Devdatt P. Dubhashi

Affiliations:
  • Chalmers University of Technology, Department of Computer Science and Engineering


According to our database1, Devdatt P. Dubhashi authored at least 77 papers between 1992 and 2023.

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Bibliography

2023
Do Kernel and Neural Embeddings Help in Training and Generalization?
Neural Process. Lett., April, 2023

Pure Exploration in Bandits with Linear Constraints.
CoRR, 2023

Pragmatic Reasoning in Structured Signaling Games.
CoRR, 2023

Iterated learning and communication jointly explain efficient color naming systems.
CoRR, 2023

Recovery Bounds on Class-Based Optimal Transport: A Sum-of-Norms Regularization Framework.
Proceedings of the International Conference on Machine Learning, 2023

Random Features Model with General Convex Regularization: A Fine Grained Analysis with Precise Asymptotic Learning Curves.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Using satellites and artificial intelligence to measure health and material-living standards in India.
CoRR, 2022

Can universities combat the 'wrong kind of AI'?
Commun. ACM, 2022

Analysis of Knowledge Transfer in Kernel Regime.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
AI futures: fact and fantasy.
Commun. ACM, 2021

Thompson Sampling for Bandits with Clustered Arms.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Learning Approximate and Exact Numeral Systems via Reinforcement Learning.
Proceedings of the 43th Annual Meeting of the Cognitive Science Society, 2021

2020
Accelerated proximal incremental algorithm schemes for non-strongly convex functions.
Theor. Comput. Sci., 2020

Statistical modeling: the three cultures.
CoRR, 2020

Models for COVID-19 Pandemic: A Comparative Analysis.
CoRR, 2020

On the Unreasonable Effectiveness of Knowledge Distillation: Analysis in the Kernel Regime.
CoRR, 2020


2019
LEGaTO: Low-Energy, Secure, and Resilient Toolset for Heterogeneous Computing.
CoRR, 2019

Spectral Analysis of Kernel and Neural Embeddings: Optimization and Generalization.
CoRR, 2019

Stochastic Incremental Algorithms for Optimal Transport with SON Regularizer.
CoRR, 2019

Bayesian optimization in ab initio nuclear physics.
CoRR, 2019

A Non-Convex Optimization Approach to Correlation Clustering.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

DeepColor: Reinforcement Learning optimizes information efficiency and well-formedness in color name partitioning.
Proceedings of the 40th Annual Meeting of the Cognitive Science Society, 2018


Distributed Approximation Algorithms via LP-Duality and Randomization.
Proceedings of the Handbook of Approximation Algorithms and Metaheuristics, 2018

2017
GANs for LIFE: Generative Adversarial Networks for Likelihood Free Inference.
CoRR, 2017

AI dangers: imagined and real.
Commun. ACM, 2017

Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery.
Proceedings of the 34th International Conference on Machine Learning, 2017

Thompson Sampling for Stochastic Bandits with Graph Feedback.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Distributed Vertex Coloring.
Encyclopedia of Algorithms, 2016

2015
Visions and open challenges for a knowledge-based culturomics.
Int. J. Digit. Libr., 2015

Extractive Summarization by Aggregating Multiple Similarities.
Proceedings of the Recent Advances in Natural Language Processing, 2015

Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization.
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.
Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing, 2015

Classifying Large Graphs with Differential Privacy.
Proceedings of the Modeling Decisions for Artificial Intelligence, 2015

Learning with Similarity Functions on Graphs using Matchings of Geometric Embeddings.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014
Global graph kernels using geometric embeddings.
Proceedings of the 31th International Conference on Machine Learning, 2014

Federated clouds for biomedical research: Integrating OpenStack for ICTBioMed.
Proceedings of the 3rd IEEE International Conference on Cloud Networking, 2014

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

2013
Lovász ϑ function, SVMs and finding dense subgraphs.
J. Mach. Learn. Res., 2013

Lovasz ϑ, SVMs and applications.
Proceedings of the 2013 IEEE Information Theory Workshop, 2013

DLOREAN: Dynamic Location-Aware Reconstruction of Multiway Networks.
Proceedings of the 13th IEEE International Conference on Data Mining Workshops, 2013

Entity disambiguation in anonymized graphs using graph kernels.
Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 2013

Mining semantics for culturomics: towards a knowledge-based approach.
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".
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.
BMC Bioinform., 2011

Scalable multi-dimensional user intent identification using tree structured distributions.
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.
Cambridge University Press, ISBN: 978-0-521-88427-3, 2009

2008
Distributed Vertex Coloring.
Proceedings of the Encyclopedia of Algorithms - 2008 Edition, 2008

Adaptive Dynamics of Realistic Small-World Networks
CoRR, 2008

2007
Distributed Approximation Algorithms via LP-Duality and Randomization.
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.
Wirel. Networks, 2007

Probabilistic analysis for a multiple depot vehicle routing problem.
Random Struct. Algorithms, 2007

Positive Influence and Negative Dependence.
Comb. Probab. Comput., 2007

Localized Techniques for Broadcasting in Wireless Sensor Networks.
Algorithmica, 2007

2006
Bayesian classifiers for detecting HGT using fixed and variable order markov models of genomic signatures.
Bioinform., 2006

Randomization in Constraint Programming for Airline Planning.
Proceedings of the Principles and Practice of Constraint Programming, 2006

2005
Fast distributed algorithms for (weakly) connected dominating sets and linear-size skeletons.
J. Comput. Syst. Sci., 2005

The Peres-Shields Order Estimator for Fixed and Variable Length Markov Models with Applications to DNA Sequence Similarity.
Proceedings of the Algorithms in Bioinformatics, 5th International Workshop, 2005

Irrigating ad hoc networks in constant time.
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.
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.
Theor. Comput. Sci., 1998

Balls and bins: A study in negative dependence.
Random Struct. Algorithms, 1998

Talagrand's Inequality and Locality in Distributed Computing.
Proceedings of the Randomization and Approximation Techniques in Computer Science, 1998

Martingales and Locality in Distributed Computing.
Proceedings of the Foundations of Software Technology and Theoretical Computer Science, 1998

1997
Probabilistic Recurrence Relations Revisited.
Theor. Comput. Sci., 1997

Simple proofs of occupancy tail bounds.
Random Struct. Algorithms, 1997

Transforming Comparison Model Lower Bounds to the Parallel-Random-Access-Machine.
Inf. Process. Lett., 1997

1995
The Fourth Moment in Luby's Distribution.
Theor. Comput. Sci., 1995

(Probabilistic) Recurrence Realtions Revisited.
Proceedings of the LATIN '95: Theoretical Informatics, 1995

Near-Optimal Distributed Edge Coloring.
Proceedings of the Algorithms, 1995

1994
A Lower Bound for Area-Universal Graphs.
Inf. Process. Lett., 1994

1993
Quantifier Elimination in p-adic Fields.
Comput. J., 1993

Searching, Sorting and Randomised Algorithms for Central Elements and Ideal Counting in Posets.
Proceedings of the Foundations of Software Technology and Theoretical Computer Science, 1993

1992
Algorithmic Investigations In P-adic Fields.
PhD thesis, 1992

On Decidable Varieties of Heyting Algebras.
J. Symb. Log., 1992


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