Devdatt Dubhashi

Full Professor at the Data Science and AI division, Department of Computer Science and Engineering.

dubhashi@chalmers.se +46317721046 Find me

My main interests are in design and analysis of randomized algorithms, machine learning for Big Data and computational biology.

Publications
Collaboration and projects

Latest publications

2022
Pragmatic Reasoning in Structured Signaling Games

Author: Emil Carlsson; Devdatt Dubhashi

Published: 2022

Published in: Proceedings of the 44th Annual Meeting of the Cognitive Science Society: Cognitive Diversity, CogSci 2022

Publication type: Paper in proceeding
Can Universities Combat the 'Wrong Kind of AI'?

Author: Devdatt Dubhashi

Published: 2022

Published in: Communications of the ACM

Publication type: Other text in scientific journal
Analysis of Knowledge Transfer in Kernel Regime

Author: Ashkan Panahi; Arman Rahbar; Chiranjib Bhattacharyya; Devdatt Dubhashi; Morteza Haghir Chehreghani

Published: 2022

Published in: Proceedings of the 31st ACM International Conference on Information & Knowledge Management

Publication type: Paper in proceeding
Controlling gene expression with deep generative design of regulatory DNA

Author: Jan Zrimec; Xiaozhi Fu; Muhammad Azam Sheikh; Christos Skrekas; Vykintas Jauniskis; Nora Speicher; Christoph Sebastian Börlin; Vilhelm Verendel; Morteza Haghir Chehreghani; Devdatt Dubhashi; Verena Siewers; Florian David; Jens B Nielsen; Aleksej Zelezniak

Published: 2022

Published in: Nature Communications

Publication type: Journal article
Do Kernel and Neural Embeddings Help in Training and Generalization?

Author: Arman Rahbar; Emilio Jorge; Devdatt Dubhashi; Morteza Haghir Chehreghani

Published: 2022

Published in: Neural Processing Letters

Publication type: Journal article
Synthetic Sweden Mobility (SySMo) Model Documentation

Author: Çaglar Tozluoglu; Swapnil Vilas Dhamal; Yuan Liao; Sonia Yeh; Frances Sprei; Devdatt Dubhashi; Madhav Marathe; Christopher Barrett

Published: 2022

Published in:

Publication type: Preprint
2021
Learning Approximate and Exact Numeral Systems via Reinforcement Learning

Author: Emil Carlsson; Devdatt Dubhashi; Fredrik Johansson

Published: 2021

Published in: Proceedings of the Annual Meeting of the Cognitive Science Society

Publication type: Paper in proceeding
Thompson Sampling for Bandits with Clustered Arms

Author: Emil Carlsson; Devdatt Dubhashi; Fredrik Johansson

Published: 2021

Published in: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence

Publication type: Paper in proceeding
AI futures

Author: Devdatt Dubhashi

Published: 2021

Published in: Communications of the ACM

Publication type: Other text in scientific journal
2020
Mathematical Models for COVID-19 Pandemic: A Comparative Analysis

Author: Aniruddha Adiga; Devdatt Dubhashi; Bryan Lewis; Madhav Marathe; Srinivasan Venkatramanan; Anil Vullikanti

Published: 2020

Published in: Journal of the Indian Institute of Science

Publication type: Review article
A reinforcement-learning approach to efficient communication

Author: Mikael Kågebäck; Emil Carlsson; Devdatt Dubhashi; Asad Sayeed

Published: 2020

Published in: PLoS ONE

Publication type: Journal article
Accelerated proximal incremental algorithm schemes for non-strongly convex functions

Author: Ashkan Panahi; Morteza Haghir Chehreghani; Devdatt Dubhashi

Published: 2020

Published in: Theoretical Computer Science

Publication type: Journal article
2019
A Non-Convex Optimization Approach to Correlation Clustering

Author: Erik Thiel; Morteza Haghir Chehreghani; Devdatt Dubhashi

Published: 2019

Published in: THIRTY-THIRD AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE / THIRTY-FIRST INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE / NINTH AAAI SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE

Publication type: Paper in proceeding
Bayesian optimization in ab initio nuclear physics

Author: Andreas Ekström; Christian Forssen; Christos Dimitrakakis; Devdatt Dubhashi; Håkan T Johansson; Muhammad Azam Sheikh; Hans Salomonsson; Alexander Schliep

Published: 2019

Published in: Journal of Physics G: Nuclear and Particle Physics

Publication type: Journal article
2018
DeepColor: Reinforcement Learning optimizes information efficiency and well-formedness in color name partitioning

Author: Mikael Kågebäck; Devdatt Dubhashi; Asad Sayeed

Published: 2018

Published in: Proceedings of the 40th Annual Meeting of the Cognitive Science Society (CogSci)

Publication type: Paper in proceeding
2017
Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery

Author: Ashkan Panahi; Devdatt Dubhashi; Fredrik Johansson; Chiranjib Bhattacharyya

Published: 2017

Published in: Proceedings of Machine Learning Research

Publication type: Paper in proceeding
Thompson Sampling for Stochastic Bandits with Graph Feedback

Author: Aristide Tossou; Christos Dimitrakakis; Devdatt Dubhashi

Published: 2017

Published in: 31st AAAI Conference on Artificial Intelligence, AAAI 2017, San Francisco, United States, 4-10 February 2017

Publication type: Paper in proceeding
AI Dangers: Imagined and Real

Author: Devdatt Dubhashi; Shalom Lappin

Published: 2017

Published in: Communications of the ACM

Publication type: Other text in scientific journal
2015
Weighted theta functions and embeddings with applications to Max-Cut, clustering and summarization

Author: Fredrik Johansson; A. Chattoraj; C. Bhattacharyya; Devdatt Dubhashi

Published: 2015

Published in: Advances in Neural Information Processing Systems

Publication type: Paper in proceeding
Visions and open challenges for a knowledge-based culturomics

Author: Nina Tahmasebi; Lars Borin; Gabriele Capannini; Devdatt Dubhashi; Peter Exner; Markus Forsberg; Gerhard Gossen; Fredrik Johansson; Richard Johansson; Mikael Kågebäck; Olof Mogren; Pierre Nugues; Thomas Risse

Published: 2015

Published in: International Journal on Digital Libraries

Publication type: Journal article
Classifying large graphs with differential privacy

Author: Fredrik Johansson; Otto Frost; Carl Thufvesson Retzner; Devdatt Dubhashi

Published: 2015

Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Publication type: Paper in proceeding
Learning with similarity functions on graphs using matchings of geometric embeddings

Author: Fredrik Johansson; Devdatt Dubhashi

Published: 2015

Published in: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Publication type: Paper in proceeding
Extractive summarization by aggregating multiple similarities

Author: Olof Mogren; Mikael Kågebäck; Devdatt Dubhashi

Published: 2015

Published in: International Conference Recent Advances in Natural Language Processing, RANLP

Publication type: Paper in proceeding
Neural context embeddings for automatic discovery of word senses

Author: Mikael Kågebäck; Fredrik Johansson; Richard Johansson; Devdatt Dubhashi

Published: 2015

Published in: Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing. Denver, United States

Publication type: Paper in proceeding
2014
Federated clouds for biomedical research: Integrating OpenStack for ICTBioMed

Author: C. Mazurek; J. Pukacki; M. Kosiedowski; S. Trocha; M. Sullivan; H. Darbari; A. Saxena; R.R. Joshi; Devdatt Dubhashi; S. Thankaswamy; P.R. Brenner; S. Gesing; J. Nabrzyski; A. Srivastava

Published: 2014

Published in: 2014 IEEE 3rd International Conference on Cloud Networking, CloudNet 2014

Publication type: Paper in proceeding

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Page manager Published: Wed 03 Jun 2020.

Devdatt Dubhashi

Latest publications

2022

2021

2020

2019

2018

2017

2015

2014

Projects

Closed