experimental Comparison of Old and New Decision Tree Algorithms. - Arman Zharmagambetov; Suryabhan Singh Hada; Miguel Á. Carreira-Perpiñán (CoRR, 2019)

DICTUM: Distributed Irrigation aCtuation with Turf hUmidity Modeling. - Daniel A. Winkler; Robert Wang 003; François Blanchette; Miguel Á. Carreira-Perpiñán; Alberto E. Cerpa (ACM Trans. Sens. Networks, 2019)

Structured Multi-Hashing for Model Compression. - Elad Eban; Yair Movshovitz-Attias; Hao Wu; Mark Sandler 002; Andrew Poon; Yerlan Idelbayev; Miguel Á. Carreira-Perpiñán (CVPR, 2020)

Low-Rank Compression of Neural Nets: Learning the Rank of Each Layer. - Yerlan Idelbayev; Miguel Á. Carreira-Perpiñán (CVPR, 2020)

Ensembles of Bagged TAO Trees Consistently Improve over Random Forests, AdaBoost and Gradient Boosting. - Miguel Á. Carreira-Perpiñán; Arman Zharmagambetov (FODS, 2020)

Smaller, more accurate regression forests using tree alternating optimization. - Arman Zharmagambetov; Miguel Á. Carreira-Perpiñán (ICML, 2020)

A flexible, extensible software framework for model compression based on the LC algorithm. - Yerlan Idelbayev; Miguel Á. Carreira-Perpiñán (CoRR, 2020)

OPTICS: OPTimizing Irrigation Control at Scale. - Daniel A. Winkler; Miguel Á. Carreira-Perpiñán; Alberto E. Cerpa (ACM Trans. Sens. Networks, 2020)

Counterfactual Explanations for Oblique Decision Trees: Exact, Efficient Algorithms. - Miguel Á. Carreira-Perpiñán; Suryabhan Singh Hada (AAAI, 2021)

LC: A Flexible, Extensible Open-Source Toolkit for Model Compression. - Yerlan Idelbayev; Miguel Á. Carreira-Perpiñán (CIKM, 2021)

Optimal Quantization Using Scaled Codebook. - Yerlan Idelbayev; Pavlo Molchanov 001; Maying Shen; Hongxu Yin; Miguel Á. Carreira-Perpiñán; José M. Álvarez 004 (CVPR, 2021)

Neural Network Compression via Additive Combination of Reshaped, Low-Rank Matrices. - Yerlan Idelbayev; Miguel Á. Carreira-Perpiñán (DCC, 2021)

Softmax Tree: An Accurate, Fast Classifier When the Number of Classes Is Large. - Arman Zharmagambetov; Magzhan Gabidolla; Miguel Á. Carreira-Perpiñán (EMNLP (1), 2021)

Optimal Selection of Matrix Shape and Decomposition Scheme for Neural Network Compression. - Yerlan Idelbayev; Miguel Á. Carreira-Perpiñán (ICASSP, 2021)

Learning a Tree of Neural Nets. - Arman Zharmagambetov; Miguel Á. Carreira-Perpiñán (ICASSP, 2021)

Sampling The "Inverse Set" of a Neuron. - Suryabhan Singh Hada; Miguel Á. Carreira-Perpiñán (ICIP, 2021)

Understanding And Manipulating Neural Net Features Using Sparse Oblique Classification Trees. - Suryabhan Singh Hada; Miguel Á. Carreira-Perpiñán; Arman Zharmagambetov (ICIP, 2021)

Beyond Flops In Low-Rank Compression Of Neural Networks: Optimizing Device-Specific Inference Runtime. - Yerlan Idelbayev; Miguel Á. Carreira-Perpiñán (ICIP, 2021)

A Simple, Effective Way To Improve Neural Net Classification: Ensembling Unit Activations With A Sparse Oblique Decision Tree. - Arman Zharmagambetov; Miguel Á. Carreira-Perpiñán (ICIP, 2021)

Improved Multiclass Adaboost For Image Classification: The Role Of Tree Optimization. - Arman Zharmagambetov; Magzhan Gabidolla; Miguel Á. Carreira-Perpiñán (ICIP, 2021)

An Empirical Comparison of Quantization, Pruning and Low-rank Neural Network Compression using the LC Toolkit. - Yerlan Idelbayev; Miguel Á. Carreira-Perpiñán (IJCNN, 2021)

Improved Boosted Regression Forests Through Non-Greedy Tree Optimization. - Arman Zharmagambetov; Magzhan Gabidolla; Miguel Á. Carreira-Perpiñán (IJCNN, 2021)

Non-Greedy Algorithms for Decision Tree Optimization: An Experimental Comparison. - Arman Zharmagambetov; Suryabhan Singh Hada; Magzhan Gabidolla; Miguel Á. Carreira-Perpiñán (IJCNN, 2021)

Exploring Counterfactual Explanations for Classification and Regression Trees. - Suryabhan Singh Hada; Miguel Á. Carreira-Perpiñán (PKDD/ECML Workshops (1), 2021)

More General and Effective Model Compression via an Additive Combination of Compressions. - Yerlan Idelbayev; Miguel Á. Carreira-Perpiñán (ECML/PKDD (3), 2021)

Style Transfer by Rigid Alignment in Neural Net Feature Space. - Suryabhan Singh Hada; Miguel Á. Carreira-Perpiñán (WACV, 2021)

Model compression as constrained optimization, with application to neural nets. Part V: combining compressions. - Miguel Á. Carreira-Perpiñán; Yerlan Idelbayev (CoRR, 2021)

Learning Interpretable, Tree-Based Projection Mappings for Nonlinear Embeddings. - Arman Serikuly Zharmagambetov; Miguel Á. Carreira-Perpiñán (AISTATS, 2022)

Pushing the Envelope of Gradient Boosting Forests via Globally-Optimized Oblique Trees. - Magzhan Gabidolla; Miguel Á. Carreira-Perpiñán (CVPR, 2022)

Interpretable Image Classification Using Sparse Oblique Decision Trees. - Suryabhan Singh Hada; Miguel Á. Carreira-Perpiñán (ICASSP, 2022)

Exploring the Effect of ℓ0/ℓ2 Regularization in Neural Network Pruning using the LC Toolkit. - Yerlan Idelbayev; Miguel Á. Carreira-Perpiñán (ICASSP, 2022)

Improved Multiclass AdaBoost Using Sparse Oblique Decision Trees. - Magzhan Gabidolla; Arman Zharmagambetov; Miguel Á. Carreira-Perpiñán (IJCNN, 2022)

Sparse Oblique Decision Trees: A Tool to Interpret Natural Language Processing Datasets. - Suryabhan Singh Hada; Miguel Á. Carreira-Perpiñán (IJCNN, 2022)

Optimal Interpretable Clustering Using Oblique Decision Trees. - Magzhan Gabidolla; Miguel Á. Carreira-Perpiñán (KDD, 2022)

Semi-Supervised Learning with Decision Trees: Graph Laplacian Tree Alternating Optimization. - Arman Zharmagambetov; Miguel Á. Carreira-Perpiñán (NeurIPS, 2022)

Very Fast, Approximate Counterfactual Explanations for Decision Forests. - Miguel Á. Carreira-Perpiñán; Suryabhan Singh Hada (AAAI, 2023)

Towards Better Decision Forests: Forest Alternating Optimization. - Miguel Á. Carreira-Perpiñán; Magzhan Gabidolla; Arman Zharmagambetov (CVPR, 2023)

Solving Recurrence Relations using Machine Learning, with Application to Cost Analysis. - Maximiliano Klemen; Miguel Á. Carreira-Perpiñán; Pedro López-García 001 (ICLP, 2023)

Inverse classification with logistic and softmax classifiers: efficient optimization. - Miguel Á. Carreira-Perpiñán; Suryabhan Singh Hada (CoRR, 2023)

Beyond the ROC Curve: Classification Trees Using Cost-Optimal Curves, with Application to Imbalanced Datasets. - Magzhan Gabidolla; Arman Zharmagambetov; Miguel Á. Carreira-Perpiñán (ICML, 2024)

Bivariate Decision Trees: Smaller, Interpretable, More Accurate. - Rasul Kairgeldin; Miguel Á. Carreira-Perpiñán (KDD, 2024)

The tree autoencoder model, with application to hierarchical data visualization. - Miguel Á. Carreira-Perpiñán; Kuat Gazizov (NeurIPS, 2024)

Adaptive Softmax Trees for Many-Class Classification. - Rasul Kairgeldin; Magzhan Gabidolla; Miguel Á. Carreira-Perpiñán (UAI, 2024)

MARS: Multi-radio Architecture with Radio Selection using Decision Trees for emerging mesoscale CPS/IoT applications. - Jothi Prasanna Shanmuga Sundaram; Arman Zharmagambetov; Magzhan Gabidolla; Miguel Á. Carreira-Perpiñán; Alberto Cerpa (CoRR, 2024)

A Machine Learning-Based Approach for Solving Recurrence Relations and Its use in Cost Analysis of Logic Programs. - Louis Rustenholz; Maximiliano Klemen; Miguel Á. Carreira-Perpiñán; Pedro López-García 001 (Theory Pract. Log. Program., 2024)

Sparse oblique decision trees: a tool to understand and manipulate neural net features. - Suryabhan Singh Hada; Miguel Á. Carreira-Perpiñán; Arman Zharmagambetov (Data Min. Knowl. Discov., 2024)

COMNETS: COst-sensitive decision trees approach to throughput optimization for Multi-radio IoT NETworkS. - Jothi Prasanna Shanmuga Sundaram; Magzhan Gabidolla; Miguel Á. Carreira-Perpiñán; Alberto E. Cerpa (CoRR, 2025)