Miguel Á. Carreira-Perpiñán

发表

Trajectory inverse kinematics by conditional density modes

Chao Qin, Miguel Á. Carreira-Perpiñán, M. A. Carreira-Perpiñán, 2008, 2008 IEEE International Conference on Robotics and Automation.

The Elastic Embedding Algorithm for Dimensionality Reduction

Miguel Á. Carreira-Perpiñán, M. A. Carreira-Perpiñán, 2010, ICML.

Semi-supervised regression with temporal image sequences

Miguel Á. Carreira-Perpiñán, Shawn D. Newsam, Ling Xie, 2010, 2010 IEEE International Conference on Image Processing.

The role of dimensionality reduction in linear classification pdf

Miguel Á. Carreira-Perpiñán, Weiran Wang, 2014, ArXiv.

Learning circulant support vector machines for fast image search

Miguel Á. Carreira-Perpiñán, Ramin Raziperchikolaei, 2017, 2017 IEEE International Conference on Image Processing (ICIP).

Poster: MICO: Model-Based Irrigation Control Optimization

Miguel Á. Carreira-Perpiñán, Alberto Cerpa, Daniel A. Winkler, 2015, SenSys.

Mode-Finding for Mixtures of Gaussian Distributions

Miguel Á. Carreira-Perpiñán, M. A. Carreira-Perpiñán, 2000, IEEE Trans. Pattern Anal. Mach. Intell..

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

Miguel Á. Carreira-Perpiñán, Mehdi Alizadeh, M. A. Carreira-Perpiñán, 2017 .

A review of mean-shift algorithms for clustering pdf

Miguel Á. Carreira-Perpiñán, M. A. Carreira-Perpiñán, 2015, ArXiv.

The Laplacian K-modes algorithm for clustering pdf

Miguel Á. Carreira-Perpiñán, Weiran Wang, M. A. Carreira-Perpiñán, 2014, ArXiv.

Estimating missing data sequences in x-ray microbeam recordings

Miguel Á. Carreira-Perpiñán, Chao Qin, 2010, INTERSPEECH.

Generalised blurring mean-shift algorithms for nonparametric clustering

Miguel Á. Carreira-Perpiñán, M. A. Carreira-Perpiñán, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

LASS: A Simple Assignment Model with Laplacian Smoothing pdf

Miguel Á. Carreira-Perpiñán, Weiran Wang, M. A. Carreira-Perpiñán, 2014, AAAI.

Dimensionality reduction of electropalatographic data using latent variable models

Miguel Á. Carreira-Perpiñán, Steve Renals, M. A. Carreira-Perpiñán, 1998, Speech Commun..

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

Miguel Á. Carreira-Perpiñán, Alberto Cerpa, Varick L. Erickson, 2011, Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks.

Style Transfer by Rigid Alignment in Neural Net Feature Space pdf

Miguel Á. Carreira-Perpiñán, Suryabhan Singh Hada, 2019, ArXiv.

Optimizing Visual Feature Perception for an Automatic Wearable Speech Supplement in Face-to-Face Communication and Classroom Situations

Miguel Á. Carreira-Perpiñán, Dominic W. Massaro, David J. Merrill, 2009, 2009 42nd Hawaii International Conference on System Sciences.

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

Miguel Á. Carreira-Perpiñán, Yerlan Idelbayev, M. A. Carreira-Perpiñán, 2017, ArXiv.

Optimizing affinity-based binary hashing using auxiliary coordinates

Miguel Á. Carreira-Perpiñán, Ramin Raziperchikolaei, 2016, NIPS.

A comparison of acoustic features for articulatory inversion

Miguel Á. Carreira-Perpiñán, Chao Qin, M. A. Carreira-Perpiñán, 2007, INTERSPEECH.

MAGIC: Model-Based Actuation for Ground Irrigation Control

Miguel Á. Carreira-Perpiñán, Alberto Cerpa, Daniel A. Winkler, 2016, 2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN).

Fast Training of Nonlinear Embedding Algorithms

Miguel Á. Carreira-Perpiñán, Max Vladymyrov, M. A. Carreira-Perpiñán, 2012, ICML.

Kernel Density Estimation, Affinity-Based Clustering, And Typical Cuts

Miguel Á. Carreira-Perpiñán, Deniz Erdogmus, Umut Ozertem, 2006, 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings.

Entropic Affinities: Properties and Efficient Numerical Computation

Miguel Á. Carreira-Perpiñán, Max Vladymyrov, M. A. Carreira-Perpiñán, 2013, ICML.

Reconstruction of sequential data with density models pdf

Miguel Á. Carreira-Perpiñán, M. A. Carreira-Perpiñán, 2011, ArXiv.

Multiscale conditional random fields for image labeling

Miguel Á. Carreira-Perpiñán, Richard S. Zemel, Xuming He, 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

Regularising an adaptation algorithm for tongue shape models

Miguel Á. Carreira-Perpiñán, Mohsen Farhadloo, 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Joint optimization of mapping and classifier using auxiliary coordinates

Miguel Á. Carreira-Perpiñán, Weiran Wang, M. A. Carreira-Perpiñán, 2014 .

Non-rigid point set registration: Coherent Point Drift

Miguel Á. Carreira-Perpiñán, Andriy Myronenko, Xubo B. Song, 2006, NIPS.

Smaller, more accurate regression forests using tree alternating optimization

Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov, M. A. Carreira-Perpiñán, 2020, ICML.

Alternating optimization of decision trees, with application to learning sparse oblique trees

Miguel Á. Carreira-Perpiñán, Pooya Tavallali, M. A. Carreira-Perpiñán, 2018, NeurIPS.

Trajectory inverse kinematics by nonlinear, nongaussian tracking

Chao Qin, Miguel Á. Carreira-Perpiñán, M. A. Carreira-Perpiñán, 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

On the Number of Modes of a Gaussian Mixture

Miguel Á. Carreira-Perpiñán, Christopher K. I. Williams, M. A. Carreira-Perpiñán, 2003, Scale-Space.

Continuous latent variable models for dimensionality reduction and sequential data reconstruction

Miguel Á. Carreira-Perpiñán, M. A. Carreira-Perpiñán, 2001 .

Quick construction of data-driven models of the short-term behavior of wireless links

Miguel Á. Carreira-Perpiñán, Alberto Cerpa, Ankur Kamthe, 2013, 2013 Proceedings IEEE INFOCOM.

People Tracking with the Laplacian Eigenmaps Latent Variable Model

Miguel Á. Carreira-Perpiñán, Cristian Sminchisescu, Zhengdong Lu, 2007, NIPS.

Distributed optimization of deeply nested systems pdf

Miguel Á. Carreira-Perpiñán, Weiran Wang, M. A. Carreira-Perpiñán, 2012, AISTATS.

Learning Independent, Diverse Binary Hash Functions: Pruning and Locality

Miguel Á. Carreira-Perpiñán, Ramin Raziperchikolaei, 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).

Proximity Graphs for Clustering and Manifold Learning

Miguel Á. Carreira-Perpiñán, Richard S. Zemel, R. Zemel, 2004, NIPS.

Wireless link simulations using multi-level Markov models

Miguel Á. Carreira-Perpiñán, Alberto Cerpa, Ankur Kamthe, 2009, SenSys '09.

Improving wireless link simulation using multilevel markov models

Miguel Á. Carreira-Perpiñán, Alberto Cerpa, Ankur Kamthe, 2013, ACM Trans. Sens. Networks.

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

Miguel Á. Carreira-Perpiñán, Weiran Wang, M. A. Carreira-Perpiñán, 2013, ArXiv.

Fast nonparametric clustering with Gaussian blurring mean-shift

Miguel Á. Carreira-Perpiñán, M. A. Carreira-Perpiñán, 2006, ICML.

Learning hashing with affinity-based loss functions using auxiliary coordinates pdf

Miguel Á. Carreira-Perpiñán, Ramin Raziperchikolaei, 2015, ArXiv.

Manifold Learning and Missing Data Recovery through Unsupervised Regression

Miguel Á. Carreira-Perpiñán, Zhengdong Lu, M. A. Carreira-Perpiñán, 2011, 2011 IEEE 11th International Conference on Data Mining.

Reconstruction of Sequential Data with Probabilistic Models and Continuity Constraints

Miguel Á. Carreira-Perpiñán, M. A. Carreira-Perpiñán, 1999, NIPS.

IGlasses: an automatic wearable speech supplementin face-to-face communication and classroom situations

Miguel Á. Carreira-Perpiñán, Dominic W. Massaro, Marcus Perlman, 2008, ICMI '08.

Parametric dimensionality reduction by unsupervised regression

Miguel Á. Carreira-Perpiñán, Zhengdong Lu, M. A. Carreira-Perpiñán, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Reconstructing the full tongue contour from EMA/X-ray microbeam

Miguel Á. Carreira-Perpiñán, Chao Qin, M. A. Carreira-Perpiñán, 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.

Enabling building energy auditing using adapted occupancy models

Miguel Á. Carreira-Perpiñán, Alberto Cerpa, Ankur Kamthe, 2011, BuildSys '11.

M&M: multi-level Markov model for wireless link simulations

Miguel Á. Carreira-Perpiñán, Alberto Cerpa, Ankur Kamthe, 2009, SenSys '09.

Predicting tongue shapes from a few landmark locations

Miguel Á. Carreira-Perpiñán, Steve Renals, Alan Wrench, 2008, INTERSPEECH.

Manifold blurring mean shift algorithms for manifold denoising

Miguel Á. Carreira-Perpiñán, Weiran Wang, M. A. Carreira-Perpiñán, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Constrained spectral clustering through affinity propagation

Miguel Á. Carreira-Perpiñán, Zhengdong Lu, M. A. Carreira-Perpiñán, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

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

Miguel Á. Carreira-Perpiñán, Mehdi Alizadeh, M. A. Carreira-Perpiñán, 2016, MLSys.

Adaptation of a tongue shape model by local feature transformations

Miguel Á. Carreira-Perpiñán, Chao Qin, Mohsen Farhadloo, 2010, INTERSPEECH.

"Learning-Compression" Algorithms for Neural Net Pruning

Miguel Á. Carreira-Perpiñán, Yerlan Idelbayev, M. A. Carreira-Perpiñán, 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

An empirical investigation of the nonuniqueness in the acoustic-to-articulatory mapping

Miguel Á. Carreira-Perpiñán, Chao Qin, M. A. Carreira-Perpiñán, 2007, Interspeech.

Adaptation of a predictive model of tongue shapes

Miguel Á. Carreira-Perpiñán, Chao Qin, 2009, INTERSPEECH.

Dimensionality reduction by unsupervised regression

Miguel Á. Carreira-Perpiñán, Zhengdong Lu, M. A. Carreira-Perpiñán, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

Scale Space Methods in Computer Vision

Miguel Á. Carreira-Perpiñán, Christopher K. I. Williams, M. A. Carreira-Perpiñán, 2003 .

Articulatory inversion of american English /turnr/ by conditional density modes

Miguel Á. Carreira-Perpiñán, Chao Qin, M. A. Carreira-Perpiñán, 2010, INTERSPEECH.

Learning and adaptation of a tongue shape modelwith missing data

Miguel Á. Carreira-Perpiñán, Mohsen Farhadloo, 2012, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Occupancy Modeling and Prediction for Building Energy Management

Miguel Á. Carreira-Perpiñán, Alberto E. Cerpa, Varick L. Erickson, 2014, ACM Trans. Sens. Networks.

Gaussian Mean-Shift Is an EM Algorithm

Miguel Á. Carreira-Perpiñán, M. A. Carreira-Perpiñán, 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

DICTUM: Distributed Irrigation aCtuation with Turf hUmidity Modeling

Miguel Á. Carreira-Perpiñán, Alberto E. Cerpa, Daniel A. Winkler, 2019, ACM Trans. Sens. Networks.

Generalised elastic nets pdf

Miguel Á. Carreira-Perpiñán, Geoffrey J. Goodhill, M. A. Carreira-Perpiñán, 2011, ArXiv.

A latent-variable modelling approach to the acoustic-to-articulatory mapping problem. I

Miguel Á. Carreira-Perpiñán, Steve Á. Renals, 1999 .

A Review of Dimension Reduction Techniques

Miguel Á. Carreira-Perpiñán, M. A. Carreira-Perpiñán, 2009 .

Practical Identifiability of Finite Mixtures of Multivariate Bernoulli Distributions

Miguel Á. Carreira-Perpiñán, Steve Renals, M. A. Carreira-Perpiñán, 2000, Neural Computation.

Sampling the "Inverse Set" of a Neuron: An Approach to Understanding Neural Nets pdf

Miguel Á. Carreira-Perpiñán, Suryabhan Singh Hada, 2019, ArXiv.

A fast, universal algorithm to learn parametric nonlinear embeddings

Miguel Á. Carreira-Perpiñán, Max Vladymyrov, 2015, NIPS.

The Variational Nystrom method for large-scale spectral problems

Miguel Á. Carreira-Perpiñán, Max Vladymyrov, M. A. Carreira-Perpiñán, 2016, ICML.

On Contrastive Divergence Learning

Miguel Á. Carreira-Perpiñán, Geoffrey E. Hinton, M. A. Carreira-Perpiñán, 2005, AISTATS.

Density geodesics for similarity clustering

Miguel Á. Carreira-Perpiñán, Deniz Erdogmus, Umut Ozertem, 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

Model compression as constrained optimization, with application to neural nets. Part I: general framework pdf

Miguel Á. Carreira-Perpiñán, M. A. Carreira-Perpiñán, 2017, ArXiv.

Learning supervised binary hashing: Optimization vs diversity

Miguel Á. Carreira-Perpiñán, Ramin Raziperchikolaei, M. A. Carreira-Perpiñán, 2017, 2017 IEEE International Conference on Image Processing (ICIP).

Nonlinear low-dimensional regression using auxiliary coordinates

Miguel Á. Carreira-Perpiñán, Weiran Wang, M. A. Carreira-Perpiñán, 2012, AISTATS.

Linear-time training of nonlinear low-dimensional embeddings

Miguel Á. Carreira-Perpiñán, Max Vladymyrov, M. A. Carreira-Perpiñán, 2014, AISTATS.

A Denoising View of Matrix Completion

Miguel Á. Carreira-Perpiñán, Zhengdong Lu, Weiran Wang, 2011, NIPS.

Locally Linear Landmarks for Large-Scale Manifold Learning

Miguel Á. Carreira-Perpiñán, Max Vladymyrov, M. A. Carreira-Perpiñán, 2013, ECML/PKDD.

Hashing with binary autoencoders

Miguel Á. Carreira-Perpiñán, Ramin Raziperchikolaei, M. A. Carreira-Perpiñán, 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

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

Miguel Á. Carreira-Perpiñán, 2014, ArXiv.

Differential Priors for Elastic Nets

Miguel Á. Carreira-Perpiñán, Peter Dayan, Geoffrey J. Goodhill, 2005, IDEAL.

The Laplacian Eigenmaps Latent Variable Model

Miguel Á. Carreira-Perpiñán, Zhengdong Lu, M. A. Carreira-Perpiñán, 2007, AISTATS.

Plug-and-Play Irrigation Control at Scale

Miguel Á. Carreira-Perpiñán, Alberto Cerpa, Daniel A. Winkler, 2018, 2018 17th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN).

Acceleration Strategies for Gaussian Mean-Shift Image Segmentation

Miguel Á. Carreira-Perpiñán, 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

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

Miguel Á. Carreira-Perpiñán, Yerlan Idelbayev, M. A. Carreira-Perpiñán, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Ensembles of Bagged TAO Trees Consistently Improve over Random Forests, AdaBoost and Gradient Boosting

Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov, M. A. Carreira-Perpiñán, 2020, FODS.

Fast, accurate spectral clustering using locally linear landmarks

Miguel Á. Carreira-Perpiñán, Max Vladymyrov, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Are Visual Cortex Maps Optimized for Coverage?

Miguel Á. Carreira-Perpiñán, Geoffrey J. Goodhill, 2002, Neural Computation.

The K-modes algorithm for clustering pdf

Miguel Á. Carreira-Perpiñán, Weiran Wang, M. A. Carreira-Perpiñán, 2013, ArXiv.

Adaptation of a Mixture of Multivariate Bernoulli Distributions

Miguel Á. Carreira-Perpiñán, Alberto Cerpa, Ankur Kamthe, 2011, IJCAI.

Free-Form Nonrigid Image Registration Using Generalized Elastic Nets

Miguel Á. Carreira-Perpiñán, Andriy Myronenko, Xubo B. Song, 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

An ensemble diversity approach to supervised binary hashing

Miguel Á. Carreira-Perpiñán, Ramin Raziperchikolaei, M. A. Carreira-Perpiñán, 2016, NIPS.

A Simple, Effective Way To Improve Neural Net Classification: Ensembling Unit Activations With A Sparse Oblique Decision Tree

Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov, 2021, ICIP 2021.

More General and Effective Model Compression via an Additive Combination of Compressions

Miguel Á. Carreira-Perpiñán, Yerlan Idelbayev, M. A. Carreira-Perpiñán, 2021, ECML/PKDD.

Non-Greedy Algorithms for Decision Tree Optimization: An Experimental Comparison

Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov, Suryabhan Singh Hada, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

Neural Network Compression via Additive Combination of Reshaped, Low-Rank Matrices

Miguel Á. Carreira-Perpiñán, Yerlan Idelbayev, M. A. Carreira-Perpiñán, 2021, 2021 Data Compression Conference (DCC).

LC: A Flexible, Extensible Open-Source Toolkit for Model Compression

Miguel Á. Carreira-Perpiñán, Yerlan Idelbayev, M. A. Carreira-Perpiñán, 2021, International Conference on Information and Knowledge Management.

Optimal Selection of Matrix Shape and Decomposition Scheme for Neural Network Compression

Miguel Á. Carreira-Perpiñán, Yerlan Idelbayev, M. A. Carreira-Perpiñán, 2021, ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Understanding And Manipulating Neural Net Features Using Sparse Oblique Classification Trees

Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov, Suryabhan Singh Hada, 2021, ICIP 2021.

Learning a Tree of Neural Nets

Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov, M. A. Carreira-Perpiñán, 2021, ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Improved Multiclass Adaboost For Image Classification: The Role Of Tree Optimization

Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov, Magzhan Gabidolla, 2021, 2021 IEEE International Conference on Image Processing (ICIP).

Softmax Tree: An Accurate, Fast Classifier When the Number of Classes Is Large

Miguel Á. Carreira-Perpiñán, Arman Zharmagambetov, Magzhan Gabidolla, 2021, EMNLP.

Optimal Neural Net Compression via Constrained Optimization

Miguel Á. Carreira-Perpiñán, 2018 .

One-to-many mappings, continuity constraints and latent variable models

Miguel Á. Carreira-Perpiñán, 1999 .

Articulatory inversion of American English /ô/ by conditional density modes

Miguel Á. Carreira-Perpiñán, Chao Qin, M. A. Carreira-Perpiñán, 2010 .

Estimating Precision by Random Sampling

Miguel Á. Carreira-Perpiñán, Zhengdong Lu, 2005 .