Devdatt P. Dubhashi

According to our database, Devdatt P. Dubhashi authored at least 82 papers between 1992 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

ACE: Abstractions for Communicating Efficiently.

Jonathan D. Thomas, Andrea Silvi, Devdatt P. Dubhashi, Vikas Garg, Moa Johansson

CoRR, 2024

Learning Efficient Recursive Numeral Systems via Reinforcement Learning.

Jonathan D. Thomas, Andrea Silvi, Devdatt P. Dubhashi, Emil Carlsson, Moa Johansson

CoRR, 2024

Predicting Ground State Properties: Constant Sample Complexity and Deep Learning Algorithms.

Marc Wanner, Laura Lewis, Chiranjib Bhattacharyya, Devdatt P. Dubhashi, Alexandru Gheorghiu

CoRR, 2024

Active Preference Learning for Ordering Items In- and Out-of-sample.

Herman Bergström, Emil Carlsson, Devdatt P. Dubhashi, Fredrik D. Johansson

CoRR, 2024

Pure Exploration in Bandits with Linear Constraints.

Emil Carlsson, Debabrota Basu, Fredrik D. Johansson, Devdatt P. Dubhashi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Do Kernel and Neural Embeddings Help in Training and Generalization?

Arman Rahbar, Emilio Jorge, Devdatt P. Dubhashi, Morteza Haghir Chehreghani

Neural Process. Lett., April, 2023

Recovery Bounds on Class-Based Optimal Transport: A Sum-of-Norms Regularization Framework.

Arman Rahbar, Ashkan Panahi, Morteza Haghir Chehreghani, Devdatt P. Dubhashi, Hamid Krim

Proceedings of the International Conference on Machine Learning, 2023

Iterated learning and communication jointly explain efficient color naming systems.

Emil Carlsson, Devdatt P. Dubhashi, Terry Regier

Proceedings of the 45th Annual Meeting of the Cognitive Science Society, 2023

Random Features Model with General Convex Regularization: A Fine Grained Analysis with Precise Asymptotic Learning Curves.

David Bosch, Ashkan Panahi, Ayça Özçelikkale, Devdatt P. Dubhashi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Double Descent in Random Feature Models: Precise Asymptotic Analysis for General Convex Regularization.

David Bosch, Ashkan Panahi, Ayça Özçelikkale, Devdatt P. Dubhashi

CoRR, 2022

Using satellites and artificial intelligence to measure health and material-living standards in India.

Adel Daoud, Felipe Jordan, Makkunda Sharma, Fredrik D. Johansson, Devdatt P. Dubhashi, Sourabh Bikash Paul, Subhashis Banerjee

CoRR, 2022

Can universities combat the 'wrong kind of AI'?

Devdatt P. Dubhashi

Commun. ACM, 2022

Pragmatic Reasoning in Structured Signaling Games.

Emil Carlsson, Devdatt P. Dubhashi

Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022

Analysis of Knowledge Transfer in Kernel Regime.

Ashkan Panahi, Arman Rahbar, Chiranjib Bhattacharyya, Devdatt P. Dubhashi, Morteza Haghir Chehreghani

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

AI futures: fact and fantasy.

Devdatt P. Dubhashi

Commun. ACM, 2021

Thompson Sampling for Bandits with Clustered Arms.

Emil Carlsson, Devdatt P. Dubhashi, Fredrik D. Johansson

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Learning Approximate and Exact Numeral Systems via Reinforcement Learning.

Emil Carlsson, Devdatt P. Dubhashi, Fredrik D. Johansson

Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

2020

Accelerated proximal incremental algorithm schemes for non-strongly convex functions.

Ashkan Panahi, Morteza Haghir Chehreghani, Devdatt P. Dubhashi

Theor. Comput. Sci., 2020

Statistical modeling: the three cultures.

Adel Daoud, Devdatt P. Dubhashi

CoRR, 2020

Models for COVID-19 Pandemic: A Comparative Analysis.

Aniruddha Adiga, Devdatt P. Dubhashi, Bryan L. Lewis, Madhav V. Marathe, Srinivasan Venkatramanan, Anil Vullikanti

CoRR, 2020

On the Unreasonable Effectiveness of Knowledge Distillation: Analysis in the Kernel Regime.

Arman Rahbar, Ashkan Panahi, Chiranjib Bhattacharyya, Devdatt P. Dubhashi, Morteza Haghir Chehreghani

CoRR, 2020

LEGaTO: Low-Energy, Secure, and Resilient Toolset for Heterogeneous Computing.

Behzad Salami, Konstantinos Parasyris, Adrián Cristal, Osman S. Unsal, Xavier Martorell, Paul Carpenter, Raúl de la Cruz, Leonardo Bautista-Gomez, Daniel A. Jiménez, Carlos Álvarez, Seyed Saber Nabavi Larimi, Sergi Madonar, Miquel Pericàs, Pedro Trancoso, Mustafa Abduljabbar, Jing Chen, Pirah Noor Soomro, Madhavan Manivannan, Micha vor dem Berge, Stefan Krupop, Frank Klawonn, Al Mekhlafi, Sigrun May, Tobias Becker, Georgi Gaydadjiev, Hans Salomonsson, Devdatt P. Dubhashi, Oron Port, Yoav Etsion, Do Le Quoc, Christof Fetzer, Martin Kaiser, Nils Kucza, Jens Hagemeyer, René Griessl, Lennart Tigges, Kevin Mika, A. Hüffmeier, Marcelo Pasin, Valerio Schiavoni, Isabelly Rocha, Christian Göttel, Pascal Felber

Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020

2019

LEGaTO: Low-Energy, Secure, and Resilient Toolset for Heterogeneous Computing.

Behzad Salami, Konstantinos Parasyris, Adrián Cristal, Osman S. Unsal, Xavier Martorell, Paul Carpenter, Raúl de la Cruz, Leonardo Bautista-Gomez, Daniel A. Jiménez, Carlos Álvarez, S. Nabavi, Sergi Madonar, Miquel Pericàs, Pedro Trancoso, Mustafa Abduljabbar, Jing Chen, Pirah Noor Soomro, Madhavan Manivannan, Micha vor dem Berge, Stefan Krupop, Frank Klawonn, Al Mekhlafi, Sigrun May, Tobias Becker, Georgi Gaydadjiev, Daniel Ödman, Hans Salomonsson, Devdatt P. Dubhashi, Oron Port, Yoav Etsion, Do Le Quoc, Christof Fetzer, Martin Kaiser, Nils Kucza, Jens Hagemeyer, René Griessl, Lennart Tigges, Kevin Mika, A. Hüffmeier, Th. Jungeblu, Marcelo Pasin, Valerio Schiavoni, Isabelly Rocha, Christian Göttel, Pascal Felber

CoRR, 2019

Spectral Analysis of Kernel and Neural Embeddings: Optimization and Generalization.

Emilio Jorge, Morteza Haghir Chehreghani, Devdatt P. Dubhashi

CoRR, 2019

Stochastic Incremental Algorithms for Optimal Transport with SON Regularizer.

Ashkan Panahi, Erik Thiel, Morteza Haghir Cheraghani, Devdatt P. Dubhashi

CoRR, 2019

Bayesian optimization in ab initio nuclear physics.

Andreas Ekström, Christian Forssén, Christos Dimitrakakis, Devdatt P. Dubhashi, Håkan T. Johansson, Azam Sheikh Muhammad, Hans Salomonsson, Alexander Schliep

CoRR, 2019

A Non-Convex Optimization Approach to Correlation Clustering.

Erik Thiel, Morteza Haghir Chehreghani, Devdatt P. Dubhashi

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

LEGaTO: first steps towards energy-efficient toolset for heterogeneous computing.

Adrián Cristal, Osman S. Unsal, Xavier Martorell, Paul Carpenter, Raúl de la Cruz, Leonardo Bautista-Gomez, Daniel Jiménez-González, Carlos Álvarez, Behzad Salami, Sergi Madonar, Miquel Pericàs, Pedro Trancoso, Micha vor dem Berge, Gunnar Billung-Meyer, Stefan Krupop, Wolfgang Christmann, Frank Klawonn, Amani Mihklafi, Tobias Becker, Georgi Gaydadjiev, Hans Salomonsson, Devdatt P. Dubhashi, Oron Port, Elad Hadar, Yoav Etsion, Christof Fetzer, Jens Hagemeyer, Thorsten Jungeblut, Nils Kucza, Martin Kaiser, Mario Porrmann, Marcelo Pasin, Valerio Schiavoni, Isabelly Rocha, Christian Göttel, Pascal Felber

Proceedings of the 18th International Conference on Embedded Computer Systems: Architectures, 2018

DeepColor: Reinforcement Learning optimizes information efficiency and well-formedness in color name partitioning.

Mikael Kågebäck, Devdatt P. Dubhashi, Asad B. Sayeed

Proceedings of the 40th Annual Meeting of the Cognitive Science Society, 2018

LEGaTO: towards energy-efficient, secure, fault-tolerant toolset for heterogeneous computing.

Adrián Cristal, Osman S. Unsal, Xavier Martorell, Paul Carpenter, Raúl de la Cruz, Leonardo Bautista-Gomez, Daniel Jiménez-González, Carlos Álvarez, Behzad Salami, Sergi Madonar, Miquel Pericàs, Pedro Trancoso, Micha vor dem Berge, Gunnar Billung-Meyer, Stefan Krupop, Wolfgang Christmann, Frank Klawonn, Amani Mihklafi, Tobias Becker, Georgi Gaydadjiev, Hans Salomonsson, Devdatt P. Dubhashi, Oron Port, Yoav Etsion, Vesna Nowack, Christof Fetzer, Jens Hagemeyer, Thorsten Jungeblut, Nils Kucza, Martin Kaiser, Mario Porrmann, Marcelo Pasin, Valerio Schiavoni, Isabelly Rocha, Christian Göttel, Pascal Felber

Proceedings of the 15th ACM International Conference on Computing Frontiers, 2018

Distributed Approximation Algorithms via LP-Duality and Randomization.

Devdatt P. Dubhashi, Fabrizio Grandoni, Alessandro Panconesi

Proceedings of the Handbook of Approximation Algorithms and Metaheuristics, 2018

2017

GANs for LIFE: Generative Adversarial Networks for Likelihood Free Inference.

Vinay Jethava, Devdatt P. Dubhashi

CoRR, 2017

AI dangers: imagined and real.

Devdatt P. Dubhashi, Shalom Lappin

Commun. ACM, 2017

Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery.

Ashkan Panahi, Devdatt P. Dubhashi, Fredrik D. Johansson, Chiranjib Bhattacharyya

Proceedings of the 34th International Conference on Machine Learning, 2017

Thompson Sampling for Stochastic Bandits with Graph Feedback.

Aristide C. Y. Tossou, Christos Dimitrakakis, Devdatt P. Dubhashi

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Distributed Vertex Coloring.

Devdatt P. Dubhashi

Encyclopedia of Algorithms, 2016

2015

Visions and open challenges for a knowledge-based culturomics.

Nina Tahmasebi, Lars Borin, Gabriele Capannini, Devdatt P. Dubhashi, Peter Exner, Markus Forsberg, Gerhard Gossen, Fredrik D. Johansson, Richard Johansson, Mikael Kågebäck, Olof Mogren, Pierre Nugues, Thomas Risse

Int. J. Digit. Libr., 2015

Extractive Summarization by Aggregating Multiple Similarities.

Olof Mogren, Mikael Kågebäck, Devdatt P. Dubhashi

Proceedings of the Recent Advances in Natural Language Processing, 2015

Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization.

Fredrik D. Johansson, Ankani Chattoraj, Chiranjib Bhattacharyya, Devdatt P. Dubhashi

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

Neural context embeddings for automatic discovery of word senses.

Mikael Kågebäck, Fredrik D. Johansson, Richard Johansson, Devdatt P. Dubhashi

Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing, 2015

Classifying Large Graphs with Differential Privacy.

Fredrik D. Johansson, Otto Frost, Carl Retzner, Devdatt P. Dubhashi

Proceedings of the Modeling Decisions for Artificial Intelligence, 2015

Learning with Similarity Functions on Graphs using Matchings of Geometric Embeddings.

Fredrik D. Johansson, Devdatt P. Dubhashi

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014

Global graph kernels using geometric embeddings.

Fredrik D. Johansson, Vinay Jethava, Devdatt P. Dubhashi, Chiranjib Bhattacharyya

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

Federated clouds for biomedical research: Integrating OpenStack for ICTBioMed.

Cezary Mazurek, Juliusz Pukacki, Michal Kosiedowski, Szymon Trocha, Michael Sullivan, Hemant Darbari, Amit Saxena, Rajendra Joshi, Devdatt P. Dubhashi, Subazini Thankaswamy, Paul R. Brenner, Sandra Gesing, Jarek Nabrzyski, Anil Srivastava

Proceedings of the 3rd IEEE International Conference on Cloud Networking, 2014

Extractive Summarization using Continuous Vector Space Models.

Mikael Kågebäck, Olof Mogren, Nina Tahmasebi, Devdatt P. Dubhashi

Proceedings of the 2nd Workshop on Continuous Vector Space Models and their Compositionality, 2014

2013

Lovász ϑ function, SVMs and finding dense subgraphs.

Vinay Jethava, Anders Martinsson, Chiranjib Bhattacharyya, Devdatt P. Dubhashi

J. Mach. Learn. Res., 2013

Lovasz ϑ, SVMs and applications.

Vinay Jethava, Jacob Sznajdman, Chiranjib Bhattacharyya, Devdatt P. Dubhashi

Proceedings of the 2013 IEEE Information Theory Workshop, 2013

DLOREAN: Dynamic Location-Aware Reconstruction of Multiway Networks.

Fredrik Johansson, Vinay Jethava, Devdatt P. Dubhashi

Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

Entity disambiguation in anonymized graphs using graph kernels.

Linus Hermansson, Tommi Kerola, Fredrik Johansson, Vinay Jethava, Devdatt P. Dubhashi

Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 2013

Mining semantics for culturomics: towards a knowledge-based approach.

Lars Borin, Devdatt P. Dubhashi, Markus Forsberg, Richard Johansson, Dimitrios Kokkinakis, Pierre Nugues

Proceedings of the 2013 international workshop on Mining unstructured big data using natural language processing, 2013

2012

"The Lovasz $\theta$ function, SVMs and finding large dense subgraphs".

Vinay Jethava, Anders Martinsson, Chiranjib Bhattacharyya, Devdatt P. Dubhashi

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

2011

NETGEM: Network Embedded Temporal GEnerative Model for gene expression data.

Vinay Jethava, Chiranjib Bhattacharyya, Devdatt P. Dubhashi, Goutham N. Vemuri

BMC Bioinform., 2011

Scalable multi-dimensional user intent identification using tree structured distributions.

Vinay Jethava, Liliana Calderón-Benavides, Ricardo Baeza-Yates, Chiranjib Bhattacharyya, Devdatt P. Dubhashi

Proceedings of the Proceeding of the 34th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2011

2009

Concentration of Measure for the Analysis of Randomized Algorithms.

Devdatt P. Dubhashi, Alessandro Panconesi

Cambridge University Press, ISBN: 978-0-521-88427-3, 2009

2008

Distributed Vertex Coloring.

Devdatt P. Dubhashi

Proceedings of the Encyclopedia of Algorithms - 2008 Edition, 2008

Adaptive Dynamics of Realistic Small-World Networks

Olof Mogren, Oskar Sandberg, Vilhelm Verendel, Devdatt P. Dubhashi

CoRR, 2008

2007

Distributed Approximation Algorithms via LP-Duality and Randomization.

Alessandro Panconesi, Fabrizio Grandoni, Devdatt P. Dubhashi

Proceedings of the Handbook of Approximation Algorithms and Metaheuristics., 2007

Blue pleiades, a new solution for device discovery and scatternet formation in multi-hop Bluetooth networks.

Devdatt P. Dubhashi, Olle Häggström, Gabriele Mambrini, Alessandro Panconesi, Chiara Petrioli

Wirel. Networks, 2007

Probabilistic analysis for a multiple depot vehicle routing problem.

Andreas Baltz, Devdatt P. Dubhashi, Anand Srivastav, Libertad Tansini, Sören Werth

Random Struct. Algorithms, 2007

Positive Influence and Negative Dependence.

Devdatt P. Dubhashi, Johan Jonasson, Desh Ranjan

Comb. Probab. Comput., 2007

Localized Techniques for Broadcasting in Wireless Sensor Networks.

Devdatt P. Dubhashi, Olle Häggström, Lorenzo Orecchia, Alessandro Panconesi, Chiara Petrioli, Andrea Vitaletti

Algorithmica, 2007

2006

Bayesian classifiers for detecting HGT using fixed and variable order markov models of genomic signatures.

Daniel Dalevi, Devdatt P. Dubhashi, Malte Hermansson

Bioinform., 2006

Randomization in Constraint Programming for Airline Planning.

Lars Otten, Mattias Grönkvist, Devdatt P. Dubhashi

Proceedings of the Principles and Practice of Constraint Programming, 2006

2005

Fast distributed algorithms for (weakly) connected dominating sets and linear-size skeletons.

Devdatt P. Dubhashi, Alessandro Mei, Alessandro Panconesi, Jaikumar Radhakrishnan, Aravind Srinivasan

J. Comput. Syst. Sci., 2005

The Peres-Shields Order Estimator for Fixed and Variable Length Markov Models with Applications to DNA Sequence Similarity.

Daniel Dalevi, Devdatt P. Dubhashi

Proceedings of the Algorithms in Bioinformatics, 5th International Workshop, 2005

Irrigating ad hoc networks in constant time.

Devdatt P. Dubhashi, C. Johansson, Olle Häggström, Alessandro Panconesi, Mauro Sozio

Proceedings of the SPAA 2005: Proceedings of the 17th Annual ACM Symposium on Parallelism in Algorithms and Architectures, 2005

2003

Analysis and Experimental Evaluation of a Simple Algorithm for Collaborative Filtering in Planted Partition Models: Extended Abstract.

Devdatt P. Dubhashi, Luigi Laura, Alessandro Panconesi

Proceedings of the FST TCS 2003: Foundations of Software Technology and Theoretical Computer Science, 2003

1998

Near-Optimal, Distributed Edge Colouring via the Nibble Method.

Devdatt P. Dubhashi, David A. Grable, Alessandro Panconesi

Theor. Comput. Sci., 1998

Balls and bins: A study in negative dependence.

Devdatt P. Dubhashi, Desh Ranjan

Random Struct. Algorithms, 1998

Talagrand's Inequality and Locality in Distributed Computing.

Devdatt P. Dubhashi

Proceedings of the Randomization and Approximation Techniques in Computer Science, 1998

Martingales and Locality in Distributed Computing.

Devdatt P. Dubhashi

Proceedings of the Foundations of Software Technology and Theoretical Computer Science, 1998

1997

Probabilistic Recurrence Relations Revisited.

Shiva Chaudhuri, Devdatt P. Dubhashi

Theor. Comput. Sci., 1997

Simple proofs of occupancy tail bounds.

Devdatt P. Dubhashi

Random Struct. Algorithms, 1997

Transforming Comparison Model Lower Bounds to the Parallel-Random-Access-Machine.

Dany Breslauer, Artur Czumaj, Devdatt P. Dubhashi, Friedhelm Meyer auf der Heide

Inf. Process. Lett., 1997

1995

The Fourth Moment in Luby's Distribution.

Devdatt P. Dubhashi, Grammati E. Pantziou, Paul G. Spirakis, Christos D. Zaroliagis

Theor. Comput. Sci., 1995

(Probabilistic) Recurrence Realtions Revisited.

Shiva Chaudhuri, Devdatt P. Dubhashi

Proceedings of the LATIN '95: Theoretical Informatics, 1995

Near-Optimal Distributed Edge Coloring.

Devdatt P. Dubhashi, Alessandro Panconesi

Proceedings of the Algorithms, 1995

1994

A Lower Bound for Area-Universal Graphs.

Gianfranco Bilardi, Shiva Chaudhuri, Devdatt P. Dubhashi, Kurt Mehlhorn

Inf. Process. Lett., 1994

1993

Quantifier Elimination in p-adic Fields.

Devdatt P. Dubhashi

Comput. J., 1993

Searching, Sorting and Randomised Algorithms for Central Elements and Ideal Counting in Posets.

Devdatt P. Dubhashi, Kurt Mehlhorn, Desh Ranjan, Christian Thiel

Proceedings of the Foundations of Software Technology and Theoretical Computer Science, 1993

1992

Algorithmic Investigations In P-adic Fields.

Devdatt P. Dubhashi

PhD thesis, 1992

On Decidable Varieties of Heyting Algebras.

Devdatt P. Dubhashi

J. Symb. Log., 1992