Optimum self-reference spatial diversity processing for FDSS and FH communication systems. - Daniel Pérez Palomar; Miguel Angel Lagunas (EUSIPCO, 2000)

Self-reference beamforming for DS-CDMA communication systems. - Daniel Pérez Palomar; Miguel Angel Lagunas (ICASSP, 2000)

Practical implementation of jointly designed transmit receive space-time IIR filters. - Daniel Pérez Palomar; Miguel Angel Lagunas; Antonio Pascual-Iserte; Ana I. Pérez-Neira (ISSPA, 2001)

Capacity results of spatially correlated frequency-selective MIMO channels in UMTS. - Daniel Pérez Palomar; Javier Rodríguez Fonollosa; Miguel Angel Lagunas (VTC Fall, 2001)

Temporal diversity on DS-CDMA communication systems for blind array signal processing. - Daniel Pérez Palomar; Miguel Angel Lagunas (Signal Process., 2001)

Power allocation techniques for joint beamforming in OFDM-MIMO channels. - Antonio Pascual-Iserte; Ana I. Pérez-Neira; Daniel Pérez Palomar; Miguel Angel Lagunas (EUSIPCO, 2002)

Convex optimization theory applied to joint beamforming design in multicarrier MIMO channels. - Daniel Pérez Palomar; John M. Cioffi; Miguel Angel Lagunas; Antonio Pascual-Iserte (ICC, 2003)

Real-time scheduling for wireless multiuser MISO systems under different fairness criteria. - Diego Bartolomé; Daniel P. Palomar; Ana I. Pérez-Neira (ISSPA (1), 2003)

Joint transmit-receive space-time equalization in spatially correlated MIMO channels: a beamforming approach. - Daniel Pérez Palomar; Miguel Angel Lagunas (IEEE J. Sel. Areas Commun., 2003)

Uniform power allocation in MIMO channels: a game-theoretic approach. - Daniel Pérez Palomar; John M. Cioffi; Miguel Angel Lagunas (IEEE Trans. Inf. Theory, 2003)

Joint Tx-Rx beamforming design for multicarrier MIMO channels: a unified framework for convex optimization. - Daniel Pérez Palomar; John M. Cioffi; Miguel Angel Lagunas (IEEE Trans. Signal Process., 2003)

Unified framework for linear MIMO transceivers with shaping constraints. - Daniel Pérez Palomar (IEEE Commun. Lett., 2004)

Optimum linear joint transmit-receive processing for MIMO channels with QoS constraints. - Daniel Pérez Palomar; Miguel Angel Lagunas; John M. Cioffi (IEEE Trans. Signal Process., 2004)

Alternative decompositions and distributed algorithms for network utility maximization. - Daniel P. Palomar; Mung Chiang (GLOBECOM, 2005)

Solving nonconvex power control problems in wireless networks: low SIR regime and distributed algorithms. - Chee Wei Tan 001; Daniel P. Palomar; Mung Chiang (GLOBECOM, 2005)

Network utility maximization with nonconcave, coupled, and reliability-based uilities. - Mung Chiang; Jang-Won Lee 001; A. Robert Calderbank; Daniel Pérez Palomar; Maryam Fazel (SIGMETRICS, 2005)

Convex primal decomposition for multicarrier linear MIMO transceivers. - Daniel Pérez Palomar (IEEE Trans. Signal Process., 2005)

Designing MIMO communication systems: constellation choice and linear transceiver design. - Daniel Pérez Palomar; Sergio Barbarossa (IEEE Trans. Signal Process., 2005)

Minimum BER linear transceivers for MIMO channels via primal decomposition. - Daniel Pérez Palomar; Mats Bengtsson; Björn E. Ottersten (IEEE Trans. Signal Process., 2005)

Practical algorithms for a family of waterfilling solutions. - Daniel Pérez Palomar; Javier Rodríguez Fonollosa (IEEE Trans. Signal Process., 2005)

Potential Games: A Framework for Vector Power Control Problems With Coupled Constraints. - Gesualdo Scutari; Sergio Barbarossa; Daniel P. Palomar (ICASSP (4), 2006)

Distributed Optimization of Coupled Systems With Applications to Network Utility Maximization. - Chee Wei Tan 001; Daniel P. Palomar; Mung Chiang (ICASSP (5), 2006)

Robust Design of Linear Mimo Transceivers Under Channel Uncertainty. - Xi Zhang 002; Daniel P. Palomar; Björn E. Ottersten (ICASSP (4), 2006)

Alternative Decompositions for Distributed Maximization of Network Utility: Framework and Applications. - Daniel Pérez Palomar; Mung Chiang (INFOCOM, 2006)

Simultaneous Iterative Water-Filling for Gaussian Frequency-Selective Interference Channels. - Gesualdo Scutari; Daniel P. Palomar; Sergio Barbarossa (ISIT, 2006)

MIMO Transceiver Design via Majorization Theory. - Daniel Pérez Palomar; Yi Jiang 002 (Found. Trends Commun. Inf. Theory, 2006)

A Tutorial on Decomposition Methods for Network Utility Maximization. - Daniel Pérez Palomar; Mung Chiang (IEEE J. Sel. Areas Commun., 2006)

Gradient of mutual information in linear vector Gaussian channels. - Daniel Pérez Palomar; Sergio Verdú (IEEE Trans. Inf. Theory, 2006)

A robust maximin approach for MIMO communications with imperfect channel state information based on convex optimization. - Antonio Pascual-Iserte; Daniel Pérez Palomar; Ana I. Pérez-Neira; Miguel Angel Lagunas (IEEE Trans. Signal Process., 2006)

Precoder Optimization for Nonlinear MIMO Transceiver Based on Arbitrary Cost Function. - Yi Jiang 002; Daniel Pérez Palomar; Mahesh K. Varanasi (CISS, 2007)

Unified Theory of Complex-Valued Matrix Differentiation. - Are Hjørungnes; David Gesbert; Daniel P. Palomar (ICASSP (3), 2007)

On Equal Constellation Minimum BER linear MIMO Transceivers. - Luis Garcia Ordóñez; Daniel P. Palomar; Alba Pagès-Zamora; Javier Rodríguez Fonollosa (ICASSP (3), 2007)

Distributed Totally Asynchronous Iterative Waterfilling for Wideband Interference Channel with Time/Frequency Offset. - Gesualdo Scutari; Daniel P. Palomar; Sergio Barbarossa (ICASSP (4), 2007)

Exploiting Hidden Convexity For Flexible And Robust Resource Allocation In Cellular Networks. - Chee-Wei Tan 001; Daniel Pérez Palomar; Mung Chiang (INFOCOM, 2007)

The Computation of the Capacity Region of the Discrete MAC is a Rank-One Non-Convex Optimization Problem. - Eduard Calvo; Daniel P. Palomar; Javier Rodríguez Fonollosa; Josep Vidal (ISIT, 2007)

Optimal Linear Precoding Strategies for Wideband Non-Cooperative Systems based on Game Theory-Part I: Nash Equilibria - Gesualdo Scutari; Daniel Pérez Palomar; Sergio Barbarossa (CoRR, 2007)

Alternative Distributed Algorithms for Network Utility Maximization: Framework and Applications. - Daniel P. Palomar; Mung Chiang (IEEE Trans. Autom. Control., 2007)

Representation of Mutual Information Via Input Estimates. - Daniel Pérez Palomar; Sergio Verdú (IEEE Trans. Inf. Theory, 2007)

High-SNR Analytical Performance of Spatial Multiplexing MIMO Systems With CSI. - Luis Garcia Ordóñez; Daniel Pérez Palomar; Alba Pagès-Zamora; Javier Rodríguez Fonollosa (IEEE Trans. Signal Process., 2007)

Power Control By Geometric Programming. - Mung Chiang; Chee-Wei Tan 001; Daniel Pérez Palomar; Daniel O'Neill; David Julian (IEEE Trans. Wirel. Commun., 2007)

Competitive design of multiuser MIMO interference systems based on game theory: A unified framework. - Gesualdo Scutari; Daniel Pérez Palomar; Sergio Barbarossa (ICASSP, 2008)

Ordered Eigenvalues of a General Class of Hermitian Random Matrices and Performance Analysis of MIMO Systems. - Luis Garcia Ordóñez; Daniel Pérez Palomar; Javier Rodríguez Fonollosa (ICC, 2008)

Image deblocking using convex optimization. - Liwei Guo; Oscar C. Au; Mengyao Ma; Xiaopeng Fan; Peter H. W. Wong; Daniel Pérez Palomar (ICIP, 2008)

The computation of the capacity region of the discrete degraded BC is a nonconvex DC problem. - Eduard Calvo; Daniel Pérez Palomar; Javier Rodríguez Fonollosa; Josep Vidal (ISIT, 2008)

A multivariate generalization of Costa's entropy power inequality. - Miquel Payaró; Daniel P. Palomar (ISIT, 2008)

Asynchronous Iterative Waterfilling for Gaussian Frequency-Selective Interference Channels - Gesualdo Scutari; Daniel Pérez Palomar; Sergio Barbarossa (CoRR, 2008)

Cognitive MIMO Radio: A Competitive Optimality Design Based on Subspace Projections - Gesualdo Scutari; Daniel Pérez Palomar; Sergio Barbarossa (CoRR, 2008)

Game Theory in Communication Systems [Guest Editorial]. - Narayan B. Mandayam; Stephen B. Wicker; Jean C. Walrand; Tamer Basar; Jianwei Huang 001; Daniel Pérez Palomar (IEEE J. Sel. Areas Commun., 2008)

Competitive Design of Multiuser MIMO Systems Based on Game Theory: A Unified View. - Gesualdo Scutari; Daniel Pérez Palomar; Sergio Barbarossa (IEEE J. Sel. Areas Commun., 2008)

Cognitive MIMO radio. - Gesualdo Scutari; Daniel P. Palomar; Sergio Barbarossa (IEEE Signal Process. Mag., 2008)

Lautum Information. - Daniel Pérez Palomar; Sergio Verdú (IEEE Trans. Inf. Theory, 2008)

Asynchronous Iterative Water-Filling for Gaussian Frequency-Selective Interference Channels. - Gesualdo Scutari; Daniel Pérez Palomar; Sergio Barbarossa (IEEE Trans. Inf. Theory, 2008)

Optimal Linear Precoding Strategies for Wideband Noncooperative Systems Based on Game Theory - Part I: Nash Equilibria. - Gesualdo Scutari; Daniel Pérez Palomar; Sergio Barbarossa (IEEE Trans. Signal Process., 2008)

Optimal Linear Precoding Strategies for Wideband Non-Cooperative Systems Based on Game Theory - Part II: Algorithms. - Gesualdo Scutari; Daniel Pérez Palomar; Sergio Barbarossa (IEEE Trans. Signal Process., 2008)

Statistically Robust Design of Linear MIMO Transceivers. - Xi Zhang 002; Daniel Pérez Palomar; Björn E. Ottersten (IEEE Trans. Signal Process., 2008)

Competitive optimization of cognitive radio MIMO systems via game theory. - Gesualdo Scutari; Daniel P. Palomar; Sergio Barbarossa (GAMENETS, 2009)

Maximin robust design for MIMO communication systems against imperfect CSIT. - Jiaheng Wang 001; Daniel Pérez Palomar (ICASSP, 2009)

Rank-constrained separable semidefinite programming for optimal beamforming design. - Yongwei Huang; Daniel Pérez Palomar (ISIT, 2009)

On optimal precoding in linear vector Gaussian channels with arbitrary input distribution. - Miquel Payaró; Daniel P. Palomar (ISIT, 2009)

Optimal Bit Loading for MIMO Systems with Decision Feedback Detection. - Svante Bergman; Daniel Pérez Palomar; Björn E. Ottersten (VTC Spring, 2009)

Flexible design of cognitive radio wireless systems. - Gesualdo Scutari; Daniel P. Palomar; Jong-Shi Pang; Francisco Facchinei (IEEE Signal Process. Mag., 2009)

Hessian and concavity of mutual information, differential entropy, and entropy power in linear vector Gaussian channels. - Miquel Payaró; Daniel Pérez Palomar (IEEE Trans. Inf. Theory, 2009)

Energy-robustness tradeoff in cellular network power control. - Chee-Wei Tan 001; Daniel Pérez Palomar; Mung Chiang (IEEE/ACM Trans. Netw., 2009)

Joint bit allocation and precoding for MIMO systems with decision feedback detection. - Svante Bergman; Daniel Pérez Palomar; Björn E. Ottersten (IEEE Trans. Signal Process., 2009)

Ordered Eigenvalues of a General Class of Hermitian Random Matrices With Application to the Performance Analysis of MIMO Systems. - Luis Garcia Ordóñez; Daniel Pérez Palomar; Javier Rodríguez Fonollosa (IEEE Trans. Signal Process., 2009)

Minimum BER linear MIMO transceivers with adaptive number of substreams. - Luis Garcia Ordóñez; Daniel Pérez Palomar; Alba Pagès-Zamora; Javier Rodríguez Fonollosa (IEEE Trans. Signal Process., 2009)

The MIMO iterative waterfilling algorithm. - Gesualdo Scutari; Daniel Pérez Palomar; Sergio Barbarossa (IEEE Trans. Signal Process., 2009)

Worst-case robust MIMO transmission with imperfect channel knowledge. - Jiaheng Wang 001; Daniel Pérez Palomar (IEEE Trans. Signal Process., 2009)

Correction to "worst-case robust MIMO transmission with imperfect channel knowledge". - Jiaheng Wang 001; Daniel Pérez Palomar (IEEE Trans. Signal Process., 2009)

Competitive optimization of cognitive radio MIMO systems via game theory. - Gesualdo Scutari; Daniel P. Palomar; Sergio Barbarossa (Convex Optimization in Signal Processing and Communications, 2010)

A dual perspective on separable semidefinite programming with applications to optimal beamforming. - Yongwei Huang; Daniel Pérez Palomar (ICASSP, 2010)

On MMSE properties and I-MMSE implications in parallel MIMO Gaussian channels. - Ronit Bustin; Miquel Payaró; Daniel Pérez Palomar; Shlomo Shamai (ISIT, 2010)

On the diversity, multiplexing, and array gain tradeoff in MIMO channels. - Luis Garcia Ordóñez; Daniel Pérez Palomar; Javier Rodríguez Fonollosa (ISIT, 2010)

Robust cognitive radio via game theory. - Jiaheng Wang 001; Gesualdo Scutari; Daniel Pérez Palomar (ISIT, 2010)

Convex Optimization, Game Theory, and Variational Inequality Theory. - Gesualdo Scutari; Daniel Pérez Palomar; Francisco Facchinei; Jong-Shi Pang (IEEE Signal Process. Mag., 2010)

On the Computation of the Capacity Region of the Discrete MAC. - Eduard Calvo; Daniel Pérez Palomar; Javier Rodríguez Fonollosa; Josep Vidal (IEEE Trans. Commun., 2010)

Rank-constrained separable semidefinite programming with applications to optimal beamforming. - Yongwei Huang; Daniel Pérez Palomar (IEEE Trans. Signal Process., 2010)

A dual perspective on separable semidefinite programming with applications to optimal downlink beamforming. - Yongwei Huang; Daniel Pérez Palomar (IEEE Trans. Signal Process., 2010)

Code design for radar STAP via optimization theory. - Antonio De Maio; Silvio De Nicola; Yongwei Huang; Daniel Pérez Palomar; Shuzhong Zhang; Alfonso Farina (IEEE Trans. Signal Process., 2010)

Design of cognitive radio systems under temperature-interference constraints: a variational inequality approach. - Jong-Shi Pang; Gesualdo Scutari; Daniel Pérez Palomar; Francisco Facchinei (IEEE Trans. Signal Process., 2010)

MIMO cognitive radio: a game theoretical approach. - Gesualdo Scutari; Daniel Pérez Palomar (IEEE Trans. Signal Process., 2010)

Robust MMSE precoding in MIMO channels with pre-fixed receivers. - Jiaheng Wang 001; Daniel Pérez Palomar (IEEE Trans. Signal Process., 2010)

Asymptotic analysis and consistent estimation of high-dimensional Markowitz portfolios. - Francisco Rubio 001; Xavier Mestre; Daniel Pérez Palomar (CAMSAP, 2011)

Fundamental diversity, multiplexing, and array gain tradeoff under different MIMO channel models. - Luis Garcia Ordóñez; Daniel Pérez Palomar; Javier Rodríguez Fonollosa (ICASSP, 2011)

Maximum likelihood ICA of quaternion Gaussian vectors. - Javier Vía; Daniel P. Palomar; Luis Vielva; Ignacio Santamaría (ICASSP, 2011)

Distributed dynamic pricing for MIMO interfering multiuser systems: A unified approach. - Gesualdo Scutari; Daniel P. Palomar; Francisco Facchinei; Jong-Shi Pang (NetGCoop, 2011)

Yet another entropy power inequality with an application. - Miquel Payaró; Maria Gregori; Daniel Pérez Palomar (WCSP, 2011)

Performance analysis and optimal selection of large mean-variance portfolios under estimation risk - Francisco Rubio 001; Xavier Mestre; Daniel P. Palomar (CoRR, 2011)

Fractional QCQP With Applications in ML Steering Direction Estimation for Radar Detection. - Antonio De Maio; Yongwei Huang; Daniel Pérez Palomar; Shuzhong Zhang; Alfonso Farina (IEEE Trans. Signal Process., 2011)

Generalized Likelihood Ratios for Testing the Properness of Quaternion Gaussian Vectors. - Javier Vía; Daniel P. Palomar; Luis Vielva (IEEE Trans. Signal Process., 2011)

Quaternion ICA From Second-Order Statistics. - Javier Vía; Daniel P. Palomar; Luis Vielva; Ignacio Santamaría (IEEE Trans. Signal Process., 2011)

Robust MIMO Cognitive Radio Via Game Theory. - Jiaheng Wang 001; Gesualdo Scutari; Daniel Pérez Palomar (IEEE Trans. Signal Process., 2011)

Lifetime maximization for beamforming applications in wireless sensor networks. - Benjamín Béjar Haro; Santiago Zazo; Daniel P. Palomar (ICASSP, 2012)

Lorentz-positive mapswith applications to robust MISO downlink beamforming. - Yongwei Huang; Daniel P. Palomar; Shuzhong Zhang (ICASSP, 2012)

Robust maximin MIMO precoding for arbitrary convex uncertainty sets. - Jiaheng Wang 001; Mats Bengtsson; Björn E. Ottersten; Daniel P. Palomar (ICASSP, 2012)

Calibration of high-dimensional precision matrices under quadratic loss. - Mengyi Zhang; Francisco Rubio 001; Daniel P. Palomar (ICASSP, 2012)

Day-ahead bidding strategies for demand-side expected cost minimization. - Italo Atzeni; Luis Garcia Ordóñez; Gesualdo Scutari; Daniel P. Palomar; Javier Rodríguez Fonollosa (SmartGridComm, 2012)

Optimal order execution for algorithmic trading: A CVaR approach. - Yiyong Feng; Francisco Rubio 001; Daniel Pérez Palomar (SPAWC, 2012)

Performance Analysis and Optimal Selection of Large Minimum Variance Portfolios Under Estimation Risk. - Francisco Rubio 001; Xavier Mestre; Daniel P. Palomar (IEEE J. Sel. Top. Signal Process., 2012)

Array Gain in the DMT Framework for MIMO Channels. - Luis Garcia Ordóñez; Daniel P. Palomar; Javier Rodríguez Fonollosa (IEEE Trans. Inf. Theory, 2012)

Robust order execution under box uncertainty sets. - Yiyong Feng; Daniel P. Palomar (ACSSC, 2013)

Robust MIMO precoding for the schatten norm based channel uncertainty sets. - Jiaheng Wang 001; Mats Bengtsson; Björn E. Ottersten; Daniel P. Palomar (GLOBECOM, 2013)

Cooperative day-ahead bidding strategies for demand-side expected cost minimization. - Italo Atzeni; Luis Garcia Ordóñez; Gesualdo Scutari; Daniel Pérez Palomar; Javier Rodríguez Fonollosa (ICASSP, 2013)

Decomposition by partial linearization in multiuser systems. - Gesualdo Scutari; Francisco Facchinei; Daniel Pérez Song; Daniel P. Palomar; Jong-Shi Pang (ICASSP, 2013)

Robust MIMO cognitive radio systems under temperature interference constraints. - Yang Yang 033; Peiran Song; Gesualdo Scutari; Daniel P. Palomar (ICASSP, 2013)

Robust adaptive beamforming with imprecise steering vector and noise covariance matrix due to finite sample size. - Mengyi Zhang; Francisco Rubio 001; Daniel P. Palomar; Xavier Mestre (ICASSP, 2013)

Parallel stochastic decomposition algorithms for multi-agent systems. - Yang Yang 033; Gesualdo Scutari; Daniel Pérez Palomar (SPAWC, 2013)

Robust MIMO Cognitive Radio Systems Under Interference Temperature Constraints. - Yang Yang 033; Gesualdo Scutari; Peiran Song; Daniel P. Palomar (IEEE J. Sel. Areas Commun., 2013)

Universal Binary Semidefinite Relaxation for ML Signal Detection. - Xiaopeng Fan; Junxiao Song; Daniel P. Palomar; Oscar C. Au (IEEE Trans. Commun., 2013)

On MMSE Crossing Properties and Implications in Parallel Vector Gaussian Channels. - Ronit Bustin; Miquel Payaró; Daniel P. Palomar; Shlomo Shamai (Shitz) (IEEE Trans. Inf. Theory, 2013)

Demand-Side Management via Distributed Energy Generation and Storage Optimization. - Italo Atzeni; Luis Garcia Ordóñez; Gesualdo Scutari; Daniel P. Palomar; Javier Rodríguez Fonollosa (IEEE Trans. Smart Grid, 2013)

Noncooperative and Cooperative Optimization of Distributed Energy Generation and Storage in the Demand-Side of the Smart Grid. - Italo Atzeni; Luis Garcia Ordóñez; Gesualdo Scutari; Daniel P. Palomar; Javier Rodríguez Fonollosa (IEEE Trans. Signal Process., 2013)

Lorentz-Positive Maps and Quadratic Matrix Inequalities With Applications to Robust MISO Transmit Beamforming. - Yongwei Huang; Daniel P. Palomar; Shuzhong Zhang (IEEE Trans. Signal Process., 2013)

Robust MIMO Precoding for Several Classes of Channel Uncertainty. - Jiaheng Wang 001; Mats Bengtsson; Björn E. Ottersten; Daniel P. Palomar (IEEE Trans. Signal Process., 2013)

Multi-Portfolio Optimization: A Potential Game Approach. - Yang Yang 033; Francisco Rubio 001; Gesualdo Scutari; Daniel P. Palomar (IEEE Trans. Signal Process., 2013)

Improved Calibration of High-Dimensional Precision Matrices. - Mengyi Zhang; Francisco Rubio 001; Daniel P. Palomar (IEEE Trans. Signal Process., 2013)

Finite-Sample Linear Filter Optimization in Wireless Communications and Financial Systems. - Mengyi Zhang; Francisco Rubio 001; Daniel P. Palomar; Xavier Mestre (IEEE Trans. Signal Process., 2013)

A fast algorithm for sparse generalized eigenvalue problem. - Junxiao Song; Prabhu Babu; Daniel P. Palomar (ACSSC, 2014)

An online parallel algorithm for spectrum sensing in cognitive radio networks. - Yang Yang 033; Mengyi Zhang; Marius Pesavento; Daniel P. Palomar (ACSSC, 2014)

Convex separable problems with linear and box constraints. - Antonio Alberto D'Amico; Luca Sanguinetti; Daniel P. Palomar (ICASSP, 2014)

Regularized robust estimation of mean and covariance matrix under heavy tails and outliers. - Ying Sun 003; Prabhu Babu; Daniel Pérez Palomar (SAM, 2014)

Convex separable problems with linear and box constraints in signal processing and communications. - Antonio A. D'Amico; Luca Sanguinetti; Daniel P. Palomar (CoRR, 2014)

A Parallel Stochastic Approximation Method for Nonconvex Multi-Agent Optimization Problems. - Yang Yang 033; Gesualdo Scutari; Daniel Pérez Palomar; Marius Pesavento (CoRR, 2014)

Real and Complex Monotone Communication Games. - Gesualdo Scutari; Francisco Facchinei; Jong-Shi Pang; Daniel P. Palomar (IEEE Trans. Inf. Theory, 2014)

Noncooperative Day-Ahead Bidding Strategies for Demand-Side Expected Cost Minimization With Real-Time Adjustments: A GNEP Approach. - Italo Atzeni; Luis Garcia Ordóñez; Gesualdo Scutari; Daniel P. Palomar; Javier Rodríguez Fonollosa (IEEE Trans. Signal Process., 2014)

Convex Separable Problems With Linear Constraints in Signal Processing and Communications. - Antonio A. D'Amico; Luca Sanguinetti; Daniel Pérez Palomar (IEEE Trans. Signal Process., 2014)

Energy Efficient Collaborative Beamforming in Wireless Sensor Networks. - Benjamín Béjar Haro; Santiago Zazo; Daniel P. Palomar (IEEE Trans. Signal Process., 2014)

Randomized Algorithms for Optimal Solutions of Double-Sided QCQP With Applications in Signal Processing. - Yongwei Huang; Daniel P. Palomar (IEEE Trans. Signal Process., 2014)

Decomposition by Partial Linearization: Parallel Optimization of Multi-Agent Systems. - Gesualdo Scutari; Francisco Facchinei; Peiran Song; Daniel P. Palomar; Jong-Shi Pang (IEEE Trans. Signal Process., 2014)

Regularized Tyler's Scatter Estimator: Existence, Uniqueness, and Algorithms. - Ying Sun 003; Prabhu Babu; Daniel P. Palomar (IEEE Trans. Signal Process., 2014)

PRIME: Phase retrieval via majorization-minimization technique. - Tianyu Qiu; Prabhu Babu; Daniel Pérez Palomar (ACSSC, 2015)

Robust low-rank optimization for large scale problems. - Licheng Zhao; Prabhu Babu; Daniel Pérez Palomar (ACSSC, 2015)

Linear support vector machines with normalizations. - Yiyong Feng; Daniel Pérez Palomar (ICASSP, 2015)

Optimization methods for sequence design with low autocorrelation sidelobes. - Junxiao Song; Prabhu Babu; Daniel P. Palomar (ICASSP, 2015)

Robust estimation of structured covariance matrix for heavy-tailed distributions. - Ying Sun 003; Prabhu Babu; Daniel Pérez Palomar (ICASSP, 2015)

Normalization of Linear Support Vector Machines. - Yiyong Feng; Daniel P. Palomar (IEEE Trans. Signal Process., 2015)

SCRIP: Successive Convex Optimization Methods for Risk Parity Portfolio Design. - Yiyong Feng; Daniel Pérez Palomar (IEEE Trans. Signal Process., 2015)

Robust Optimization of Order Execution. - Yiyong Feng; Daniel Pérez Palomar; Francisco Rubio 001 (IEEE Trans. Signal Process., 2015)

Sparse Generalized Eigenvalue Problem Via Smooth Optimization. - Junxiao Song; Prabhu Babu; Daniel Pérez Palomar (IEEE Trans. Signal Process., 2015)

Optimization Methods for Designing Sequences With Low Autocorrelation Sidelobes. - Junxiao Song; Prabhu Babu; Daniel Pérez Palomar (IEEE Trans. Signal Process., 2015)

Regularized Robust Estimation of Mean and Covariance Matrix Under Heavy-Tailed Distributions. - Ying Sun 003; Prabhu Babu; Daniel Pérez Palomar (IEEE Trans. Signal Process., 2015)

Robust rank constrained kronecker covariance matrix estimation. - Arnaud Breloy; Ying Sun 003; Prabhu Babu; Guillaume Ginolhac; Daniel Pérez Palomar (ACSSC, 2016)

Distributed nonconvex multiagent optimization over time-varying networks. - Ying Sun 003; Gesualdo Scutari; Daniel Pérez Palomar (ACSSC, 2016)

Mean-reverting portfolio design via majorization-minimization method. - Ziping Zhao 002; Daniel P. Palomar (ACSSC, 2016)

Block majorization-minimization algorithms for low-rank clutter subspace estimation. - Arnaud Breloy; Ying Sun 003; Prabhu Babu; Daniel Pérez Palomar (EUSIPCO, 2016)

Orthogonal sparse eigenvectors: A procrustes problem. - Konstantinos Benidis; Ying Sun 003; Prabhu Babu; Daniel Pérez Palomar (ICASSP, 2016)

Portfolio optimization with asset selection and risk parity control. - Yiyong Feng; Daniel Pérez Palomar (ICASSP, 2016)

Sequence design to minimize the peak sidelobe level. - Junxiao Song; Prabhu Babu; Daniel Pérez Palomar (ICASSP, 2016)

Optimal design of constant-modulus channel training sequences. - Zhongju Wang 001; Prabhu Babu; Daniel P. Palomar (ICASSP, 2016)

SWIPT techniques for multiuser MIMO broadcast systems. - Javier Rubio; Antonio Pascual-Iserte; Daniel P. Palomar; Andrea Goldsmith (PIMRC, 2016)

A robust signal subspace estimator. - Arnaud Breloy; Ying Sun 003; Prabhu Babu; Guillaume Ginolhac; Daniel Pérez Palomar; Frédéric Pascal 001 (SSP, 2016)

Undersampled Phase Retrieval via Majorization-Minimization. - Tianyu Qiu; Daniel P. Palomar (CoRR, 2016)

A Signal Processing Perspective of Financial Engineering. - Yiyong Feng; Daniel P. Palomar (Found. Trends Signal Process., 2016)

Introduction to the Issue on Financial Signal Processing and Machine Learning for Electronic Trading. - Ali N. Akansu; Dmitry Malioutov; Daniel P. Palomar; Emmanuelle Jay; Danilo P. Mandic (IEEE J. Sel. Top. Signal Process., 2016)

An Online Parallel Algorithm for Recursive Estimation of Sparse Signals. - Yang Yang 033; Marius Pesavento; Mengyi Zhang; Daniel P. Palomar (IEEE Trans. Signal Inf. Process. over Networks, 2016)

Orthogonal Sparse PCA and Covariance Estimation via Procrustes Reformulation. - Konstantinos Benidis; Ying Sun 003; Prabhu Babu; Daniel P. Palomar (IEEE Trans. Signal Process., 2016)

PRIME: Phase Retrieval via Majorization-Minimization. - Tianyu Qiu; Prabhu Babu; Daniel Pérez Palomar (IEEE Trans. Signal Process., 2016)

Sequence Design to Minimize the Weighted Integrated and Peak Sidelobe Levels. - Junxiao Song; Prabhu Babu; Daniel P. Palomar (IEEE Trans. Signal Process., 2016)

Sequence Set Design With Good Correlation Properties Via Majorization-Minimization. - Junxiao Song; Prabhu Babu; Daniel P. Palomar (IEEE Trans. Signal Process., 2016)

Low-Complexity Algorithms for Low Rank Clutter Parameters Estimation in Radar Systems. - Ying Sun 003; Arnaud Breloy; Prabhu Babu; Daniel P. Palomar; Frédéric Pascal 001; Guillaume Ginolhac (IEEE Trans. Signal Process., 2016)

Robust Estimation of Structured Covariance Matrix for Heavy-Tailed Elliptical Distributions. - Ying Sun 003; Prabhu Babu; Daniel Pérez Palomar (IEEE Trans. Signal Process., 2016)

Design of PAR-Constrained Sequences for MIMO Channel Estimation via Majorization-Minimization. - Zhongju Wang 001; Prabhu Babu; Daniel P. Palomar (IEEE Trans. Signal Process., 2016)

A Parallel Decomposition Method for Nonconvex Stochastic Multi-Agent Optimization Problems. - Yang Yang 033; Gesualdo Scutari; Daniel P. Palomar; Marius Pesavento (IEEE Trans. Signal Process., 2016)

Efficient Algorithms on Robust Low-Rank Matrix Completion Against Outliers. - Licheng Zhao; Prabhu Babu; Daniel P. Palomar (IEEE Trans. Signal Process., 2016)

Sum-Rate Maximization for Energy Harvesting Nodes With a Generalized Power Consumption Model. - Maria Gregori; Miquel Payaró; Daniel Pérez Palomar (IEEE Trans. Wirel. Commun., 2016)

Robust estimation of mean and covariance matrix for incomplete data in financial applications. - Junyan Liu; Daniel P. Palomar (GlobalSIP, 2017)

Robust maximum likelihood estimation of sparse vector error correction model. - Ziping Zhao 002; Daniel P. Palomar (GlobalSIP, 2017)

A low-complexity algorithm for OFDM phase noise estimation. - Zhongju Wang 001; Prabhu Babu; Daniel P. Palomar (SPAWC, 2017)

A fast algorithm for joint design of transmit waveforms and receive filters. - Linlong Wu; Prabhu Babu; Daniel P. Palomar (SPAWC, 2017)

Introduction to the Issue on Cooperative Signal Processing for Heterogeneous and Multi-Task Wireless Sensor Networks. - Abdelhak M. Zoubir; Jorge Plata-Chaves; Daniel Pérez Palomar; Anna Scaglione; Alejandro Ribeiro (IEEE J. Sel. Top. Signal Process., 2017)

Joint Optimization of Power and Data Transfer in Multiuser MIMO Systems. - Javier Rubio; Antonio Pascual-Iserte; Daniel P. Palomar; Andrea Goldsmith (IEEE Trans. Signal Process., 2017)

Majorization-Minimization Algorithms in Signal Processing, Communications, and Machine Learning. - Ying Sun 003; Prabhu Babu; Daniel P. Palomar (IEEE Trans. Signal Process., 2017)

Effective Low-Complexity Optimization Methods for Joint Phase Noise and Channel Estimation in OFDM. - Zhongju Wang 001; Prabhu Babu; Daniel P. Palomar (IEEE Trans. Signal Process., 2017)

Cognitive Radar-Based Sequence Design via SINR Maximization. - Linlong Wu; Prabhu Babu; Daniel P. Palomar (IEEE Trans. Signal Process., 2017)

Maximin Joint Optimization of Transmitting Code and Receiving Filter in Radar and Communications. - Licheng Zhao; Daniel P. Palomar (IEEE Trans. Signal Process., 2017)

A Unified Framework for Low Autocorrelation Sequence Design via Majorization-Minimization. - Licheng Zhao; Junxiao Song; Prabhu Babu; Daniel P. Palomar (IEEE Trans. Signal Process., 2017)

Distributed optimization for Generalized Phase Retrieval Over Networks. - Ziping Zhao 002; Songtao Lu; Mingyi Hong 001; Daniel P. Palomar (ACSSC, 2018)

Parameter Estimation of Heavy-Tailed Random Walk Model from Incomplete Data. - Junyan Liu; Sandeep Kumar 005; Daniel P. Palomar (ICASSP, 2018)

MIMO Transmit Beampattern Matching Under Waveform Constraints. - Ziping Zhao 002; Daniel P. Palomar (ICASSP, 2018)

Sparse Reduced Rank Regression with Nonconvex Regularization. - Ziping Zhao 002; Daniel P. Palomar (SSP, 2018)

Optimal Portfolio Design for Statistical Arbitrage in Finance. - Ziping Zhao 002; Rui Zhou; Zhongju Wang 001; Daniel P. Palomar (SSP, 2018)

Coordinated Scheduling and Spectrum Sharing via Matrix Fractional Programming. - Kaiming Shen; Wei Yu 001; Licheng Zhao; Daniel P. Palomar (CoRR, 2018)

Optimization Methods for Financial Index Tracking: From Theory to Practice. - Konstantinos Benidis; Yiyong Feng; Daniel P. Palomar (Found. Trends Optim., 2018)

Sparse Portfolios for High-Dimensional Financial Index Tracking. - Konstantinos Benidis; Yiyong Feng; Daniel P. Palomar (IEEE Trans. Signal Process., 2018)

MISO Channel Estimation and Tracking from Received Signal Strength Feedback. - Tianyu Qiu; Xiao Fu 001; Nicholas D. Sidiropoulos; Daniel P. Palomar (IEEE Trans. Signal Process., 2018)

Transmit Waveform/Receive Filter Design for MIMO Radar With Multiple Waveform Constraints. - Linlong Wu; Prabhu Babu; Daniel P. Palomar (IEEE Trans. Signal Process., 2018)

Mean-Reverting Portfolio With Budget Constraint. - Ziping Zhao 002; Daniel P. Palomar (IEEE Trans. Signal Process., 2018)

A Markowitz Portfolio Approach to Options Trading. - Licheng Zhao; Daniel P. Palomar (IEEE Trans. Signal Process., 2018)

Bipartite Structured Gaussian Graphical Modeling via Adjacency Spectral Priors. - Sandeep Kumar 005; Jiaxi Ying; José Vinícius de Miranda Cardoso; Daniel P. Palomar (ACSSC, 2019)

Accelerating the Multivariate SKEW T Parameter Estimation. - Rui Zhou; Daniel P. Palomar (CAMSAP, 2019)

Robust Factor Analysis Parameter Estimation. - Rui Zhou; Junyan Liu; Sandeep Kumar 005; Daniel P. Palomar (EUROCAST (2), 2019)

Parameter Estimation of Heavy-Tailed AR(p) Model from Incomplete Data. - Junyan Liu; Sandeep Kumar 005; Daniel P. Palomar (EUSIPCO, 2019)

Large-Scale Regularized Portfolio Selection Via Convex Optimization. - Ziping Zhao 002; Daniel P. Palomar (GlobalSIP, 2019)

Unified Framework for Minimax MIMO Transmit Beampattern Matching under Waveform Constraints. - Rui Zhou; Ziping Zhao 002; Daniel P. Palomar (ICASSP, 2019)

Structured Graph Learning Via Laplacian Spectral Constraints. - Sandeep Kumar 005; Jiaxi Ying; José Vinícius de Miranda Cardoso; Daniel P. Palomar (NeurIPS, 2019)

Distributed Inexact Successive Convex Approximation ADMM: Analysis-Part I. - Sandeep Kumar 005; Ketan Rajawat; Daniel P. Palomar (CoRR, 2019)

Regularized robust estimation of mean and covariance matrix for incomplete data. - Junyan Liu; Daniel P. Palomar (Signal Process., 2019)

Optimization of MIMO Device-to-Device Networks via Matrix Fractional Programming: A Minorization-Maximization Approach. - Kaiming Shen; Wei Yu 001; Licheng Zhao; Daniel P. Palomar (IEEE/ACM Trans. Netw., 2019)

Parameter Estimation of Heavy-Tailed AR Model With Missing Data Via Stochastic EM. - Junyan Liu; Sandeep Kumar 005; Daniel P. Palomar (IEEE Trans. Signal Process., 2019)

Sequence Design for Spectral Shaping via Minimization of Regularized Spectral Level Ratio. - Linlong Wu; Daniel P. Palomar (IEEE Trans. Signal Process., 2019)

Optimization Algorithms for Graph Laplacian Estimation via ADMM and MM. - Licheng Zhao; Yiwei Wang 001; Sandeep Kumar 005; Daniel P. Palomar (IEEE Trans. Signal Process., 2019)

Optimal Mean-Reverting Portfolio With Leverage Constraint for Statistical Arbitrage in Finance. - Ziping Zhao 002; Rui Zhou; Daniel P. Palomar (IEEE Trans. Signal Process., 2019)

Learning Undirected Graphs in Financial Markets. - José Vinícius de Miranda Cardoso; Daniel P. Palomar (ACSSC, 2020)

M-Estimators of Scatter with Eigenvalue Shrinkage. - Esa Ollila; Daniel P. Palomar; Frédéric Pascal 001 (ICASSP, 2020)

A Theoretical Basis for Practitioners Heuristic 1/N and Long-Only Quintile Portfolio. - Rui Zhou; Daniel P. Palomar (ICASSP, 2020)

Nonconvex Sparse Graph Learning under Laplacian Constrained Graphical Model. - Jiaxi Ying; José Vinícius de Miranda Cardoso; Daniel P. Palomar (NeurIPS, 2020)

Does the 𝓁1-norm Learn a Sparse Graph under Laplacian Constrained Graphical Models? - Jiaxi Ying; José Vinícius de Miranda Cardoso; Daniel P. Palomar (CoRR, 2020)

Algorithms for Learning Graphs in Financial Markets. - José Vinícius de Miranda Cardoso; Jiaxi Ying; Daniel Pérez Palomar (CoRR, 2020)

A Unified Framework for Structured Graph Learning via Spectral Constraints. - Sandeep Kumar 005; Jiaxi Ying; José Vinícius de Miranda Cardoso; Daniel P. Palomar (J. Mach. Learn. Res., 2020)

General sparse risk parity portfolio design via successive convex optimization. - Linlong Wu; Yiyong Feng; Daniel P. Palomar (Signal Process., 2020)

Student's $t$ VAR Modeling With Missing Data Via Stochastic EM and Gibbs Sampling. - Rui Zhou; Junyan Liu; Sandeep Kumar 005; Daniel P. Palomar (IEEE Trans. Signal Process., 2020)

Understanding the Quintile Portfolio. - Rui Zhou; Daniel P. Palomar (IEEE Trans. Signal Process., 2020)

A Fast Algorithm for Graph Learning under Attractive Gaussian Markov Random Fields. - Jiaxi Ying; José Vinícius de Miranda Cardoso; Daniel P. Palomar (ACSCC, 2021)

Minimax Estimation of Laplacian Constrained Precision Matrices. - Jiaxi Ying; José Vinícius de Miranda Cardoso; Daniel P. Palomar (AISTATS, 2021)

Improved estimation of the degree of freedom parameter of multivariate $t$-distribution. - Frédéric Pascal 001; Esa Ollila; Daniel P. Palomar (EUSIPCO, 2021)

Parameter Estimation for Student's t VAR Model with Missing Data. - Rui Zhou; Junyan Liu; Sandeep Kumar 005; Daniel P. Palomar (ICASSP, 2021)

Graphical Models in Heavy-Tailed Markets. - José Vinícius de Miranda Cardoso; Jiaxi Ying; Daniel P. Palomar (NeurIPS, 2021)

Fast Projected Newton-like Method for Precision Matrix Estimation with Nonnegative Partial Correlations. - Jiaxi Ying; José Vinícius de Miranda Cardoso; Jian-Feng Cai 001; Daniel P. Palomar (CoRR, 2021)

Majorization-Minimization on the Stiefel Manifold With Application to Robust Sparse PCA. - Arnaud Breloy; Sandeep Kumar 005; Ying Sun 003; Daniel P. Palomar (IEEE Trans. Signal Process., 2021)

Shrinking the Eigenvalues of M-Estimators of Covariance Matrix. - Esa Ollila; Daniel P. Palomar; Frédéric Pascal 001 (IEEE Trans. Signal Process., 2021)

Solving High-Order Portfolios via Successive Convex Approximation Algorithms. - Rui Zhou; Daniel P. Palomar (IEEE Trans. Signal Process., 2021)

Efficient Algorithms for General Isotone Optimization. - Xiwen Wang 003; Jiaxi Ying; José Vinícius de Miranda Cardoso; Daniel P. Palomar (AAAI, 2022)

False Discovery Rate Control for Grouped Variable Selection in High-Dimensional Linear Models Using the T-Knock Filter. - Jasin Machkour; Michael Muma; Daniel P. Palomar (EUSIPCO, 2022)

Learning Bipartite Graphs: Heavy Tails and Multiple Components. - José Vinícius de Miranda Cardoso; Jiaxi Ying; Daniel P. Palomar (NeurIPS, 2022)

Adaptive Estimation of MTP2 Graphical Models. - Jiaxi Ying; José Vinícius de Miranda Cardoso; Daniel P. Palomar (CoRR, 2022)

Covariance Matrix Estimation Under Low-Rank Factor Model With Nonnegative Correlations. - Rui Zhou; Jiaxi Ying; Daniel P. Palomar (IEEE Trans. Signal Process., 2022)

Graph Learning for Balanced Clustering of Heavy-Tailed Data. - Amirhossein Javaheri; José Vinícius de Miranda Cardoso; Daniel P. Palomar (CAMSAP, 2023)

The Informed Elastic Net for Fast Grouped Variable Selection and FDR Control in Genomics Research. - Jasin Machkour; Michael Muma; Daniel P. Palomar (CAMSAP, 2023)

Intraday Volatility-Volume Joint Modeling and Forecasting: A State-Space Approach. - Shengjie Xiu; Daniel P. Palomar (EUSIPCO, 2023)

Estimating Normalized Graph Laplacians in Financial Markets. - José Vinícius de Miranda Cardoso; Jiaxi Ying; Sandeep Kumar 005; Daniel P. Palomar (ICASSP, 2023)

Adaptive Estimation of Graphical Models under Total Positivity. - Jiaxi Ying; José Vinícius de Miranda Cardoso; Daniel P. Palomar (ICML, 2023)

Fast Projected Newton-like Method for Precision Matrix Estimation under Total Positivity. - Jianfeng Cai 001; José Vinícius de Miranda Cardoso; Daniel P. Palomar; Jiaxi Ying (NeurIPS, 2023)

Learning Large-Scale MTP2 Gaussian Graphical Models via Bridge-Block Decomposition. - Xiwen Wang 003; Jiaxi Ying; Daniel P. Palomar (NeurIPS, 2023)

A Novel Algorithm for GARCH Model Estimation. - Chenyu Gao; Ziping Zhao 002; Daniel P. Palomar (SSP, 2023)

False Discovery Rate Control for Fast Screening of Large-Scale Genomics Biobanks. - Jasin Machkour; Michael Muma; Daniel P. Palomar (SSP, 2023)

Discerning and Enhancing the Weighted Sum-Rate Maximization Algorithms in Communications. - Zepeng Zhang; Ziping Zhao 002; Kaiming Shen; Daniel P. Palomar; Wei Yu 001 (CoRR, 2023)

Affine Equivariant Tyler's M-Estimator Applied to Tail Parameter Learning of Elliptical Distributions. - Esa Ollila; Daniel P. Palomar; Frédéric Pascal 001 (IEEE Signal Process. Lett., 2023)

Efficient and Scalable Parametric High-Order Portfolios Design via the Skew-$t$ Distribution. - Xiwen Wang 003; Rui Zhou; Jiaxi Ying; Daniel P. Palomar (IEEE Trans. Signal Process., 2023)

A Fast Successive QP Algorithm for General Mean-Variance Portfolio Optimization. - Shengjie Xiu; Xiwen Wang 003; Daniel P. Palomar (IEEE Trans. Signal Process., 2023)

Robust and Constrained Estimation of State-Space Models: A Majorization-Minimization Approach. - Yifan Yu; Shengjie Xiu; Daniel P. Palomar (IEEECONF, 2024)

Learning Time-Varying Graphs for Heavy-Tailed Data Clustering. - Amirhossein Javaheri; Daniel P. Palomar (EUSIPCO, 2024)

FDR-Controlled Sparse Index Tracking with Autoregressive Stock Dependency Models. - Jasin Machkour; Michael Muma; Daniel P. Palomar (EUSIPCO, 2024)

Joint Signal Recovery and Graph Learning from Incomplete Time-Series. - Amirhossein Javaheri; Arash Amini; Farokh Marvasti; Daniel P. Palomar (ICASSP, 2024)

Sparse PCA with False Discovery Rate Controlled Variable Selection. - Jasin Machkour; Arnaud Breloy; Michael Muma; Daniel P. Palomar; Frédéric Pascal 001 (ICASSP, 2024)

Adaptive Passive-Aggressive Framework for Online Regression with Side Information. - Runhao Shi; Jiaxi Ying; Daniel P. Palomar (NeurIPS, 2024)

Learning Spatiotemporal Graphical Models From Incomplete Observations. - Amirhossein Javaheri; Arash Amini; Farokh Marvasti; Daniel P. Palomar (IEEE Trans. Signal Process., 2024)

SAOFTRL: A Novel Adaptive Algorithmic Framework for Enhancing Online Portfolio Selection. - Runhao Shi; Daniel P. Palomar (IEEE Trans. Signal Process., 2024)

FDR-Controlled Portfolio Optimization for Sparse Financial Index Tracking. - Jasin Machkour; Daniel P. Palomar; Michael Muma (ICASSP, 2025)

The terminating-random experiments selector: Fast high-dimensional variable selection with false discovery rate control. - Jasin Machkour; Michael Muma; Daniel P. Palomar (Signal Process., 2025)

High-dimensional false discovery rate control for dependent variables. - Jasin Machkour; Michael Muma; Daniel P. Palomar (Signal Process., 2025)

Polynomial Graphical Lasso: Learning Edges From Gaussian Graph-Stationary Signals. - Andrei Buciulea; Jiaxi Ying; Antonio G. Marques; Daniel P. Palomar (IEEE Trans. Signal Process., 2025)

Time-Varying Graph Learning for Data With Heavy-Tailed Distribution. - Amirhossein Javaheri; Jiaxi Ying; Daniel P. Palomar; Farokh Marvasti (IEEE Trans. Signal Process., 2025)

Clustering of Incomplete Data via a Bipartite Graph Structure. - Amirhossein Javaheri; Daniel P. Palomar (CoRR, 2025)

Robust Filtering and Learning in State-Space Models: Skewness and Heavy Tails Via Asymmetric Laplace Distribution. - Yifan Yu; Shengjie Xiu; Daniel P. Palomar (CoRR, 2025)