Dino Sejdinovic

According to our database, Dino Sejdinovic authored at least 106 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Doubly Robust Kernel Statistics for Testing Distributional Treatment Effects.

Jake Fawkes, Robert Hu, Robin J. Evans, Dino Sejdinovic

Trans. Mach. Learn. Res., 2024

A Kernel Test for Causal Association via Noise Contrastive Backdoor Adjustment.

Robert Hu, Dino Sejdinovic, Robin J. Evans

J. Mach. Learn. Res., 2024

An Overview of Causal Inference using Kernel Embeddings.

Dino Sejdinovic

CoRR, 2024

Credal Two-Sample Tests of Epistemic Ignorance.

Siu Lun Chau, Antonin Schrab, Arthur Gretton, Dino Sejdinovic, Krikamol Muandet

CoRR, 2024

Bayesian Low-Rank LeArning (Bella): A Practical Approach to Bayesian Neural Networks.

Bao Gia Doan, Afshar Shamsi, Xiao-Yu Guo, Arash Mohammadi, Hamid Alinejad-Rokny, Dino Sejdinovic, Damith C. Ranasinghe, Ehsan Abbasnejad

CoRR, 2024

Bayesian Adaptive Calibration and Optimal Design.

Rafael Oliveira, Dino Sejdinovic, David Howard, Edwin V. Bonilla

CoRR, 2024

Neural-Kernel Conditional Mean Embeddings.

Eiki Shimizu, Kenji Fukumizu, Dino Sejdinovic

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Exact, Fast and Expressive Poisson Point Processes via Squared Neural Families.

Russell Tsuchida, Cheng Soon Ong, Dino Sejdinovic

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Identifying Pauli spin blockade using deep learning.

Jonas Schuff, Dominic T. Lennon, Simon Geyer, David L. Craig, Federico Fedele, Florian Vigneau, Leon C. Camenzind, Andreas V. Kuhlmann, G. Andrew D. Briggs, Dominik M. Zumbühl, Dino Sejdinovic, Natalia Ares

Quantum, August, 2023

Fair Kernel Regression through Cross-Covariance Operators.

Adrian Perez-Suay, Paula Gordaliza, Jean-Michel Loubes, Dino Sejdinovic, Gustau Camps-Valls

Trans. Mach. Learn. Res., 2023

A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods.

Veit David Wild, Sahra Ghalebikesabi, Dino Sejdinovic, Jeremias Knoblauch

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Squared Neural Families: A New Class of Tractable Density Models.

Russell Tsuchida, Cheng Soon Ong, Dino Sejdinovic

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Explaining the Uncertain: Stochastic Shapley Values for Gaussian Process Models.

Siu Lun Chau, Krikamol Muandet, Dino Sejdinovic

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Returning The Favour: When Regression Benefits From Probabilistic Causal Knowledge.

Shahine Bouabid, Jake Fawkes, Dino Sejdinovic

Proceedings of the International Conference on Machine Learning, 2023

2022

Bayesian Kernel Two-Sample Testing.

Qinyi Zhang, Veit Wild, Sarah Filippi, Seth R. Flaxman, Dino Sejdinovic

J. Comput. Graph. Stat., October, 2022

Kernel dependence regularizers and Gaussian processes with applications to algorithmic fairness.

Zhu Li, Adrián Pérez-Suay, Gustau Camps-Valls, Dino Sejdinovic

Pattern Recognit., 2022

Large scale tensor regression using kernels and variational inference.

Robert Hu, Geoff K. Nicholls, Dino Sejdinovic

Mach. Learn., 2022

Doubly Robust Kernel Statistics for Testing Distributional Treatment Effects Even Under One Sided Overlap.

Jake Fawkes, Robert Hu, Robin J. Evans, Dino Sejdinovic

CoRR, 2022

Bayesian Counterfactual Mean Embeddings and Off-Policy Evaluation.

Diego Martinez-Taboada, Dino Sejdinovic

CoRR, 2022

Sequential Decision Making on Unmatched Data using Bayesian Kernel Embeddings.

Diego Martinez-Taboada, Dino Sejdinovic

CoRR, 2022

Discussion of 'Multiscale Fisher's Independence Test for Multivariate Dependence'.

Antonin Schrab, Wittawat Jitkrittum, Zoltán Szabó, Dino Sejdinovic, Arthur Gretton

CoRR, 2022

Giga-scale Kernel Matrix Vector Multiplication on GPU.

Robert Hu, Dino Sejdinovic, Joan Alexis Glaunès

CoRR, 2022

Spectral Ranking with Covariates.

Siu Lun Chau, Mihai Cucuringu, Dino Sejdinovic

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning.

Veit D. Wild, Robert Hu, Dino Sejdinovic

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Giga-scale Kernel Matrix-Vector Multiplication on GPU.

Robert Hu, Siu Lun Chau, Dino Sejdinovic, Joan Glaunès

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Explaining Preferences with Shapley Values.

Robert Hu, Siu Lun Chau, Jaime Ferrando Huertas, Dino Sejdinovic

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

RKHS-SHAP: Shapley Values for Kernel Methods.

Siu Lun Chau, Robert Hu, Javier González, Dino Sejdinovic

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Selection, Ignorability and Challenges With Causal Fairness.

Jake Fawkes, Robin J. Evans, Dino Sejdinovic

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

Survival regression with proper scoring rules and monotonic neural networks.

David Rindt, Robert Hu, David Steinsaltz, Dino Sejdinovic

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Learning Inconsistent Preferences with Gaussian Processes.

Siu Lun Chau, Javier González, Dino Sejdinovic

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Kernel-Based Graph Learning From Smooth Signals: A Functional Viewpoint.

Xingyue Pu, Siu Lun Chau, Xiaowen Dong, Dino Sejdinovic

IEEE Trans. Signal Inf. Process. over Networks, 2021

The Role of Digital Technologies in Responding to the Grand Challenges of the Natural Environment: The Windermere Accord.

Gordon S. Blair, Richard Bassett, Lucy Bastin, Lindsay Beevers, Maribel Isabel Borrajo, Mike Brown, Sarah L. Dance, Ada Dionescu, Liz Edwards, Maria Angela Ferrario, Rob Fraser, Harriet Fraser, Simon Gardner, Peter A. Henrys, Tony Hey, Stuart Homann, Chantal Huijbers, James Hutchison, Phil Jonathan, Rob Lamb, Sophie Laurie, Amber Leeson, David Leslie, Malcolm McMillan, Vatsala Nundloll, Oluwole K. Oyebamiji, Jordan Phillipson, Vicky Pope, Rachel Prudden, Stefan Reis, Maria Salama, Faiza Samreen, Dino Sejdinovic, Will Simm, Roger Street, Lauren Thornton, Ross Towe, Joshua Vande Hey, Massimo Vieno, Joanne A. Waller, John Watkins

Patterns, 2021

Unrepresentative big surveys significantly overestimated US vaccine uptake.

Valerie C. Bradley, Shiro Kuriwaki, Michael Isakov, Dino Sejdinovic, Xiao-Li Meng, Seth R. Flaxman

Nat., 2021

Towards a Unified Analysis of Random Fourier Features.

Zhu Li, Jean-Francois Ton, Dino Oglic, Dino Sejdinovic

J. Mach. Learn. Res., 2021

Bridging the reality gap in quantum devices with physics-aware machine learning.

David L. Craig, H. Moon, Federico Fedele, Dominic T. Lennon, Barnaby van Straaten, Florian Vigneau, Leon C. Camenzind, Dominik M. Zumbühl, G. Andrew D. Briggs, Michael A. Osborne, Dino Sejdinovic, Natalia Ares

CoRR, 2021

RKHS-SHAP: Shapley Values for Kernel Methods.

Siu Lun Chau, Javier González, Dino Sejdinovic

CoRR, 2021

Cross-architecture Tuning of Silicon and SiGe-based Quantum Devices Using Machine Learning.

Brandon Severin, Dominic T. Lennon, Leon C. Camenzind, Florian Vigneau, Federico Fedele, D. Jirovec, A. Ballabio, D. Chrastina, G. Isella, M. de Kruijf, Miguel J. Carballido, Simon Svab, Andreas V. Kuhlmann, F. R. Braakman, Simon Geyer, F. N. M. Froning, H. Moon, Michael A. Osborne, Dino Sejdinovic, G. Katsaros, Dominik M. Zumbühl, G. Andrew D. Briggs, Natalia Ares

CoRR, 2021

Connections and Equivalences between the Nyström Method and Sparse Variational Gaussian Processes.

Veit Wild, Motonobu Kanagawa, Dino Sejdinovic

CoRR, 2021

Time-to-event regression using partially monotonic neural networks.

David Rindt, Robert Hu, David Steinsaltz, Dino Sejdinovic

CoRR, 2021

Variational inference with continuously-indexed normalizing flows.

Anthony L. Caterini, Robert Cornish, Dino Sejdinovic, Arnaud Doucet

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Robust Deep Interpretable Features for Binary Image Classification.

Robert Hu, Dino Sejdinovic

Proceedings of the 2021 Northern Lights Deep Learning Workshop, 2021

BayesIMP: Uncertainty Quantification for Causal Data Fusion.

Siu Lun Chau, Jean-Francois Ton, Javier González, Yee Whye Teh, Dino Sejdinovic

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deconditional Downscaling with Gaussian Processes.

Siu Lun Chau, Shahine Bouabid, Dino Sejdinovic

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Noise Contrastive Meta-Learning for Conditional Density Estimation using Kernel Mean Embeddings.

Jean-Francois Ton, Lucian Chan, Yee Whye Teh, Dino Sejdinovic

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Meta Learning for Causal Direction.

Jean-François Ton, Dino Sejdinovic, Kenji Fukumizu

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Deep Reinforcement Learning for Efficient Measurement of Quantum Devices.

V. Nguyen, S. B. Orbell, Dominic T. Lennon, Hyungil Moon, Florian Vigneau, Leon C. Camenzind, Liuqi Yu, Dominik M. Zumbühl, G. Andrew D. Briggs, Michael A. Osborne, Dino Sejdinovic, Natalia Ares

CoRR, 2020

Benign Overfitting and Noisy Features.

Zhu Li, Weijie J. Su, Dino Sejdinovic

CoRR, 2020

A Perspective on Gaussian Processes for Earth Observation.

Gustau Camps-Valls, Dino Sejdinovic, Jakob Runge, Markus Reichstein

CoRR, 2020

Learning Inconsistent Preferences with Kernel Methods.

Siu Lun Chau, Javier González, Dino Sejdinovic

CoRR, 2020

Quantum device fine-tuning using unsupervised embedding learning.

Nina M. van Esbroeck, Dominic T. Lennon, Hyungil Moon, V. Nguyen, Florian Vigneau, Leon C. Camenzind, Liuqi Yu, Dominik M. Zumbühl, G. Andrew D. Briggs, Dino Sejdinovic, Natalia Ares

CoRR, 2020

Machine learning enables completely automatic tuning of a quantum device faster than human experts.

Hyungil Moon, Dominic T. Lennon, James Kirkpatrick, Nina M. van Esbroeck, Leon C. Camenzind, Liuqi Yu, Florian Vigneau, Dominik M. Zumbühl, G. Andrew D. Briggs, Michael A. Osborne, Dino Sejdinovic, Edward A. Laird, Natalia Ares

CoRR, 2020

Inter-domain Deep Gaussian Processes.

Tim G. J. Rudner, Dino Sejdinovic, Yarin Gal

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Detecting anthropogenic cloud perturbations with deep learning.

Duncan Watson-Parris, Samuel Sutherland, Matthew Christensen, Anthony L. Caterini, Dino Sejdinovic, Philip Stier

CoRR, 2019

A Differentially Private Kernel Two-Sample Test.

Anant Raj, Ho Chung Leon Law, Dino Sejdinovic, Mijung Park

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Hyperparameter Learning via Distributional Transfer.

Ho Chung Leon Law, Peilin Zhao, Leung Sing Chan, Junzhou Huang, Dino Sejdinovic

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Large-scale kernel methods for independence testing.

Qinyi Zhang, Sarah Filippi, Arthur Gretton, Dino Sejdinovic

Stat. Comput., 2018

Rejoinder for "Probabilistic Integration: A Role in Statistical Computation?".

François-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne, Dino Sejdinovic

CoRR, 2018

Hyperparameter Learning via Distributional Transfer.

Ho Chung Leon Law, Peilin Zhao, Junzhou Huang, Dino Sejdinovic

CoRR, 2018

Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences.

Motonobu Kanagawa, Philipp Hennig, Dino Sejdinovic, Bharath K. Sriperumbudur

CoRR, 2018

A Unified Analysis of Random Fourier Features.

Zhu Li, Jean-Francois Ton, Dino Oglic, Dino Sejdinovic

CoRR, 2018

Causal Inference via Kernel Deviance Measures.

Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Variational Learning on Aggregate Outputs with Gaussian Processes.

Ho Chung Leon Law, Dino Sejdinovic, Ewan Cameron, Tim C. D. Lucas, Seth R. Flaxman, Katherine Battle, Kenji Fukumizu

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Hamiltonian Variational Auto-Encoder.

Anthony L. Caterini, Arnaud Doucet, Dino Sejdinovic

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Bayesian Approaches to Distribution Regression.

Ho Chung Leon Law, Danica J. Sutherland, Dino Sejdinovic, Seth R. Flaxman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Bayesian Distribution Regression.

Ho Chung Leon Law, Danica J. Sutherland, Dino Sejdinovic, Seth R. Flaxman

CoRR, 2017

Feature-to-Feature Regression for a Two-Step Conditional Independence Test.

Qinyi Zhang, Sarah Filippi, Seth R. Flaxman, Dino Sejdinovic

Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Kernel Sequential Monte Carlo.

Ingmar Schuster, Heiko Strathmann, Brooks Paige, Dino Sejdinovic

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Testing and Learning on Distributions with Symmetric Noise Invariance.

Ho Chung Leon Law, Christopher Yau, Dino Sejdinovic

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Deep Kernel Machines via the Kernel Reparametrization Trick.

Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh

Proceedings of the 5th International Conference on Learning Representations, 2017

Poisson intensity estimation with reproducing kernels.

Seth R. Flaxman, Yee Whye Teh, Dino Sejdinovic

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

CONDENSE: A Reconfigurable Knowledge Acquisition Architecture for Future 5G IoT.

Dejan Vukobratovic, Dusan Jakovetic, Vitaly Skachek, Dragana Bajovic, Dino Sejdinovic, Günes Karabulut-Kurt, Camilla Hollanti, Ingo Fischer

IEEE Access, 2016

Super-Sampling with a Reservoir.

Brooks Paige, Dino Sejdinovic, Frank D. Wood

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Bayesian Learning of Kernel Embeddings.

Seth R. Flaxman, Dino Sejdinovic, John P. Cunningham, Sarah Filippi

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

Network function computation as a service in future 5G machine type communications.

Dejan Vukobratovic, Dusan Jakovetic, Vitaly Skachek, Dragana Bajovic, Dino Sejdinovic

Proceedings of the 9th International Symposium on Turbo Codes and Iterative Information Processing, 2016

DR-ABC: Approximate Bayesian Computation with Kernel-Based Distribution Regression.

Jovana Mitrovic, Dino Sejdinovic, Yee Whye Teh

Proceedings of the 33nd International Conference on Machine Learning, 2016

Hyperspectral image classification with support vector machines on kernel distribution embeddings.

Gianni Franchi, Jesús Angulo, Dino Sejdinovic

Proceedings of the 2016 IEEE International Conference on Image Processing, 2016

K2-ABC: Approximate Bayesian Computation with Kernel Embeddings.

Mijung Park, Wittawat Jitkrittum, Dino Sejdinovic

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Unbiased Bayes for Big Data: Paths of Partial Posteriors.

Heiko Strathmann, Dino Sejdinovic, Mark A. Girolami

CoRR, 2015

Probabilistic Integration.

François-Xavier Briol, Chris J. Oates, Mark A. Girolami, Michael A. Osborne, Dino Sejdinovic

CoRR, 2015

Kernel-Based Just-In-Time Learning for Passing Expectation Propagation Messages.

Wittawat Jitkrittum, Arthur Gretton, Nicolas Heess, S. M. Ali Eslami, Balaji Lakshminarayanan, Dino Sejdinovic, Zoltán Szabó

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Compressed Sensing using sparse binary measurements: A rateless coding perspective.

Dejan Vukobratovic, Dino Sejdinovic, Aleksandra Pizurica

Proceedings of the 16th IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2015

Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families.

Heiko Strathmann, Dino Sejdinovic, Samuel Livingstone, Zoltán Szabó, Arthur Gretton

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Fast Two-Sample Testing with Analytic Representations of Probability Measures.

Kacper Chwialkowski, Aaditya Ramdas, Dino Sejdinovic, Arthur Gretton

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

A Wild Bootstrap for Degenerate Kernel Tests.

Kacper Chwialkowski, Dino Sejdinovic, Arthur Gretton

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Kernel Adaptive Metropolis-Hastings.

Dino Sejdinovic, Heiko Strathmann, Maria Lomeli Garcia, Christophe Andrieu, Arthur Gretton

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

A Kernel Test for Three-Variable Interactions.

Dino Sejdinovic, Arthur Gretton, Wicher Bergsma

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012

Equivalence of distance-based and RKHS-based statistics in hypothesis testing

Dino Sejdinovic, Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu

CoRR, 2012

Hypothesis testing using pairwise distances and associated kernels (with Appendix)

Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu

CoRR, 2012

Optimal kernel choice for large-scale two-sample tests.

Arthur Gretton, Bharath K. Sriperumbudur, Dino Sejdinovic, Heiko Strathmann, Sivaraman Balakrishnan, Massimiliano Pontil, Kenji Fukumizu

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Hypothesis testing using pairwise distances and associated kernels.

Dino Sejdinovic, Arthur Gretton, Bharath K. Sriperumbudur, Kenji Fukumizu

Proceedings of the 29th International Conference on Machine Learning, 2012

Combinatorial channel signature modulation for wireless ad-hoc networks.

Robert J. Piechocki, Dino Sejdinovic

Proceedings of IEEE International Conference on Communications, 2012

Approximate message passing under finite alphabet constraints.

Andreas Müller, Dino Sejdinovic, Robert J. Piechocki

Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2011

Non-parametric change-point detection using string matching algorithms

Oliver Johnson, Dino Sejdinovic, James R. Cruise, Ayalvadi Ganesh, Robert J. Piechocki

CoRR, 2011

2010

Decentralised distributed fountain coding: asymptotic analysis and design.

Dino Sejdinovic, Robert J. Piechocki, Angela Doufexi, Mohamed Ismail

IEEE Commun. Lett., 2010

Note on noisy group testing: Asymptotic bounds and belief propagation reconstruction.

Dino Sejdinovic, Oliver Johnson

Proceedings of the 48th Annual Allerton Conference on Communication, 2010

Bayesian sequential compressed sensing in sparse dynamical systems.

Dino Sejdinovic, Christophe Andrieu, Robert J. Piechocki

Proceedings of the 48th Annual Allerton Conference on Communication, 2010

2009

Fountain code design for data multicast with side information.

Dino Sejdinovic, Robert J. Piechocki, Angela Doufexi, Mohamed Ismail

IEEE Trans. Wirel. Commun., 2009

Scalable Video Multicast Using Expanding Window Fountain Codes.

Dejan Vukobratovic, Vladimir Stankovic, Dino Sejdinovic, Lina Stankovic, Zixiang Xiong

IEEE Trans. Multim., 2009

Expanding window fountain codes for unequal error protection.

Dino Sejdinovic, Dejan Vukobratovic, Angela Doufexi, Vojin Senk, Robert J. Piechocki

IEEE Trans. Commun., 2009

Precoded EWF codes for unequal error protection of scalable video.

Dejan Vukobratovic, Vladimir Stankovic, Lina Stankovic, Dino Sejdinovic

Proceedings of the 5th International Conference on Mobile Multimedia Communications, 2009

Rateless distributed source code design.

Dino Sejdinovic, Robert J. Piechocki, Angela Doufexi

Proceedings of the 5th International Conference on Mobile Multimedia Communications, 2009

AND-OR tree analysis of distributed LT codes.

Dino Sejdinovic, Robert J. Piechocki, Angela Doufexi

Proceedings of the 2009 IEEE Information Theory Workshop, 2009

2008

The Throughput Analysis of Different IR-HARQ Schemes Based on Fountain Codes.

Dino Sejdinovic, Vishakan Ponnampalam, Robert J. Piechocki, Angela Doufexi

Proceedings of the WCNC 2008, IEEE Wireless Communications & Networking Conference, March 31 2008, 2008

Expanding Window Fountain codes for scalable video multicast.

Dejan Vukobratovic, Vladimir Stankovic, Dino Sejdinovic, Lina Stankovic, Zixiang Xiong

Proceedings of the 2008 IEEE International Conference on Multimedia and Expo, 2008

Fountain Coding with Decoder Side Information.

Dino Sejdinovic, Robert J. Piechocki, Angela Doufexi, Mohamed Ismail

Proceedings of IEEE International Conference on Communications, 2008

Rate Adaptive Binary Erasure Quantization with Dual Fountain Codes.

Dino Sejdinovic, Robert J. Piechocki, Angela Doufexi, Mohamed Ismail

Proceedings of the Global Communications Conference, 2008. GLOBECOM 2008, New Orleans, LA, USA, 30 November, 2008