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ORCIDDaniel Pérez Palomar
Daniel P. Palomar
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- affiliation: Hong Kong University of Science and Technology
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2020 – today
- 2024
[j117]Amirhossein Javaheri
, Arash Amini, Farokh Marvasti, Daniel P. Palomar:
Learning Spatiotemporal Graphical Models From Incomplete Observations. IEEE Trans. Signal Process. 72: 1361-1374 (2024)- [j116]Runhao Shi, Daniel P. Palomar:
SAOFTRL: A Novel Adaptive Algorithmic Framework for Enhancing Online Portfolio Selection. IEEE Trans. Signal Process. 72: 5291-5305 (2024) - [c117]Amirhossein Javaheri, Daniel P. Palomar:
Learning Time-Varying Graphs for Heavy-Tailed Data Clustering. EUSIPCO 2024: 2472-2476 - [c116]Jasin Machkour, Michael Muma, Daniel P. Palomar:
FDR-Controlled Sparse Index Tracking with Autoregressive Stock Dependency Models. EUSIPCO 2024: 2662-2666 - [c115]Jasin Machkour, Arnaud Breloy, Michael Muma, Daniel P. Palomar, Frédéric Pascal:
Sparse PCA with False Discovery Rate Controlled Variable Selection. ICASSP 2024: 9716-9720 - [c114]Amirhossein Javaheri, Arash Amini, Farokh Marvasti, Daniel P. Palomar:
Joint Signal Recovery and Graph Learning from Incomplete Time-Series. ICASSP 2024: 13511-13515 - [i43]Jasin Machkour, Arnaud Breloy, Michael Muma, Daniel P. Palomar, Frédéric Pascal:
Sparse PCA with False Discovery Rate Controlled Variable Selection. CoRR abs/2401.08375 (2024) - [i42]Jasin Machkour, Daniel P. Palomar, Michael Muma:
FDR-Controlled Portfolio Optimization for Sparse Financial Index Tracking. CoRR abs/2401.15139 (2024) - [i41]Andrei Buciulea, Jiaxi Ying, Antonio G. Marques, Daniel P. Palomar:
Polynomial Graphical Lasso: Learning Edges from Gaussian Graph-Stationary Signals. CoRR abs/2404.02621 (2024) - 2023
- [j115]Esa Ollila, Daniel P. Palomar, Frédéric Pascal:
Affine Equivariant Tyler's M-Estimator Applied to Tail Parameter Learning of Elliptical Distributions. IEEE Signal Process. Lett. 30: 1017-1021 (2023) - [j114]Shengjie Xiu, Xiwen Wang, Daniel P. Palomar:
A Fast Successive QP Algorithm for General Mean-Variance Portfolio Optimization. IEEE Trans. Signal Process. 71: 2713-2727 (2023) - [j113]Xiwen Wang, Rui Zhou, Jiaxi Ying, Daniel P. Palomar:
Efficient and Scalable Parametric High-Order Portfolios Design via the Skew-$t$ Distribution. IEEE Trans. Signal Process. 71: 3726-3740 (2023) - [c113]Jasin Machkour, Michael Muma, Daniel P. Palomar:
The Informed Elastic Net for Fast Grouped Variable Selection and FDR Control in Genomics Research. CAMSAP 2023: 466-470 - [c112]Amirhossein Javaheri, José Vinícius de Miranda Cardoso, Daniel P. Palomar:
Graph Learning for Balanced Clustering of Heavy-Tailed Data. CAMSAP 2023: 481-485 - [c111]Shengjie Xiu, Daniel P. Palomar:
Intraday Volatility-Volume Joint Modeling and Forecasting: A State-Space Approach. EUSIPCO 2023: 1395-1399 - [c110]José Vinícius de Miranda Cardoso, Jiaxi Ying, Sandeep Kumar, Daniel P. Palomar:
Estimating Normalized Graph Laplacians in Financial Markets. ICASSP 2023: 1-5 - [c109]Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar:
Adaptive Estimation of Graphical Models under Total Positivity. ICML 2023: 40054-40074 - [c108]Jianfeng Cai, José Vinícius de Miranda Cardoso, Daniel P. Palomar, Jiaxi Ying:
Fast Projected Newton-like Method for Precision Matrix Estimation under Total Positivity. NeurIPS 2023 - [c107]Xiwen Wang, Jiaxi Ying, Daniel P. Palomar:
Learning Large-Scale MTP2 Gaussian Graphical Models via Bridge-Block Decomposition. NeurIPS 2023 - [c106]Chenyu Gao, Ziping Zhao, Daniel P. Palomar:
A Novel Algorithm for GARCH Model Estimation. SSP 2023: 210-214 - [c105]Jasin Machkour, Michael Muma, Daniel P. Palomar:
False Discovery Rate Control for Fast Screening of Large-Scale Genomics Biobanks. SSP 2023: 666-670 - [i40]Xiwen Wang, Jiaxi Ying, Daniel P. Palomar:
Learning Large-Scale MTP2 Gaussian Graphical Models via Bridge-Block Decomposition. CoRR abs/2309.13405 (2023) - [i39]Zepeng Zhang, Ziping Zhao, Kaiming Shen, Daniel P. Palomar, Wei Yu:
Discerning and Enhancing the Weighted Sum-Rate Maximization Algorithms in Communications. CoRR abs/2311.04546 (2023) - [i38]Amirhossein Javaheri, Arash Amini, Farokh Marvasti, Daniel P. Palomar:
Joint Signal Recovery and Graph Learning from Incomplete Time-Series. CoRR abs/2312.16940 (2023) - 2022
- [j112]Rui Zhou, Jiaxi Ying, Daniel P. Palomar:
Covariance Matrix Estimation Under Low-Rank Factor Model With Nonnegative Correlations. IEEE Trans. Signal Process. 70: 4020-4030 (2022) - [c104]Xiwen Wang, Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar:
Efficient Algorithms for General Isotone Optimization. AAAI 2022: 8575-8583 - [c103]Jasin Machkour, Michael Muma, Daniel P. Palomar:
False Discovery Rate Control for Grouped Variable Selection in High-Dimensional Linear Models Using the T-Knock Filter. EUSIPCO 2022: 892-896 - [c102]José Vinícius de Miranda Cardoso, Jiaxi Ying, Daniel P. Palomar:
Learning Bipartite Graphs: Heavy Tails and Multiple Components. NeurIPS 2022 - [i37]Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar:
Adaptive Estimation of MTP2 Graphical Models. CoRR abs/2210.15471 (2022) - 2021
- [j111]Esa Ollila, Daniel P. Palomar, Frédéric Pascal:
Shrinking the Eigenvalues of M-Estimators of Covariance Matrix. IEEE Trans. Signal Process. 69: 256-269 (2021) - [j110]Rui Zhou, Daniel P. Palomar:
Solving High-Order Portfolios via Successive Convex Approximation Algorithms. IEEE Trans. Signal Process. 69: 892-904 (2021) - [j109]Arnaud Breloy, Sandeep Kumar, Ying Sun, Daniel P. Palomar:
Majorization-Minimization on the Stiefel Manifold With Application to Robust Sparse PCA. IEEE Trans. Signal Process. 69: 1507-1520 (2021) - [c101]Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar:
A Fast Algorithm for Graph Learning under Attractive Gaussian Markov Random Fields. ACSCC 2021: 1520-1524 - [c100]Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar:
Minimax Estimation of Laplacian Constrained Precision Matrices. AISTATS 2021: 3736-3744 - [c99]Frédéric Pascal, Esa Ollila, Daniel P. Palomar:
Improved estimation of the degree of freedom parameter of multivariate $t$-distribution. EUSIPCO 2021: 860-864 - [c98]Rui Zhou, Junyan Liu, Sandeep Kumar, Daniel P. Palomar:
Parameter Estimation for Student's t VAR Model with Missing Data. ICASSP 2021: 5145-5149 - [c97]José Vinícius de Miranda Cardoso, Jiaxi Ying, Daniel P. Palomar:
Graphical Models in Heavy-Tailed Markets. NeurIPS 2021: 19989-20001 - [i36]Jiaxi Ying, José Vinícius de Miranda Cardoso, Jian-Feng Cai, Daniel P. Palomar:
Fast Projected Newton-like Method for Precision Matrix Estimation with Nonnegative Partial Correlations. CoRR abs/2112.01939 (2021) - 2020
- [j108]Sandeep Kumar, Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar:
A Unified Framework for Structured Graph Learning via Spectral Constraints. J. Mach. Learn. Res. 21: 22:1-22:60 (2020) - [j107]Linlong Wu, Yiyong Feng, Daniel P. Palomar:
General sparse risk parity portfolio design via successive convex optimization. Signal Process. 170: 107433 (2020) - [j106]Rui Zhou, Daniel P. Palomar:
Understanding the Quintile Portfolio. IEEE Trans. Signal Process. 68: 4030-4040 (2020) - [j105]Rui Zhou, Junyan Liu, Sandeep Kumar, Daniel P. Palomar:
Student's $t$ VAR Modeling With Missing Data Via Stochastic EM and Gibbs Sampling. IEEE Trans. Signal Process. 68: 6198-6211 (2020) - [c96]José Vinícius de Miranda Cardoso, Daniel P. Palomar:
Learning Undirected Graphs in Financial Markets. ACSSC 2020: 741-745 - [c95]Esa Ollila, Daniel P. Palomar, Frédéric Pascal:
M-Estimators of Scatter with Eigenvalue Shrinkage. ICASSP 2020: 5305-5309 - [c94]Rui Zhou, Daniel P. Palomar:
A Theoretical Basis for Practitioners Heuristic 1/N and Long-Only Quintile Portfolio. ICASSP 2020: 8434-8438 - [c93]Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar:
Nonconvex Sparse Graph Learning under Laplacian Constrained Graphical Model. NeurIPS 2020 - [i35]Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar:
Does the 𝓁1-norm Learn a Sparse Graph under Laplacian Constrained Graphical Models? CoRR abs/2006.14925 (2020) - [i34]José Vinícius de Miranda Cardoso, Jiaxi Ying, Daniel Pérez Palomar:
Algorithms for Learning Graphs in Financial Markets. CoRR abs/2012.15410 (2020)
2010 – 2019
- 2019
- [j104]Junyan Liu, Daniel P. Palomar:
Regularized robust estimation of mean and covariance matrix for incomplete data. Signal Process. 165: 278-291 (2019) - [j103]Kaiming Shen, Wei Yu, Licheng Zhao, Daniel P. Palomar:
Optimization of MIMO Device-to-Device Networks via Matrix Fractional Programming: A Minorization-Maximization Approach. IEEE/ACM Trans. Netw. 27(5): 2164-2177 (2019) - [j102]Ziping Zhao, Rui Zhou, Daniel P. Palomar:
Optimal Mean-Reverting Portfolio With Leverage Constraint for Statistical Arbitrage in Finance. IEEE Trans. Signal Process. 67(7): 1681-1695 (2019) - [j101]Junyan Liu, Sandeep Kumar, Daniel P. Palomar:
Parameter Estimation of Heavy-Tailed AR Model With Missing Data Via Stochastic EM. IEEE Trans. Signal Process. 67(8): 2159-2172 (2019) - [j100]Licheng Zhao, Yiwei Wang, Sandeep Kumar, Daniel P. Palomar:
Optimization Algorithms for Graph Laplacian Estimation via ADMM and MM. IEEE Trans. Signal Process. 67(16): 4231-4244 (2019) - [j99]Linlong Wu, Daniel P. Palomar:
Sequence Design for Spectral Shaping via Minimization of Regularized Spectral Level Ratio. IEEE Trans. Signal Process. 67(18): 4683-4695 (2019) - [c92]Sandeep Kumar, Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar:
Bipartite Structured Gaussian Graphical Modeling via Adjacency Spectral Priors. ACSSC 2019: 322-326 - [c91]Rui Zhou, Daniel P. Palomar:
Accelerating the Multivariate SKEW T Parameter Estimation. CAMSAP 2019: 251-255 - [c90]Rui Zhou, Junyan Liu, Sandeep Kumar, Daniel P. Palomar:
Robust Factor Analysis Parameter Estimation. EUROCAST (2) 2019: 3-11 - [c89]Junyan Liu, Sandeep Kumar, Daniel P. Palomar:
Parameter Estimation of Heavy-Tailed AR(p) Model from Incomplete Data. EUSIPCO 2019: 1-5 - [c88]Ziping Zhao, Daniel P. Palomar:
Large-Scale Regularized Portfolio Selection Via Convex Optimization. GlobalSIP 2019: 1-5 - [c87]Rui Zhou, Ziping Zhao, Daniel P. Palomar:
Unified Framework for Minimax MIMO Transmit Beampattern Matching under Waveform Constraints. ICASSP 2019: 4150-4154 - [c86]Sandeep Kumar, Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar:
Structured Graph Learning Via Laplacian Spectral Constraints. NeurIPS 2019: 11647-11658 - [i33]Sandeep Kumar, Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar:
A Unified Framework for Structured Graph Learning via Spectral Constraints. CoRR abs/1904.09792 (2019) - [i32]Sandeep Kumar, Ketan Rajawat, Daniel P. Palomar:
Distributed Inexact Successive Convex Approximation ADMM: Analysis-Part I. CoRR abs/1907.08969 (2019) - [i31]Sandeep Kumar, Jiaxi Ying, José Vinícius de Miranda Cardoso, Daniel P. Palomar:
Structured Graph Learning Via Laplacian Spectral Constraints. CoRR abs/1909.11594 (2019) - 2018
- [j98]Konstantinos Benidis, Yiyong Feng, Daniel P. Palomar:
Optimization Methods for Financial Index Tracking: From Theory to Practice. Found. Trends Optim. 3(3): 171-279 (2018) - [j97]Konstantinos Benidis, Yiyong Feng, Daniel P. Palomar:
Sparse Portfolios for High-Dimensional Financial Index Tracking. IEEE Trans. Signal Process. 66(1): 155-170 (2018) - [j96]Linlong Wu, Prabhu Babu, Daniel P. Palomar:
Transmit Waveform/Receive Filter Design for MIMO Radar With Multiple Waveform Constraints. IEEE Trans. Signal Process. 66(6): 1526-1540 (2018) - [j95]Tianyu Qiu, Xiao Fu, Nicholas D. Sidiropoulos, Daniel P. Palomar:
MISO Channel Estimation and Tracking from Received Signal Strength Feedback. IEEE Trans. Signal Process. 66(7): 1691-1704 (2018) - [j94]Ziping Zhao, Daniel P. Palomar:
Mean-Reverting Portfolio With Budget Constraint. IEEE Trans. Signal Process. 66(9): 2342-2357 (2018) - [j93]Licheng Zhao, Daniel P. Palomar:
A Markowitz Portfolio Approach to Options Trading. IEEE Trans. Signal Process. 66(16): 4223-4238 (2018) - [c85]Ziping Zhao, Songtao Lu, Mingyi Hong, Daniel P. Palomar:
Distributed optimization for Generalized Phase Retrieval Over Networks. ACSSC 2018: 48-52 - [c84]Ziping Zhao, Daniel P. Palomar:
MIMO Transmit Beampattern Matching Under Waveform Constraints. ICASSP 2018: 3281-3285 - [c83]Junyan Liu, Sandeep Kumar, Daniel P. Palomar:
Parameter Estimation of Heavy-Tailed Random Walk Model from Incomplete Data. ICASSP 2018: 4439-4443 - [c82]Ziping Zhao, Rui Zhou, Zhongju Wang, Daniel P. Palomar:
Optimal Portfolio Design for Statistical Arbitrage in Finance. SSP 2018: 801-805 - [c81]Ziping Zhao, Daniel P. Palomar:
Sparse Reduced Rank Regression with Nonconvex Regularization. SSP 2018: 811-815 - [i30]Ziping Zhao, Daniel P. Palomar:
MIMO Transmit Beampattern Matching Under Waveform Constraints. CoRR abs/1802.06957 (2018) - [i29]Ziping Zhao, Daniel P. Palomar:
Sparse Reduced Rank Regression With Nonconvex Regularization. CoRR abs/1803.07247 (2018) - [i28]Kaiming Shen, Wei Yu, Licheng Zhao, Daniel P. Palomar:
Coordinated Scheduling and Spectrum Sharing via Matrix Fractional Programming. CoRR abs/1808.05678 (2018) - 2017
- [j92]Abdelhak M. Zoubir, Jorge Plata-Chaves, Daniel Pérez Palomar, Anna Scaglione, Alejandro Ribeiro:
Introduction to the Issue on Cooperative Signal Processing for Heterogeneous and Multi-Task Wireless Sensor Networks. IEEE J. Sel. Top. Signal Process. 11(3): 447-449 (2017) - [j91]Javier Rubio, Antonio Pascual-Iserte, Daniel P. Palomar, Andrea Goldsmith:
Joint Optimization of Power and Data Transfer in Multiuser MIMO Systems. IEEE Trans. Signal Process. 65(1): 212-227 (2017) - [j90]Licheng Zhao, Junxiao Song, Prabhu Babu, Daniel P. Palomar:
A Unified Framework for Low Autocorrelation Sequence Design via Majorization-Minimization. IEEE Trans. Signal Process. 65(2): 438-453 (2017) - [j89]Linlong Wu, Prabhu Babu, Daniel P. Palomar:
Cognitive Radar-Based Sequence Design via SINR Maximization. IEEE Trans. Signal Process. 65(3): 779-793 (2017) - [j88]Ying Sun, Prabhu Babu, Daniel P. Palomar:
Majorization-Minimization Algorithms in Signal Processing, Communications, and Machine Learning. IEEE Trans. Signal Process. 65(3): 794-816 (2017) - [j87]Licheng Zhao, Daniel P. Palomar:
Maximin Joint Optimization of Transmitting Code and Receiving Filter in Radar and Communications. IEEE Trans. Signal Process. 65(4): 850-863 (2017) - [j86]Zhongju Wang, Prabhu Babu, Daniel P. Palomar:
Effective Low-Complexity Optimization Methods for Joint Phase Noise and Channel Estimation in OFDM. IEEE Trans. Signal Process. 65(12): 3247-3260 (2017) - [c80]Junyan Liu, Daniel P. Palomar:
Robust estimation of mean and covariance matrix for incomplete data in financial applications. GlobalSIP 2017: 908-912 - [c79]Ziping Zhao, Daniel P. Palomar:
Robust maximum likelihood estimation of sparse vector error correction model. GlobalSIP 2017: 913-917 - [c78]Zhongju Wang, Prabhu Babu, Daniel P. Palomar:
A low-complexity algorithm for OFDM phase noise estimation. SPAWC 2017: 1-5 - [c77]Linlong Wu, Prabhu Babu, Daniel P. Palomar:
A fast algorithm for joint design of transmit waveforms and receive filters. SPAWC 2017: 1-5 - [i27]Ziping Zhao, Daniel P. Palomar:
Robust Maximum Likelihood Estimation of Sparse Vector Error Correction Model. CoRR abs/1710.05513 (2017) - 2016
- [j85]Yiyong Feng, Daniel P. Palomar:
A Signal Processing Perspective of Financial Engineering. Found. Trends Signal Process. 9(1-2) (2016) - [j84]Ali N. Akansu, Dmitry Malioutov, Daniel P. Palomar, Emmanuelle Jay, Danilo P. Mandic:
Introduction to the Issue on Financial Signal Processing and Machine Learning for Electronic Trading. IEEE J. Sel. Top. Signal Process. 10(6): 979-981 (2016) - [j83]Yang Yang, Marius Pesavento, Mengyi Zhang, Daniel P. Palomar:
An Online Parallel Algorithm for Recursive Estimation of Sparse Signals. IEEE Trans. Signal Inf. Process. over Networks 2(3): 290-305 (2016) - [j82]Ying Sun, Arnaud Breloy, Prabhu Babu, Daniel P. Palomar, Frédéric Pascal, Guillaume Ginolhac:
Low-Complexity Algorithms for Low Rank Clutter Parameters Estimation in Radar Systems. IEEE Trans. Signal Process. 64(8): 1986-1998 (2016) - [j81]Junxiao Song, Prabhu Babu, Daniel P. Palomar:
Sequence Design to Minimize the Weighted Integrated and Peak Sidelobe Levels. IEEE Trans. Signal Process. 64(8): 2051-2064 (2016) - [j80]Junxiao Song, Prabhu Babu, Daniel P. Palomar:
Sequence Set Design With Good Correlation Properties Via Majorization-Minimization. IEEE Trans. Signal Process. 64(11): 2866-2879 (2016) - [j79]Yang Yang, Gesualdo Scutari, Daniel P. Palomar, Marius Pesavento:
A Parallel Decomposition Method for Nonconvex Stochastic Multi-Agent Optimization Problems. IEEE Trans. Signal Process. 64(11): 2949-2964 (2016) - [j78]Ying Sun, Prabhu Babu, Daniel Pérez Palomar:
Robust Estimation of Structured Covariance Matrix for Heavy-Tailed Elliptical Distributions. IEEE Trans. Signal Process. 64(14): 3576-3590 (2016) - [j77]Licheng Zhao, Prabhu Babu, Daniel P. Palomar:
Efficient Algorithms on Robust Low-Rank Matrix Completion Against Outliers. IEEE Trans. Signal Process. 64(18): 4767-4780 (2016) - [j76]Tianyu Qiu, Prabhu Babu, Daniel Pérez Palomar:
PRIME: Phase Retrieval via Majorization-Minimization. IEEE Trans. Signal Process. 64(19): 5174-5186 (2016) - [j75]Zhongju Wang, Prabhu Babu, Daniel P. Palomar:
Design of PAR-Constrained Sequences for MIMO Channel Estimation via Majorization-Minimization. IEEE Trans. Signal Process. 64(23): 6132-6144 (2016) - [j74]Konstantinos Benidis, Ying Sun, Prabhu Babu, Daniel P. Palomar:
Orthogonal Sparse PCA and Covariance Estimation via Procrustes Reformulation. IEEE Trans. Signal Process. 64(23): 6211-6226 (2016) - [j73]Maria Gregori, Miquel Payaró, Daniel Pérez Palomar:
Sum-Rate Maximization for Energy Harvesting Nodes With a Generalized Power Consumption Model. IEEE Trans. Wirel. Commun. 15(8): 5341-5354 (2016) - [c76]Ying Sun, Gesualdo Scutari, Daniel Pérez Palomar:
Distributed nonconvex multiagent optimization over time-varying networks. ACSSC 2016: 788-794 - [c75]Arnaud Breloy, Ying Sun, Prabhu Babu, Guillaume Ginolhac, Daniel Pérez Palomar:
Robust rank constrained kronecker covariance matrix estimation. ACSSC 2016: 810-814 - [c74]Ziping Zhao, Daniel P. Palomar:
Mean-reverting portfolio design via majorization-minimization method. ACSSC 2016: 1530-1534 - [c73]Arnaud Breloy, Ying Sun, Prabhu Babu, Daniel Pérez Palomar:
Block majorization-minimization algorithms for low-rank clutter subspace estimation. EUSIPCO 2016: 2186-2190 - [c72]Junxiao Song, Prabhu Babu, Daniel Pérez Palomar:
Sequence design to minimize the peak sidelobe level. ICASSP 2016: 3896-3900 - [c71]Zhongju Wang, Prabhu Babu, Daniel P. Palomar:
Optimal design of constant-modulus channel training sequences. ICASSP 2016: 3901-3905 - [c70]Konstantinos Benidis, Ying Sun, Prabhu Babu, Daniel Pérez Palomar:
Orthogonal sparse eigenvectors: A procrustes problem. ICASSP 2016: 4683-4686 - [c69]Yiyong Feng, Daniel Pérez Palomar:
Portfolio optimization with asset selection and risk parity control. ICASSP 2016: 6585-6589 - [c68]Javier Rubio, Antonio Pascual-Iserte, Daniel P. Palomar, Andrea Goldsmith:
SWIPT techniques for multiuser MIMO broadcast systems. PIMRC 2016: 1-6 - [c67]Arnaud Breloy, Ying Sun, Prabhu Babu, Guillaume Ginolhac, Daniel Pérez Palomar, Frédéric Pascal:
A robust signal subspace estimator. SSP 2016: 1-4 - [i26]Konstantinos Benidis, Ying Sun, Prabhu Babu, Daniel Pérez Palomar:
Orthogonal Sparse PCA and Covariance Estimation via Procrustes Reformulation. CoRR abs/1602.03992 (2016) - [i25]Zhongju Wang, Prabhu Babu, Daniel P. Palomar:
Design of PAR-Constrained Sequences for MIMO Channel Estimation via Majorization-Minimization. CoRR abs/1602.08877 (2016) - [i24]Javier Rubio, Antonio Pascual-Iserte, Daniel Pérez Palomar, Andrea Goldsmith:
Joint Optimization of Power and Data Transfer in Multiuser MIMO Systems. CoRR abs/1604.00434 (2016) - [i23]Ying Sun, Gesualdo Scutari, Daniel P. Palomar:
Distributed Nonconvex Multiagent Optimization Over Time-Varying Networks. CoRR abs/1607.00249 (2016) - [i22]Tianyu Qiu, Daniel P. Palomar:
Undersampled Phase Retrieval via Majorization-Minimization. CoRR abs/1609.02842 (2016) - [i21]Zhongju Wang, Prabhu Babu, Daniel P. Palomar:
Effective Low-Complexity Optimization Methods for Joint Phase Noise and Channel Estimation in OFDM. CoRR abs/1610.01433 (2016) - 2015
- [j72]Yiyong Feng, Daniel Pérez Palomar, Francisco Rubio:
Robust Optimization of Order Execution. IEEE Trans. Signal Process. 63(4): 907-920 (2015) - [j71]Junxiao Song, Prabhu Babu, Daniel Pérez Palomar:
Sparse Generalized Eigenvalue Problem Via Smooth Optimization. IEEE Trans. Signal Process. 63(7): 1627-1642 (2015) - [j70]Ying Sun, Prabhu Babu, Daniel Pérez Palomar:
Regularized Robust Estimation of Mean and Covariance Matrix Under Heavy-Tailed Distributions. IEEE Trans. Signal Process. 63(12): 3096-3109 (2015) - [j69]Junxiao Song, Prabhu Babu, Daniel Pérez Palomar:
Optimization Methods for Designing Sequences With Low Autocorrelation Sidelobes. IEEE Trans. Signal Process. 63(15): 3998-4009 (2015) - [j68]Yiyong Feng, Daniel P. Palomar:
Normalization of Linear Support Vector Machines. IEEE Trans. Signal Process. 63(17): 4673-4688 (2015) - [j67]Yiyong Feng, Daniel Pérez Palomar:
SCRIP: Successive Convex Optimization Methods for Risk Parity Portfolio Design. IEEE Trans. Signal Process. 63(19): 5285-5300 (2015) - [c66]Licheng Zhao, Prabhu Babu, Daniel Pérez Palomar:
Robust low-rank optimization for large scale problems. ACSSC 2015: 391-395 - [c65]Tianyu Qiu, Prabhu Babu, Daniel Pérez Palomar:
PRIME: Phase retrieval via majorization-minimization technique. ACSSC 2015: 1681-1685 - [c64]Yiyong Feng, Daniel Pérez Palomar:
Linear support vector machines with normalizations. ICASSP 2015: 1941-1945 - [c63]Junxiao Song, Prabhu Babu, Daniel P. Palomar:
Optimization methods for sequence design with low autocorrelation sidelobes. ICASSP 2015: 3033-3037 - [c62]Ying Sun, Prabhu Babu, Daniel Pérez Palomar:
Robust estimation of structured covariance matrix for heavy-tailed distributions. ICASSP 2015: 5693-5697 - [i20]Junxiao Song, Prabhu Babu, Daniel Pérez Palomar:
Optimization Methods for Designing Sequences with Low Autocorrelation Sidelobes. CoRR abs/1501.02252 (2015) - [i19]Tianyu Qiu, Prabhu Babu, Daniel Pérez Palomar:
PRIME: Phase Retrieval via Majorization-Minimization. CoRR abs/1511.01669 (2015) - 2014
- [j66]Gesualdo Scutari, Francisco Facchinei, Jong-Shi Pang, Daniel P. Palomar:
Real and Complex Monotone Communication Games. IEEE Trans. Inf. Theory 60(7): 4197-4231 (2014) - [j65]Benjamín Béjar Haro, Santiago Zazo, Daniel P. Palomar:
Energy Efficient Collaborative Beamforming in Wireless Sensor Networks. IEEE Trans. Signal Process. 62(2): 496-510 (2014) - [j64]Gesualdo Scutari, Francisco Facchinei, Peiran Song, Daniel P. Palomar, Jong-Shi Pang:
Decomposition by Partial Linearization: Parallel Optimization of Multi-Agent Systems. IEEE Trans. Signal Process. 62(3): 641-656 (2014) - [j63]Yongwei Huang, Daniel P. Palomar:
Randomized Algorithms for Optimal Solutions of Double-Sided QCQP With Applications in Signal Processing. IEEE Trans. Signal Process. 62(5): 1093-1108 (2014) - [j62]Italo Atzeni, Luis Garcia Ordóñez, Gesualdo Scutari, Daniel P. Palomar, Javier Rodríguez Fonollosa:
Noncooperative Day-Ahead Bidding Strategies for Demand-Side Expected Cost Minimization With Real-Time Adjustments: A GNEP Approach. IEEE Trans. Signal Process. 62(9): 2397-2412 (2014) - [j61]Ying Sun, Prabhu Babu, Daniel P. Palomar:
Regularized Tyler's Scatter Estimator: Existence, Uniqueness, and Algorithms. IEEE Trans. Signal Process. 62(19): 5143-5156 (2014) - [j60]Antonio A. D'Amico, Luca Sanguinetti, Daniel Pérez Palomar:
Convex Separable Problems With Linear Constraints in Signal Processing and Communications. IEEE Trans. Signal Process. 62(22): 6045-6058 (2014) - [c61]Junxiao Song, Prabhu Babu, Daniel P. Palomar:
A fast algorithm for sparse generalized eigenvalue problem. ACSSC 2014: 1652-1656 - [c60]Yang Yang, Mengyi Zhang, Marius Pesavento, Daniel P. Palomar:
An online parallel algorithm for spectrum sensing in cognitive radio networks. ACSSC 2014: 1801-1805 - [c59]Antonio Alberto D'Amico, Luca Sanguinetti, Daniel P. Palomar:
Convex separable problems with linear and box constraints. ICASSP 2014: 5641-5645 - [c58]Ying Sun, Prabhu Babu, Daniel Pérez Palomar:
Regularized robust estimation of mean and covariance matrix under heavy tails and outliers. SAM 2014: 125-128 - [i18]Antonio A. D'Amico, Luca Sanguinetti, Daniel P. Palomar:
Convex separable problems with linear and box constraints. CoRR abs/1403.5638 (2014) - [i17]Antonio A. D'Amico, Luca Sanguinetti, Daniel P. Palomar:
Convex separable problems with linear and box constraints in signal processing and communications. CoRR abs/1407.4477 (2014) - [i16]Junxiao Song, Prabhu Babu, Daniel Pérez Palomar:
Sparse Generalized Eigenvalue Problem via Smooth Optimization. CoRR abs/1408.6686 (2014) - [i15]Yang Yang, Gesualdo Scutari, Daniel Pérez Palomar, Marius Pesavento:
A Parallel Stochastic Approximation Method for Nonconvex Multi-Agent Optimization Problems. CoRR abs/1410.5076 (2014) - 2013
- [j59]Yang Yang, Gesualdo Scutari, Peiran Song, Daniel P. Palomar:
Robust MIMO Cognitive Radio Systems Under Interference Temperature Constraints. IEEE J. Sel. Areas Commun. 31(11): 2465-2482 (2013) - [j58]Xiaopeng Fan, Junxiao Song, Daniel P. Palomar, Oscar C. Au:
Universal Binary Semidefinite Relaxation for ML Signal Detection. IEEE Trans. Commun. 61(11): 4565-4576 (2013) - [j57]Ronit Bustin, Miquel Payaró, Daniel P. Palomar, Shlomo Shamai (Shitz):
On MMSE Crossing Properties and Implications in Parallel Vector Gaussian Channels. IEEE Trans. Inf. Theory 59(2): 818-844 (2013) - [j56]Italo Atzeni, Luis Garcia Ordóñez, Gesualdo Scutari, Daniel P. Palomar, Javier Rodríguez Fonollosa:
Demand-Side Management via Distributed Energy Generation and Storage Optimization. IEEE Trans. Smart Grid 4(2): 866-876 (2013) - [j55]Yongwei Huang, Daniel P. Palomar, Shuzhong Zhang:
Lorentz-Positive Maps and Quadratic Matrix Inequalities With Applications to Robust MISO Transmit Beamforming. IEEE Trans. Signal Process. 61(5): 1121-1130 (2013) - [j54]Mengyi Zhang, Francisco Rubio, Daniel P. Palomar:
Improved Calibration of High-Dimensional Precision Matrices. IEEE Trans. Signal Process. 61(6): 1509-1519 (2013) - [j53]Italo Atzeni, Luis Garcia Ordóñez, Gesualdo Scutari, Daniel P. Palomar, Javier Rodríguez Fonollosa:
Noncooperative and Cooperative Optimization of Distributed Energy Generation and Storage in the Demand-Side of the Smart Grid. IEEE Trans. Signal Process. 61(10): 2454-2472 (2013) - [j52]Jiaheng Wang, Mats Bengtsson, Björn E. Ottersten, Daniel P. Palomar:
Robust MIMO Precoding for Several Classes of Channel Uncertainty. IEEE Trans. Signal Process. 61(12): 3056-3070 (2013) - [j51]Mengyi Zhang, Francisco Rubio, Daniel P. Palomar, Xavier Mestre:
Finite-Sample Linear Filter Optimization in Wireless Communications and Financial Systems. IEEE Trans. Signal Process. 61(20): 5014-5025 (2013) - [j50]Yang Yang, Francisco Rubio, Gesualdo Scutari, Daniel P. Palomar:
Multi-Portfolio Optimization: A Potential Game Approach. IEEE Trans. Signal Process. 61(22): 5590-5602 (2013) - [c57]Yiyong Feng, Daniel P. Palomar:
Robust order execution under box uncertainty sets. ACSSC 2013: 44-48 - [c56]Jiaheng Wang, Mats Bengtsson, Björn E. Ottersten, Daniel P. Palomar:
Robust MIMO precoding for the schatten norm based channel uncertainty sets. GLOBECOM 2013: 3394-3399 - [c55]Mengyi Zhang, Francisco Rubio, Daniel P. Palomar, Xavier Mestre:
Robust adaptive beamforming with imprecise steering vector and noise covariance matrix due to finite sample size. ICASSP 2013: 3786-3790 - [c54]Gesualdo Scutari, Francisco Facchinei, Daniel Pérez Song, Daniel P. Palomar, Jong-Shi Pang:
Decomposition by partial linearization in multiuser systems. ICASSP 2013: 4424-4428 - [c53]Yang Yang, Peiran Song, Gesualdo Scutari, Daniel P. Palomar:
Robust MIMO cognitive radio systems under temperature interference constraints. ICASSP 2013: 4504-4508 - [c52]Italo Atzeni, Luis Garcia Ordóñez, Gesualdo Scutari, Daniel Pérez Palomar, Javier Rodríguez Fonollosa:
Cooperative day-ahead bidding strategies for demand-side expected cost minimization. ICASSP 2013: 5224-5228 - [c51]Yang Yang, Gesualdo Scutari, Daniel Pérez Palomar:
Parallel stochastic decomposition algorithms for multi-agent systems. SPAWC 2013: 180-184 - [i14]Gesualdo Scutari, Francisco Facchinei, Peiran Song, Daniel P. Palomar, Jong-Shi Pang:
Decomposition by Partial Linearization: Parallel Optimization of Multi-Agent Systems. CoRR abs/1302.0756 (2013) - 2012
- [j49]Francisco Rubio, Xavier Mestre, Daniel P. Palomar:
Performance Analysis and Optimal Selection of Large Minimum Variance Portfolios Under Estimation Risk. IEEE J. Sel. Top. Signal Process. 6(4): 337-350 (2012) - [j48]Luis Garcia Ordóñez, Daniel P. Palomar, Javier Rodríguez Fonollosa:
Array Gain in the DMT Framework for MIMO Channels. IEEE Trans. Inf. Theory 58(7): 4577-4593 (2012) - [c50]Yongwei Huang, Daniel P. Palomar, Shuzhong Zhang:
Lorentz-positive mapswith applications to robust MISO downlink beamforming. ICASSP 2012: 2801-2804 - [c49]Benjamín Béjar Haro, Santiago Zazo, Daniel P. Palomar:
Lifetime maximization for beamforming applications in wireless sensor networks. ICASSP 2012: 2849-2852 - [c48]Jiaheng Wang, Mats Bengtsson, Björn E. Ottersten, Daniel P. Palomar:
Robust maximin MIMO precoding for arbitrary convex uncertainty sets. ICASSP 2012: 3045-3048 - [c47]Mengyi Zhang, Francisco Rubio, Daniel P. Palomar:
Calibration of high-dimensional precision matrices under quadratic loss. ICASSP 2012: 3365-3368 - [c46]Italo Atzeni, Luis Garcia Ordóñez, Gesualdo Scutari, Daniel P. Palomar, Javier Rodríguez Fonollosa:
Day-ahead bidding strategies for demand-side expected cost minimization. SmartGridComm 2012: 91-96 - [c45]Yiyong Feng, Francisco Rubio, Daniel Pérez Palomar:
Optimal order execution for algorithmic trading: A CVaR approach. SPAWC 2012: 480-484 - [e2]Javier Del Ser, Eduard A. Jorswieck, Joaquín Míguez, Marja Matinmikko, Daniel P. Palomar, Sancho Salcedo-Sanz, Sergio Gil-Lopez:
Mobile Lightweight Wireless Systems - Third International ICST Conference, MOBILIGHT 2011, Bilbao, Spain, May 9-10, 2011, Revised Selected Papers. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 81, Springer 2012, ISBN 978-3-642-29478-5 [contents] - [i13]Ronit Bustin, Miquel Payaró, Daniel Pérez Palomar, Shlomo Shamai:
On MMSE Properties and I-MMSE Implications in Parallel MIMO Gaussian Channels. CoRR abs/1203.5638 (2012) - [i12]Gesualdo Scutari, Francisco Facchinei, Jong-Shi Pang, Daniel P. Palomar:
Real and Complex Monotone Communication Games. CoRR abs/1212.6235 (2012) - 2011
- [j47]Antonio De Maio, Yongwei Huang, Daniel Pérez Palomar, Shuzhong Zhang, Alfonso Farina:
Fractional QCQP With Applications in ML Steering Direction Estimation for Radar Detection. IEEE Trans. Signal Process. 59(1): 172-185 (2011) - [j46]Jiaheng Wang, Gesualdo Scutari, Daniel Pérez Palomar:
Robust MIMO Cognitive Radio Via Game Theory. IEEE Trans. Signal Process. 59(3): 1183-1201 (2011) - [j45]Javier Vía, Daniel P. Palomar, Luis Vielva:
Generalized Likelihood Ratios for Testing the Properness of Quaternion Gaussian Vectors. IEEE Trans. Signal Process. 59(4): 1356-1370 (2011) - [j44]Javier Vía, Daniel P. Palomar, Luis Vielva, Ignacio Santamaría:
Quaternion ICA From Second-Order Statistics. IEEE Trans. Signal Process. 59(4): 1586-1600 (2011) - [c44]Francisco Rubio, Xavier Mestre, Daniel Pérez Palomar:
Asymptotic analysis and consistent estimation of high-dimensional Markowitz portfolios. CAMSAP 2011: 25-28 - [c43]Yang Yang, Francisco Rubio, Gesualdo Scutari, Daniel Pérez Palomar:
Multi-portfolio Optimization: A Potential Game Approach. GAMENETS 2011: 182-189 - [c42]Luis Garcia Ordóñez, Daniel Pérez Palomar, Javier Rodríguez Fonollosa:
Fundamental diversity, multiplexing, and array gain tradeoff under different MIMO channel models. ICASSP 2011: 3252-3255 - [c41]Javier Vía, Daniel P. Palomar, Luis Vielva, Ignacio Santamaría:
Maximum likelihood ICA of quaternion Gaussian vectors. ICASSP 2011: 4260-4263 - [c40]Gesualdo Scutari, Daniel P. Palomar, Francisco Facchinei, Jong-Shi Pang:
Distributed dynamic pricing for MIMO interfering multiuser systems: A unified approach. NetGCoop 2011: 1-5 - [c39]Miquel Payaró, Maria Gregori, Daniel Pérez Palomar:
Yet another entropy power inequality with an application. WCSP 2011: 1-5 - [i11]Francisco Rubio, Xavier Mestre, Daniel P. Palomar:
Performance analysis and optimal selection of large mean-variance portfolios under estimation risk. CoRR abs/1110.3460 (2011) - 2010
- [j43]Gesualdo Scutari, Daniel Pérez Palomar, Francisco Facchinei, Jong-Shi Pang:
Convex Optimization, Game Theory, and Variational Inequality Theory. IEEE Signal Process. Mag. 27(3): 35-49 (2010) - [j42]Eduard Calvo, Daniel Pérez Palomar, Javier Rodríguez Fonollosa, Josep Vidal:
On the Computation of the Capacity Region of the Discrete MAC. IEEE Trans. Commun. 58(12): 3512-3525 (2010) - [j41]Yongwei Huang, Daniel Pérez Palomar:
Rank-constrained separable semidefinite programming with applications to optimal beamforming. IEEE Trans. Signal Process. 58(2): 664-678 (2010) - [j40]Antonio De Maio, Silvio De Nicola, Yongwei Huang, Daniel Pérez Palomar, Shuzhong Zhang, Alfonso Farina:
Code design for radar STAP via optimization theory. IEEE Trans. Signal Process. 58(2): 679-694 (2010) - [j39]Gesualdo Scutari, Daniel Pérez Palomar:
MIMO cognitive radio: a game theoretical approach. IEEE Trans. Signal Process. 58(2): 761-780 (2010) - [j38]Jong-Shi Pang, Gesualdo Scutari, Daniel Pérez Palomar, Francisco Facchinei:
Design of cognitive radio systems under temperature-interference constraints: a variational inequality approach. IEEE Trans. Signal Process. 58(6): 3251-3271 (2010) - [j37]Yongwei Huang, Daniel Pérez Palomar:
A dual perspective on separable semidefinite programming with applications to optimal downlink beamforming. IEEE Trans. Signal Process. 58(8): 4254-4271 (2010) - [j36]Jiaheng Wang, Daniel Pérez Palomar:
Robust MMSE precoding in MIMO channels with pre-fixed receivers. IEEE Trans. Signal Process. 58(11): 5802-5818 (2010) - [c38]Jong-Shi Pang, Gesualdo Scutari, Daniel Pérez Palomar, Francisco Facchinei:
Design of cognitive radio systems under temperature-interference constraints: A variational inequality approach. ICASSP 2010: 2994-2997 - [c37]Yongwei Huang, Daniel Pérez Palomar:
A dual perspective on separable semidefinite programming with applications to optimal beamforming. ICASSP 2010: 3062-3065 - [c36]Ronit Bustin, Miquel Payaró, Daniel Pérez Palomar, Shlomo Shamai:
On MMSE properties and I-MMSE implications in parallel MIMO Gaussian channels. ISIT 2010: 535-539 - [c35]Jiaheng Wang, Gesualdo Scutari, Daniel Pérez Palomar:
Robust cognitive radio via game theory. ISIT 2010: 2073-2077 - [c34]Luis Garcia Ordóñez, Daniel Pérez Palomar, Javier Rodríguez Fonollosa:
On the diversity, multiplexing, and array gain tradeoff in MIMO channels. ISIT 2010: 2183-2187 - [p1]Gesualdo Scutari, Daniel P. Palomar, Sergio Barbarossa:
Competitive optimization of cognitive radio MIMO systems via game theory. Convex Optimization in Signal Processing and Communications 2010: 387-442 - [e1]Daniel P. Palomar, Yonina C. Eldar:
Convex Optimization in Signal Processing and Communications. Cambridge University Press 2010, ISBN 978-0-521-76222-9 [contents] - [i10]Ronit Bustin, Miquel Payaró, Daniel Pérez Palomar, Shlomo Shamai:
On MMSE Properties and I-MMSE Implications in Parallel MIMO Gaussian Channels. CoRR abs/1004.4490 (2010)
2000 – 2009
- 2009
- [j35]Gesualdo Scutari, Daniel P. Palomar, Jong-Shi Pang, Francisco Facchinei:
Flexible design of cognitive radio wireless systems. IEEE Signal Process. Mag. 26(5): 107-123 (2009) - [j34]Miquel Payaró, Daniel Pérez Palomar:
Hessian and concavity of mutual information, differential entropy, and entropy power in linear vector Gaussian channels. IEEE Trans. Inf. Theory 55(8): 3613-3628 (2009) - [j33]Chee-Wei Tan, Daniel Pérez Palomar, Mung Chiang:
Energy-robustness tradeoff in cellular network power control. IEEE/ACM Trans. Netw. 17(3): 912-925 (2009) - [j32]Luis Garcia Ordóñez, Daniel Pérez Palomar, Javier Rodríguez Fonollosa:
Ordered Eigenvalues of a General Class of Hermitian Random Matrices With Application to the Performance Analysis of MIMO Systems. IEEE Trans. Signal Process. 57(2): 672-689 (2009) - [j31]Gesualdo Scutari, Daniel Pérez Palomar, Sergio Barbarossa:
The MIMO iterative waterfilling algorithm. IEEE Trans. Signal Process. 57(5): 1917-1935 (2009) - [j30]Luis Garcia Ordóñez, Daniel Pérez Palomar, Alba Pagès-Zamora, Javier Rodríguez Fonollosa:
Minimum BER linear MIMO transceivers with adaptive number of substreams. IEEE Trans. Signal Process. 57(6): 2336-2353 (2009) - [j29]Jiaheng Wang, Daniel Pérez Palomar:
Worst-case robust MIMO transmission with imperfect channel knowledge. IEEE Trans. Signal Process. 57(8): 3086-3100 (2009) - [j28]Jiaheng Wang, Daniel Pérez Palomar:
Correction to "worst-case robust MIMO transmission with imperfect channel knowledge". IEEE Trans. Signal Process. 57(10): 4159 (2009) - [j27]Svante Bergman, Daniel Pérez Palomar, Björn E. Ottersten:
Joint bit allocation and precoding for MIMO systems with decision feedback detection. IEEE Trans. Signal Process. 57(11): 4509-4521 (2009) - [c33]Gesualdo Scutari, Daniel P. Palomar, Sergio Barbarossa:
Competitive optimization of cognitive radio MIMO systems via game theory. GAMENETS 2009: 452-461 - [c32]Jiaheng Wang, Daniel Pérez Palomar:
Maximin robust design for MIMO communication systems against imperfect CSIT. ICASSP 2009: 2397-2400 - [c31]Miquel Payaró, Daniel P. Palomar:
On optimal precoding in linear vector Gaussian channels with arbitrary input distribution. ISIT 2009: 1085-1089 - [c30]Yongwei Huang, Daniel Pérez Palomar:
Rank-constrained separable semidefinite programming for optimal beamforming design. ISIT 2009: 2432-2436 - [c29]Svante Bergman, Daniel Pérez Palomar, Björn E. Ottersten:
Optimal Bit Loading for MIMO Systems with Decision Feedback Detection. VTC Spring 2009 - [i9]Miquel Payaró, Daniel Pérez Palomar:
Hessian and concavity of mutual information, differential entropy, and entropy power in linear vector Gaussian channels. CoRR abs/0903.1945 (2009) - [i8]Miquel Payaró, Daniel Pérez Palomar:
On optimal precoding in linear vector Gaussian channels with arbitrary input distribution. CoRR abs/0904.4900 (2009) - 2008
- [j26]Narayan B. Mandayam, Stephen B. Wicker, Jean C. Walrand, Tamer Basar, Jianwei Huang, Daniel Pérez Palomar:
Game Theory in Communication Systems [Guest Editorial]. IEEE J. Sel. Areas Commun. 26(7): 1042-1046 (2008) - [j25]Gesualdo Scutari, Daniel Pérez Palomar, Sergio Barbarossa:
Competitive Design of Multiuser MIMO Systems Based on Game Theory: A Unified View. IEEE J. Sel. Areas Commun. 26(7): 1089-1103 (2008) - [j24]Gesualdo Scutari, Daniel P. Palomar, Sergio Barbarossa:
Cognitive MIMO radio. IEEE Signal Process. Mag. 25(6): 46-59 (2008) - [j23]Daniel Pérez Palomar, Sergio Verdú:
Lautum Information. IEEE Trans. Inf. Theory 54(3): 964-975 (2008) - [j22]Gesualdo Scutari, Daniel Pérez Palomar, Sergio Barbarossa:
Asynchronous Iterative Water-Filling for Gaussian Frequency-Selective Interference Channels. IEEE Trans. Inf. Theory 54(7): 2868-2878 (2008) - [j21]Gesualdo Scutari, Daniel Pérez Palomar, Sergio Barbarossa:
Optimal Linear Precoding Strategies for Wideband Noncooperative Systems Based on Game Theory - Part I: Nash Equilibria. IEEE Trans. Signal Process. 56(3): 1230-1249 (2008) - [j20]Gesualdo Scutari, Daniel Pérez Palomar, Sergio Barbarossa:
Optimal Linear Precoding Strategies for Wideband Non-Cooperative Systems Based on Game Theory - Part II: Algorithms. IEEE Trans. Signal Process. 56(3): 1250-1267 (2008) - [j19]Xi Zhang, Daniel Pérez Palomar, Björn E. Ottersten:
Statistically Robust Design of Linear MIMO Transceivers. IEEE Trans. Signal Process. 56(8-1): 3678-3689 (2008) - [c28]Gesualdo Scutari, Daniel Pérez Palomar, Sergio Barbarossa:
Competitive design of multiuser MIMO interference systems based on game theory: A unified framework. ICASSP 2008: 5376-5379 - [c27]Luis Garcia Ordóñez, Daniel Pérez Palomar, Javier Rodríguez Fonollosa:
Ordered Eigenvalues of a General Class of Hermitian Random Matrices and Performance Analysis of MIMO Systems. ICC 2008: 3846-3852 - [c26]Liwei Guo, Oscar C. Au, Mengyao Ma, Xiaopeng Fan, Peter H. W. Wong, Daniel Pérez Palomar:
Image deblocking using convex optimization. ICIP 2008: 3148-3151 - [c25]Miquel Payaró, Daniel P. Palomar:
A multivariate generalization of Costa's entropy power inequality. ISIT 2008: 1088-1092 - [c24]Eduard Calvo, Daniel Pérez Palomar, Javier Rodríguez Fonollosa, Josep Vidal:
The computation of the capacity region of the discrete degraded BC is a nonconvex DC problem. ISIT 2008: 1721-1725 - [i7]Gesualdo Scutari, Daniel Pérez Palomar, Sergio Barbarossa:
Asynchronous Iterative Waterfilling for Gaussian Frequency-Selective Interference Channels. CoRR abs/0801.2480 (2008) - [i6]Miquel Payaró, Daniel Pérez Palomar:
A multivariate generalization of Costa's entropy power inequality. CoRR abs/0804.4517 (2008) - [i5]Gesualdo Scutari, Daniel Pérez Palomar, Sergio Barbarossa:
Competitive Design of Multiuser MIMO Systems based on Game Theory: A Unified View. CoRR abs/0806.1565 (2008) - [i4]Gesualdo Scutari, Daniel Pérez Palomar, Sergio Barbarossa:
Cognitive MIMO Radio: A Competitive Optimality Design Based on Subspace Projections. CoRR abs/0808.0978 (2008) - [i3]Gesualdo Scutari, Daniel Pérez Palomar, Sergio Barbarossa:
The MIMO Iterative Waterfilling Algorithm. CoRR abs/0812.2324 (2008) - 2007
- [j18]Daniel P. Palomar, Mung Chiang:
Alternative Distributed Algorithms for Network Utility Maximization: Framework and Applications. IEEE Trans. Autom. Control. 52(12): 2254-2269 (2007) - [j17]Daniel Pérez Palomar, Sergio Verdú:
Representation of Mutual Information Via Input Estimates. IEEE Trans. Inf. Theory 53(2): 453-470 (2007) - [j16]Luis Garcia Ordóñez, Daniel Pérez Palomar, Alba Pagès-Zamora, Javier Rodríguez Fonollosa:
High-SNR Analytical Performance of Spatial Multiplexing MIMO Systems With CSI. IEEE Trans. Signal Process. 55(11): 5447-5463 (2007) - [j15]Mung Chiang, Chee-Wei Tan, Daniel Pérez Palomar, Daniel O'Neill, David Julian:
Power Control By Geometric Programming. IEEE Trans. Wirel. Commun. 6(7): 2640-2651 (2007) - [c23]Yi Jiang, Daniel Pérez Palomar, Mahesh K. Varanasi:
Precoder Optimization for Nonlinear MIMO Transceiver Based on Arbitrary Cost Function. CISS 2007: 119-124 - [c22]Luis Garcia Ordóñez, Daniel P. Palomar, Alba Pagès-Zamora, Javier Rodríguez Fonollosa:
On Equal Constellation Minimum BER linear MIMO Transceivers. ICASSP (3) 2007: 221-224 - [c21]Are Hjørungnes, David Gesbert, Daniel P. Palomar:
Unified Theory of Complex-Valued Matrix Differentiation. ICASSP (3) 2007: 345-348 - [c20]Gesualdo Scutari, Daniel P. Palomar, Sergio Barbarossa:
Distributed Totally Asynchronous Iterative Waterfilling for Wideband Interference Channel with Time/Frequency Offset. ICASSP (4) 2007: 1325-1328 - [c19]Chee-Wei Tan, Daniel Pérez Palomar, Mung Chiang:
Exploiting Hidden Convexity For Flexible And Robust Resource Allocation In Cellular Networks. INFOCOM 2007: 964-972 - [c18]Eduard Calvo, Daniel P. Palomar, Javier Rodríguez Fonollosa, Josep Vidal:
The Computation of the Capacity Region of the Discrete MAC is a Rank-One Non-Convex Optimization Problem. ISIT 2007: 2396-2400 - [i2]Gesualdo Scutari, Daniel Pérez Palomar, Sergio Barbarossa:
Optimal Linear Precoding Strategies for Wideband Non-Cooperative Systems based on Game Theory-Part I: Nash Equilibria. CoRR abs/0707.0568 (2007) - [i1]Gesualdo Scutari, Daniel Pérez Palomar, Sergio Barbarossa:
Optimal Linear Precoding Strategies for Wideband Non-Cooperative Systems based on Game Theory-Part II: Algorithms. CoRR abs/0707.0871 (2007) - 2006
- [j14]Daniel Pérez Palomar, Yi Jiang:
MIMO Transceiver Design via Majorization Theory. Found. Trends Commun. Inf. Theory 3(4/5) (2006) - [j13]Daniel Pérez Palomar, Mung Chiang:
A Tutorial on Decomposition Methods for Network Utility Maximization. IEEE J. Sel. Areas Commun. 24(8): 1439-1451 (2006) - [j12]Daniel Pérez Palomar, Sergio Verdú:
Gradient of mutual information in linear vector Gaussian channels. IEEE Trans. Inf. Theory 52(1): 141-154 (2006) - [j11]Antonio Pascual-Iserte, Daniel Pérez Palomar, Ana I. Pérez-Neira, Miguel Angel Lagunas:
A robust maximin approach for MIMO communications with imperfect channel state information based on convex optimization. IEEE Trans. Signal Process. 54(1): 346-360 (2006) - [c17]Xi Zhang, Daniel P. Palomar, Björn E. Ottersten:
Robust Design of Linear Mimo Transceivers Under Channel Uncertainty. ICASSP (4) 2006: 77-80 - [c16]Gesualdo Scutari, Sergio Barbarossa, Daniel P. Palomar:
Potential Games: A Framework for Vector Power Control Problems With Coupled Constraints. ICASSP (4) 2006: 241-244 - [c15]Chee Wei Tan, Daniel P. Palomar, Mung Chiang:
Distributed Optimization of Coupled Systems With Applications to Network Utility Maximization. ICASSP (5) 2006: 981-984 - [c14]Daniel Pérez Palomar, Mung Chiang:
Alternative Decompositions for Distributed Maximization of Network Utility: Framework and Applications. INFOCOM 2006 - [c13]Gesualdo Scutari, Daniel P. Palomar, Sergio Barbarossa:
Simultaneous Iterative Water-Filling for Gaussian Frequency-Selective Interference Channels. ISIT 2006: 600-604 - [c12]Daniel P. Palomar, Sergio Verdú:
Lautum Information. ITW 2006: 1-5 - 2005
- [j10]Daniel Pérez Palomar, Javier Rodríguez Fonollosa:
Practical algorithms for a family of waterfilling solutions. IEEE Trans. Signal Process. 53(2-1): 686-695 (2005) - [j9]Daniel Pérez Palomar, Mats Bengtsson, Björn E. Ottersten:
Minimum BER linear transceivers for MIMO channels via primal decomposition. IEEE Trans. Signal Process. 53(8-1): 2866-2882 (2005) - [j8]Daniel Pérez Palomar, Sergio Barbarossa:
Designing MIMO communication systems: constellation choice and linear transceiver design. IEEE Trans. Signal Process. 53(10): 3804-3818 (2005) - [j7]Daniel Pérez Palomar:
Convex primal decomposition for multicarrier linear MIMO transceivers. IEEE Trans. Signal Process. 53(12): 4661-4674 (2005) - [c11]Daniel P. Palomar, Mung Chiang:
Alternative decompositions and distributed algorithms for network utility maximization. GLOBECOM 2005: 6 - [c10]Chee Wei Tan, Daniel P. Palomar, Mung Chiang:
Solving nonconvex power control problems in wireless networks: low SIR regime and distributed algorithms. GLOBECOM 2005: 6 - [c9]Daniel P. Palomar, Sergio Verdú:
Gradient of mutual information in linear vector Gaussian channels. ISIT 2005: 705-708 - [c8]Mung Chiang, Jang-Won Lee, A. Robert Calderbank, Daniel Pérez Palomar, Maryam Fazel:
Network utility maximization with nonconcave, coupled, and reliability-based uilities. SIGMETRICS 2005: 277 - 2004
- [j6]Daniel Pérez Palomar:
Unified framework for linear MIMO transceivers with shaping constraints. IEEE Commun. Lett. 8(12): 697-699 (2004) - [j5]Daniel Pérez Palomar, Miguel Angel Lagunas, John M. Cioffi:
Optimum linear joint transmit-receive processing for MIMO channels with QoS constraints. IEEE Trans. Signal Process. 52(5): 1179-1197 (2004) - 2003
- [j4]Daniel Pérez Palomar, Miguel Angel Lagunas:
Joint transmit-receive space-time equalization in spatially correlated MIMO channels: a beamforming approach. IEEE J. Sel. Areas Commun. 21(5): 730-743 (2003) - [j3]Daniel Pérez Palomar, John M. Cioffi, Miguel Angel Lagunas:
Uniform power allocation in MIMO channels: a game-theoretic approach. IEEE Trans. Inf. Theory 49(7): 1707-1727 (2003) - [j2]Daniel Pérez Palomar, John M. Cioffi, Miguel Angel Lagunas:
Joint Tx-Rx beamforming design for multicarrier MIMO channels: a unified framework for convex optimization. IEEE Trans. Signal Process. 51(9): 2381-2401 (2003) - [c7]Daniel Pérez Palomar, John M. Cioffi, Miguel Angel Lagunas, Antonio Pascual-Iserte:
Convex optimization theory applied to joint beamforming design in multicarrier MIMO channels. ICC 2003: 2974-2978 - [c6]Diego Bartolomé, Daniel P. Palomar, Ana I. Pérez-Neira:
Real-time scheduling for wireless multiuser MISO systems under different fairness criteria. ISSPA (1) 2003: 213-216 - 2002
- [c5]Antonio Pascual-Iserte, Ana I. Pérez-Neira, Daniel Pérez Palomar, Miguel Angel Lagunas:
Power allocation techniques for joint beamforming in OFDM-MIMO channels. EUSIPCO 2002: 1-4 - 2001
- [j1]Daniel Pérez Palomar, Miguel Angel Lagunas:
Temporal diversity on DS-CDMA communication systems for blind array signal processing. Signal Process. 81(8): 1625-1640 (2001) - [c4]Daniel Pérez Palomar, Miguel Angel Lagunas, Antonio Pascual-Iserte, Ana I. Pérez-Neira:
Practical implementation of jointly designed transmit receive space-time IIR filters. ISSPA 2001: 521-524 - [c3]Daniel Pérez Palomar, Javier Rodríguez Fonollosa, Miguel Angel Lagunas:
Capacity results of spatially correlated frequency-selective MIMO channels in UMTS. VTC Fall 2001: 553-557 - 2000
- [c2]Daniel Pérez Palomar, Miguel Angel Lagunas:
Optimum self-reference spatial diversity processing for FDSS and FH communication systems. EUSIPCO 2000: 1-4 - [c1]Daniel Pérez Palomar, Miguel Angel Lagunas:
Self-reference beamforming for DS-CDMA communication systems. ICASSP 2000: 3001-3004
Coauthor Index
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to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-12-23 19:28 CET by the dblp team
all metadata released as open data under CC0 1.0 license
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since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
