Devdatt Dubhashi

Professor på avdelningen för Data Science och AI, Institutionen för data- och informationsteknik.

dubhashi@chalmers.se +46317721046 Hitta till mig

Mina huvudintressen är inom design och analys av randomiserade algoritmer, maskininlärning för Big Data och beräkningsbiologi.

Publikationer
Samverkan och projekt

Senaste publikationer

2020
Mathematical Models for COVID-19 Pandemic: A Comparative Analysis

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

Publiceringsår: 2020

Publicerat i: Journal of the Indian Institute of Science

Publikationstyp: Reviewartikel
A reinforcement-learning approach to efficient communication

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

Publiceringsår: 2020

Publicerat i: PLoS ONE

Publikationstyp: Artikel i vetenskaplig tidskrift
Accelerated proximal incremental algorithm schemes for non-strongly convex functions

Författare: Ashkan Panahi; Morteza Haghir Chehreghani; Devdatt Dubhashi

Publiceringsår: 2020

Publicerat i: Theoretical Computer Science

Publikationstyp: Artikel i vetenskaplig tidskrift
2019
A Non-Convex Optimization Approach to Correlation Clustering

Författare: Erik Thiel; Morteza Haghir Chehreghani; Devdatt Dubhashi

Publiceringsår: 2019

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

Publikationstyp: Paper i proceeding
Bayesian optimization in ab initio nuclear physics

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

Publiceringsår: 2019

Publicerat i: Journal of Physics G: Nuclear and Particle Physics

Publikationstyp: Artikel i vetenskaplig tidskrift
2018
DeepColor: Reinforcement Learning optimizes information efficiency and well-formedness in color name partitioning

Författare: Mikael Kågebäck; Devdatt Dubhashi; Asad Sayeed

Publiceringsår: 2018

Publicerat i: Proceedings of the 40th Annual Meeting of the Cognitive Science Society (CogSci)

Publikationstyp: Paper i proceeding
2017
Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery

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

Publiceringsår: 2017

Publicerat i: Proceedings of Machine Learning Research

Publikationstyp: Paper i proceeding
Thompson Sampling for Stochastic Bandits with Graph Feedback

Författare: Aristide Tossou; Christos Dimitrakakis; Devdatt Dubhashi

Publiceringsår: 2017

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

Publikationstyp: Paper i proceeding
AI Dangers: Imagined and Real

Författare: Devdatt Dubhashi; Shalom Lappin

Publiceringsår: 2017

Publicerat i: Communications of the ACM

Publikationstyp: Artikel i vetenskaplig tidskrift
2015
Weighted theta functions and embeddings with applications to Max-Cut, clustering and summarization

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

Publiceringsår: 2015

Publicerat i: 29th Annual Conference on Neural Information Processing Systems, NIPS 2015, Montreal, Canada, 7-12 December

Publikationstyp: Konferensbidrag (offentliggjort, men ej förlagsutgivet)
Visions and open challenges for a knowledge-based culturomics

Författare: 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

Publiceringsår: 2015

Publicerat i: International Journal on Digital Libraries

Publikationstyp: Artikel i vetenskaplig tidskrift
Classifying large graphs with differential privacy

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

Publiceringsår: 2015

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

Publikationstyp: Paper i proceeding
Learning with similarity functions on graphs using matchings of geometric embeddings

Författare: Fredrik Johansson; Devdatt Dubhashi

Publiceringsår: 2015

Publicerat i: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Publikationstyp: Paper i proceeding
Extractive summarization by aggregating multiple similarities

Författare: Olof Mogren; Mikael Kågebäck; Devdatt Dubhashi

Publiceringsår: 2015

Publicerat i: International Conference Recent Advances in Natural Language Processing, RANLP

Publikationstyp: Paper i proceeding
Neural context embeddings for automatic discovery of word senses

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

Publiceringsår: 2015

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

Publikationstyp: Paper i proceeding
2014
Federated clouds for biomedical research: Integrating OpenStack for ICTBioMed

Författare: 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

Publiceringsår: 2014

Publicerat i: 2014 IEEE 3rd International Conference on Cloud Networking, CloudNet 2014

Publikationstyp: Paper i proceeding
Global graph kernels using geometric embeddings

Författare: Fredrik Johansson; Vinay Jethava; Devdatt Dubhashi; C. Bhattacharyya

Publiceringsår: 2014

Publicerat i: Proceedings of the 31st International Conference on Machine Learning, ICML 2014, Beijing, China, 21-26 June 2014

Publikationstyp: Paper i proceeding
Extractive Summarization using Continuous Vector Space Models

Författare: Mikael Kågebäck; Olof Mogren; Nina Tahmasebi; Devdatt Dubhashi

Publiceringsår: 2014

Publicerat i: Proceedings of the 2nd Workshop on Continuous Vector Space Models and their Compositionality (CVSC) EACL, April 26-30, 2014 Gothenburg, Sweden

Publikationstyp: Paper i proceeding
2013
Computational approaches for reconstruction of time-varying biological networks from omics data

Författare: Vinay Jethava; Chiranjib Bhattacharyya; Devdatt Dubhashi

Publiceringsår: 2013

Publicerat i: Systems Biology: Integrative Biology and Simulation Tools

Publikationstyp: Kapitel i bok
DLOREAN: Dynamic Location-aware Reconstruction of multiway Networks

Författare: Fredrik Johansson; Vinay Jethava; Devdatt Dubhashi

Publiceringsår: 2013

Publicerat i: 2013 13th IEEE International Conference on Data Mining Workshops, ICDMW 2013; Dallas, TX; United States; 7 December 2013 through 10 December 2013

Publikationstyp: Paper i proceeding
Mining semantics for culturomics: towards a knowledge-based approach

Författare: Lars Borin; Devdatt Dubhashi; Markus Forsberg; Richard Johansson; Dimitrios Kokkinakis; Pierre Nugues

Publiceringsår: 2013

Publicerat i: 2013 ACM International Workshop on Mining Unstructured Big Data Using Natural Language Processing, UnstructureNLP 2013, Held at 22nd ACM International Conference on Information and Knowledge Management, CIKM 2013; San Francisco, CA; United States; 28 October 2013 through 28 October 2013

Publikationstyp: Paper i proceeding
Entity disambiguation in anonymized graphs using graph kernels

Författare: Linus Hermansson; Tommi Kerola; Fredrik Johansson; Vinay Jethava; Devdatt Dubhashi

Publiceringsår: 2013

Publicerat i: 22nd ACM International Conference on Information and Knowledge Management, CIKM 2013; San Francisco, CA; United States; 27 October 2013 through 1 November 2013

Publikationstyp: Paper i proceeding
Lovasz theta function, SVMs and Finding Dense Subgraphs

Författare: Vinay Jethava; Anders Martinsson; C. Bhattacharyya; Devdatt Dubhashi

Publiceringsår: 2013

Publicerat i: Journal of Machine Learning Research

Publikationstyp: Artikel i vetenskaplig tidskrift
Lovasz θ, SVMs and applications

Författare: Vinay Jethava; Jacob Sznajdman; C. Bhattacharyya; Devdatt Dubhashi

Publiceringsår: 2013

Publicerat i: 2013 IEEE Information Theory Workshop - ITW 2013, Seville, Spain, 9-13 September 2013

Publikationstyp: Paper i proceeding
2012
The Lovász v function, SVMs and finding large dense subgraphs

Författare: Vinay Jethava; Anders Martinsson; C. Bhattacharyya; Devdatt Dubhashi

Publiceringsår: 2012

Publicerat i: 26th Annual Conference on Neural Information Processing Systems 2012, NIPS 2012, Lake Tahoe, United States, 3-6 December 2012

Publikationstyp: Paper i proceeding

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Sidansvarig Publicerad: on 03 jun 2020.

Devdatt Dubhashi

Senaste publikationer

2020

2019

2018

2017

2015

2014

2013

2012

Projekt

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