Ricard Gavaldà

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All published works

Action	Title	Year	Authors
+	Compressibility of Infinite Binary Sequences	2019	José L. Balcázar Ricard Gavaldà Montserrat Hermo
+ PDF Chat	A new method of moments for latent variable models	2018	Matteo Ruffini Marta Casanellas Ricard Gavaldà
+	Generating Synthetic but Plausible Healthcare Record Datasets	2018	Laura J. Avino Matteo Ruffini Ricard Gavaldà
+	Clustering patients with tensor decomposition	2017	Matteo Ruffini Ricard Gavaldà Esther Limón
+	Clustering Patients with Tensor Decomposition	2017	Matteo Ruffini Ricard Gavaldà Esther Limón
+	Clustering Patients with Tensor Decomposition	2017	Matteo Ruffini Ricard Gavaldà Esther Limón Ramírez
+	Identifiability and Transportability in Dynamic Causal Networks	2016	Gilles Blondel Marta Arias Ricard Gavaldà
+ PDF Chat	Identifiability and transportability in dynamic causal networks	2016	Gilles Blondel Marta Arias Ricard Gavaldà
+	A New Spectral Method for Latent Variable Models	2016	Matteo Ruffini Marta Casanellas Ricard Gavaldà
+	Identifiability and Transportability in Dynamic Causal Networks	2016	Gilles Blondel Marta Arias Ricard Gavaldà
+ PDF Chat	Visual summary of egocentric photostreams by representative keyframes	2015	Marc Bolaños Ricard Gavaldà Estefanía Talavera Xavier Giró-i-Nieto Petia Radeva
+	Visual Summary of Egocentric Photostreams by Representative Keyframes	2015	Marc Bolaños Ricard Gavaldà Estefanía Talavera Xavier Giró-i-Nieto Petia Radeva
+	Visual Summary of Egocentric Photostreams by Representative Keyframes	2015	Marc Bolaños Ricard Gavaldà Estefanía Talavera Xavier Giró-i-Nieto Petia Radeva
+	Resource-bounded Dimension in Computational Learning Theory	2010	Ricard Gavaldà María López-Valdés Elvira Mayordomo N. V. Vinodchandran
+	Generalized kolmogorov complexity in relativized separations	2005	Ricard Gavaldà Leen Torenvliet Osamu Watanabe José L. Balcázar
+ PDF Chat	Practical Algorithms for On-Line Sampling	1998	Carlos Domingo Ricard Gavaldà Osamu Watanabe
+	Practical algorithms for on-line sampling	1998	Carlos Domingo Ricard Gavaldà Osamu Watanabe
+	On infinite sequences (almost) as easy as pi	1994	Ricard Gavaldà José Luis Balcázar Navarro Montserrat Hermo
+	Kolmogorov randomnes and its applications to structural complexity theory	1992	Ricard Gavaldà

Common Coauthors

Coauthor	Papers Together
Matteo Ruffini	6
Marc Bolaños	3
Xavier Giró-i-Nieto	3
Marta Arias	3
Estefanía Talavera	3
Petia Radeva	3
Osamu Watanabe	3
Gilles Blondel	3
Montserrat Hermo	2
Carlos Domingo	2
Esther Limón	2
Marta Casanellas	2
José L. Balcázar	2
José Luis Balcázar Navarro	1
Laura J. Avino	1
N. V. Vinodchandran	1
Esther Limón Ramírez	1
María López-Valdés	1
Elvira Mayordomo	1
Leen Torenvliet	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Solving Multiclass Learning Problems via Error-Correcting Output Codes	1995	Tom Dietterich Ghulum Bakiri	2
+	Tensor Factorization via Matrix Factorization	2015	Volodymyr Kuleshov Arun Tejasvi Chaganty Percy Liang	2
+	A Spectral Algorithm for Latent Dirichlet Allocation	2012	Animashree Anandkumar Dean P. Foster Daniel Hsu Sham M. Kakade Yi-Kai Liu	2
+	A Method of Moments for Mixture Models and Hidden Markov Models	2012	Animashree Anandkumar Daniel Hsu Sham M. Kakade	2
+ PDF Chat	The NumPy Array: A Structure for Efficient Numerical Computation	2011	Stéfan van der Walt Steven C. Colbert Gaël Varoquaux	2
+	Maximum Likelihood from Incomplete Data Via the <i>EM</i> Algorithm	1977	A. P. Dempster N. M. Laird Donald B. Rubin	2
+	Clustering Patients with Tensor Decomposition	2017	Matteo Ruffini Ricard Gavaldà Esther Limón	2
+ PDF Chat	R-Clustering for Egocentric Video Segmentation	2015	Estefanía Talavera Mariella Dimiccoli Marc Bolaños Maedeh Aghaei Petia Radeva	2
+	Discovering Cyclic Causal Models by Independent Components Analysis	2012	Gustavo Lacerda Peter Spirtes Joseph Ramsey Patrik O. Hoyer	2
+	Tensor decompositions for learning latent variable models	2014	Animashree Anandkumar Rong Ge Daniel Hsu Sham M. Kakade Matus Telgarsky	2
+ PDF Chat	Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions	2011	Nathan Halko Per‐Gunnar Martinsson Joel A. Tropp	2
+	Efficient algorithms for agglomerative hierarchical clustering methods	1984	W. H. Day Herbert Edelsbrunner	2
+ PDF Chat	Gales suffice for constructive dimension	2003	John M. Hitchcock	1
+ PDF Chat	Multivariate Bernoulli Mixture Models with Application to Postmortem Tissue Studies in Schizophrenia	2007	Zhuoxin Sun Ori Rosen Allan R. Sampson	1
+ PDF Chat	On Granger causality and the effect of interventions in time series	2009	Michael Eichler Vanessa Didelez	1
+ PDF Chat	Learning mixtures of spherical gaussians	2013	Daniel Hsu Sham M. Kakade	1
+	Tensor Decompositions and Applications	2009	Tamara G. Kolda Brett W. Bader	1
+	A Decomposition for Three-Way Arrays	1993	Sue E. Leurgans R. Ross Robert Abel	1
+	Tensorial resolution: A direct trilinear decomposition	1990	Eugenio Sanchez Bruce R. Kowalski	1
+ PDF Chat	Learning Mixtures of Gaussians in High Dimensions	2015	Rong Ge Qingqing Huang Sham M. Kakade	1
+	A comparison of algorithms for fitting the PARAFAC model	2004	Giorgio Tomasi Rasmus Bro	1
+ PDF Chat	Two decades of applied Kolmogorov complexity: in memoriam Andrei Nikolaevich Kolmogorov 1903-87	1988	M. Li Paul Vitányi	1
+	Three-way arrays: rank and uniqueness of trilinear decompositions, with application to arithmetic complexity and statistics	1977	Joseph B. Kruskal	1
+	Computation of the Canonical Decomposition by Means of a Simultaneous Generalized Schur Decomposition	2004	Lieven De Lathauwer Bart De Moor Joos Vandewalle	1
+ PDF Chat	Transportability of Causal and Statistical Relations: A Formal Approach	2011	Judea Pearl Elias Bareinboim	1
+ PDF Chat	Chain Graph Models and their Causal Interpretations	2002	Steffen L. Lauritzen Thomas S. Richardson	1
+	Scikit-learn: Machine Learning in Python	2012	Fabián Pedregosa Gaël Varoquaux Alexandre Gramfort Vincent Michel Bertrand Thirion Olivier Grisel Mathieu Blondel Peter Prettenhofer Ron J. Weiss Vincent Dubourg	1
+	Foundations of the PARAFAC procedure: Models and conditions for an "explanatory" multi-model factor analysis	1970	Richard A. Harshman	1
+ PDF Chat	A tutorial on spectral clustering	2007	Ulrike von Luxburg	1
+	Contrastive Learning Using Spectral Methods	2013	James Zou Daniel Hsu David C. Parkes Ryan P. Adams	1
+ PDF Chat	Can we believe the DAGs? A comment on the relationship between causal DAGs and mechanisms	2014	OO Aalen Kjetil Røysland J. M. Gran Roger D. Kouyos Theis Lange	1
+	A kernel two-sample test	2012	Arthur Gretton Karsten Borgwardt Malte J. Rasch Bernhard Schölkopf Alexander J. Smola	1
+	Perturbation theory for the singular value decomposition	1990	G. W. Stewart	1
+	Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja's Algorithm	2016	Prateek Jain Chi Jin Sham M. Kakade Praneeth Netrapalli Aaron Sidford	1
+ PDF Chat	Semialgebraic Geometry of Nonnegative Tensor Rank	2016	Qi Yang Pierre Comon Lek‐Heng Lim	1
+	Tensor decomposition via joint matrix schur decomposition	2016	Nicolò Colombo Nikos Vlassis	1
+	Tensor Decomposition for Signal Processing and Machine Learning	2017	Nicholas D. Sidiropoulos Lieven De Lathauwer Xiao Fu Kejun Huang Evangelos E. Papalexakis Christos Faloutsos	1
+ PDF Chat	Identifiability of an X-Rank Decomposition of Polynomial Maps	2017	Pierre Comon Qi Yang Konstantin Usevich	1
+	Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs	2017	Cristóbal Esteban Stephanie L. Hyland Gunnar Rätsch	1
+	Caffe: Convolutional Architecture for Fast Feature Embedding	2014	Yangqing Jia Evan Shelhamer Jeff Donahue Sergey Karayev Jonathan Long Ross Girshick Sergio Guadarrama Trevor Darrell	1
+	SPARTan: Scalable PARAFAC2 for Large & Sparse Data	2017	Ioakeim Perros Evangelos E. Papalexakis Fei Wang Richard Vuduc Elizabeth Searles Michael Thompson Jimeng Sun	1
+	A New Spectral Method for Latent Variable Models	2016	Matteo Ruffini Marta Casanellas Ricard Gavaldà	1
+	Causal Reasoning in Graphical Time Series Models	2012	Michael Eichler Vanessa Didelez	1
+	Learning Why Things Change: The Difference-Based Causality Learner	2012	Mark Voortman Denver Dash Marek J. Drużdżel	1
+	Generalization and Equilibrium in Generative Adversarial Nets (GANs)	2017	Sanjeev Arora Rong Ge Yingyu Liang Tengyu Ma Yi Zhang	1
+	Spectral Experts for Estimating Mixtures of Linear Regressions	2013	Arun Tejasvi Chaganty Percy Liang	1
+	Return of the Devil in the Details: Delving Deep into Convolutional Nets	2014	Ken Chatfield Karen Simonyan Andrea Vedaldi Andrew Zisserman	1
+	Identifying conditional causal effects	2004	Jin Tian	1
+	A Practical Algorithm for Topic Modeling with Provable Guarantees	2012	Sanjeev Arora Rong Ge Yonatan Halpern David Mimno Ankur Moitra David Sontag Yichen Wu Michael Zhu	1
+	On the method of bounded differences	1989	Colin McDiarmid	1