On Decidable Varieties of Heyting Algebras. - Devdatt P. Dubhashi (J. Symb. Log., 1992)

Algorithmic Investigations In P-adic Fields. - Devdatt P. Dubhashi (1992)

Searching, Sorting and Randomised Algorithms for Central Elements and Ideal Counting in Posets. - Devdatt P. Dubhashi; Kurt Mehlhorn; Desh Ranjan; Christian Thiel 003 (FSTTCS, 1993)

Quantifier Elimination in p-adic Fields. - Devdatt P. Dubhashi (Comput. J., 1993)

A Lower Bound for Area-Universal Graphs. - Gianfranco Bilardi; Shiva Chaudhuri; Devdatt P. Dubhashi; Kurt Mehlhorn (Inf. Process. Lett., 1994)

Near-Optimal Distributed Edge Coloring. - Devdatt P. Dubhashi; Alessandro Panconesi (ESA, 1995)

(Probabilistic) Recurrence Realtions Revisited. - Shiva Chaudhuri; Devdatt P. Dubhashi (LATIN, 1995)

The Fourth Moment in Luby's Distribution. - Devdatt P. Dubhashi; Grammati E. Pantziou; Paul G. Spirakis; Christos D. Zaroliagis (Theor. Comput. Sci., 1995)

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)

Simple proofs of occupancy tail bounds. - Devdatt P. Dubhashi (Random Struct. Algorithms, 1997)

Probabilistic Recurrence Relations Revisited. - Shiva Chaudhuri; Devdatt P. Dubhashi (Theor. Comput. Sci., 1997)

Martingales and Locality in Distributed Computing. - Devdatt P. Dubhashi (FSTTCS, 1998)

Talagrand's Inequality and Locality in Distributed Computing. - Devdatt P. Dubhashi (RANDOM, 1998)

Balls and bins: A study in negative dependence. - Devdatt P. Dubhashi; Desh Ranjan (Random Struct. Algorithms, 1998)

Near-Optimal, Distributed Edge Colouring via the Nibble Method. - Devdatt P. Dubhashi; David A. Grable; Alessandro Panconesi (Theor. Comput. Sci., 1998)

Analysis and Experimental Evaluation of a Simple Algorithm for Collaborative Filtering in Planted Partition Models: Extended Abstract. - Devdatt P. Dubhashi; Luigi Laura; Alessandro Panconesi (FSTTCS, 2003)

Fast distributed algorithms for (weakly) connected dominating sets and linear-size skeletons. - Devdatt P. Dubhashi; Alessandro Mei; Alessandro Panconesi; Jaikumar Radhakrishnan; Aravind Srinivasan (SODA, 2003)

Probabilistic Analysis for a Multiple Depot Vehicle Routing Problem. - Andreas Baltz; Devdatt P. Dubhashi; Libertad Tansini; Anand Srivastav; Sören Werth (FSTTCS, 2005)

Irrigating ad hoc networks in constant time. - Devdatt P. Dubhashi; C. Johansson; Olle Häggström; Alessandro Panconesi; Mauro Sozio (SPAA, 2005)

The Peres-Shields Order Estimator for Fixed and Variable Length Markov Models with Applications to DNA Sequence Similarity. - Daniel Dalevi; Devdatt P. Dubhashi (WABI, 2005)

Randomization in Constraint Programming for Airline Planning. - Lars Otten; Mattias Grönkvist; Devdatt P. Dubhashi (CP, 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)

Localized Techniques for Broadcasting in Wireless Sensor Networks. - Devdatt P. Dubhashi; Olle Häggström; Lorenzo Orecchia; Alessandro Panconesi; Chiara Petrioli; Andrea Vitaletti (Algorithmica, 2007)

Positive Influence and Negative Dependence. - Devdatt P. Dubhashi; Johan Jonasson; Desh Ranjan (Comb. Probab. Comput., 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)

Distributed Approximation Algorithms via LP-Duality and Randomization. - Alessandro Panconesi; Fabrizio Grandoni 001; Devdatt P. Dubhashi (Handbook of Approximation Algorithms and Metaheuristics, 2007)

Adaptive Dynamics of Realistic Small-World Networks - Olof Mogren; Oskar Sandberg; Vilhelm Verendel; Devdatt P. Dubhashi (CoRR, 2008)

Distributed Vertex Coloring. - Devdatt P. Dubhashi (Encyclopedia of Algorithms, 2008)

Concentration of Measure for the Analysis of Randomized Algorithms. - Devdatt P. Dubhashi; Alessandro Panconesi (Cambridge University Press, 2009)

Scalable multi-dimensional user intent identification using tree structured distributions. - Vinay Jethava; Liliana Calderón-Benavides; Ricardo Baeza-Yates; Chiranjib Bhattacharyya; Devdatt P. Dubhashi (SIGIR, 2011)

NETGEM: Network Embedded Temporal GEnerative Model for gene expression data. - Vinay Jethava; Chiranjib Bhattacharyya; Devdatt P. Dubhashi; Goutham N. Vemuri (BMC Bioinform., 2011)

"The Lovasz $ theta$ function, SVMs and finding large dense subgraphs". - Vinay Jethava; Anders Martinsson; Chiranjib Bhattacharyya; Devdatt P. Dubhashi (NIPS, 2012)

Mining semantics for culturomics: towards a knowledge-based approach. - Lars Borin; Devdatt P. Dubhashi; Markus Forsberg; Richard Johansson; Dimitrios Kokkinakis; Pierre Nugues (UnstructureNLP@CIKM, 2013)

Entity disambiguation in anonymized graphs using graph kernels. - Linus Hermansson; Tommi Kerola; Fredrik Johansson 002; Vinay Jethava; Devdatt P. Dubhashi (CIKM, 2013)

DLOREAN: Dynamic Location-Aware Reconstruction of Multiway Networks. - Fredrik Johansson 002; Vinay Jethava; Devdatt P. Dubhashi (ICDM Workshops, 2013)

Lovasz ϑ, SVMs and applications. - Vinay Jethava; Jacob Sznajdman; Chiranjib Bhattacharyya; Devdatt P. Dubhashi (ITW, 2013)

Lovász ϑ function, SVMs and finding dense subgraphs. - Vinay Jethava; Anders Martinsson; Chiranjib Bhattacharyya; Devdatt P. Dubhashi (J. Mach. Learn. Res., 2013)

Extractive Summarization using Continuous Vector Space Models. - Mikael Kågebäck; Olof Mogren; Nina Tahmasebi; Devdatt P. Dubhashi (CVSC@EACL, 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; et al. (CloudNet, 2014)

Global graph kernels using geometric embeddings. - Fredrik D. Johansson; Vinay Jethava; Devdatt P. Dubhashi; Chiranjib Bhattacharyya (ICML, 2014)

Learning with Similarity Functions on Graphs using Matchings of Geometric Embeddings. - Fredrik D. Johansson; Devdatt P. Dubhashi (KDD, 2015)

Classifying Large Graphs with Differential Privacy. - Fredrik D. Johansson; Otto Frost; Carl Retzner; Devdatt P. Dubhashi (MDAI, 2015)

Neural context embeddings for automatic discovery of word senses. - Mikael Kågebäck; Fredrik D. Johansson; Richard Johansson; Devdatt P. Dubhashi (VS@HLT-NAACL, 2015)

Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization. - Fredrik D. Johansson; Ankani Chattoraj; Chiranjib Bhattacharyya; Devdatt P. Dubhashi (NIPS, 2015)

Extractive Summarization by Aggregating Multiple Similarities. - Olof Mogren; Mikael Kågebäck; Devdatt P. Dubhashi (RANLP, 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; et al. (Int. J. Digit. Libr., 2015)

Distributed Vertex Coloring. - Devdatt P. Dubhashi (Encyclopedia of Algorithms, 2016)

Thompson Sampling for Stochastic Bandits with Graph Feedback. - Aristide C. Y. Tossou; Christos Dimitrakakis; Devdatt P. Dubhashi (AAAI, 2017)

Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery. - Ashkan Panahi; Devdatt P. Dubhashi; Fredrik D. Johansson; Chiranjib Bhattacharyya (ICML, 2017)

AI dangers: imagined and real. - Devdatt P. Dubhashi; Shalom Lappin (Commun. ACM, 2017)

GANs for LIFE: Generative Adversarial Networks for Likelihood Free Inference. - Vinay Jethava; Devdatt P. Dubhashi (CoRR, 2017)

Distributed Approximation Algorithms via LP-Duality and Randomization. - Devdatt P. Dubhashi; Fabrizio Grandoni 001; Alessandro Panconesi (Handbook of Approximation Algorithms and Metaheuristics (1), 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 001; Behzad Salami 001; Sergi Madonar; Miquel Pericàs; Pedro Trancoso; et al. (CF, 2018)

DeepColor: Reinforcement Learning optimizes information efficiency and well-formedness in color name partitioning. - Mikael Kågebäck; Devdatt P. Dubhashi; Asad B. Sayeed (CogSci, 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 001; Behzad Salami 001; Sergi Madonar; Miquel Pericàs; Pedro Trancoso; et al. (SAMOS, 2018)

A Non-Convex Optimization Approach to Correlation Clustering. - Erik Thiel; Morteza Haghir Chehreghani; Devdatt P. Dubhashi (AAAI, 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)

Stochastic Incremental Algorithms for Optimal Transport with SON Regularizer. - Ashkan Panahi; Erik Thiel; Morteza Haghir Cheraghani; Devdatt P. Dubhashi (CoRR, 2019)

Spectral Analysis of Kernel and Neural Embeddings: Optimization and Generalization. - Emilio Jorge; Morteza Haghir Chehreghani; Devdatt P. Dubhashi (CoRR, 2019)

LEGaTO: Low-Energy, Secure, and Resilient Toolset for Heterogeneous Computing. - Behzad Salami 001; Konstantinos Parasyris; Adrián Cristal; Osman S. Unsal; Xavier Martorell; Paul Carpenter; Raúl de la Cruz; Leonardo Bautista-Gomez; Daniel A. Jiménez; Carlos Álvarez 001; S. Nabavi; Sergi Madonar; et al. (CoRR, 2019)

LEGaTO: Low-Energy, Secure, and Resilient Toolset for Heterogeneous Computing. - Behzad Salami 001; Konstantinos Parasyris; Adrián Cristal; Osman S. Unsal; Xavier Martorell; Paul Carpenter; Raúl de la Cruz; Leonardo Bautista-Gomez; Daniel A. Jiménez; Carlos Álvarez 001; Seyed Saber Nabavi Larimi; Sergi Madonar; et al. (DATE, 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)

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)

Statistical modeling: the three cultures. - Adel Daoud; Devdatt P. Dubhashi (CoRR, 2020)

Accelerated proximal incremental algorithm schemes for non-strongly convex functions. - Ashkan Panahi; Morteza Haghir Chehreghani; Devdatt P. Dubhashi (Theor. Comput. Sci., 2020)

Learning Approximate and Exact Numeral Systems via Reinforcement Learning. - Emil Carlsson; Devdatt P. Dubhashi; Fredrik D. Johansson (CogSci, 2021)

Thompson Sampling for Bandits with Clustered Arms. - Emil Carlsson; Devdatt P. Dubhashi; Fredrik D. Johansson (IJCAI, 2021)

AI futures: fact and fantasy. - Devdatt P. Dubhashi (Commun. ACM, 2021)

Analysis of Knowledge Transfer in Kernel Regime. - Ashkan Panahi; Arman Rahbar; Chiranjib Bhattacharyya; Devdatt P. Dubhashi; Morteza Haghir Chehreghani (CIKM, 2022)

Pragmatic Reasoning in Structured Signaling Games. - Emil Carlsson; Devdatt P. Dubhashi (CogSci, 2022)

Can universities combat the 'wrong kind of AI'? - Devdatt P. Dubhashi (Commun. ACM, 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)

Double Descent in Random Feature Models: Precise Asymptotic Analysis for General Convex Regularization. - David Bosch 002; Ashkan Panahi; Ayça Özçelikkale; Devdatt P. Dubhashi (CoRR, 2022)

Random Features Model with General Convex Regularization: A Fine Grained Analysis with Precise Asymptotic Learning Curves. - David Bosch 002; Ashkan Panahi; Ayça Özçelikkale; Devdatt P. Dubhashi (AISTATS, 2023)

Iterated learning and communication jointly explain efficient color naming systems. - Emil Carlsson; Devdatt P. Dubhashi; Terry Regier (CogSci, 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 (ICML, 2023)

Do Kernel and Neural Embeddings Help in Training and Generalization? - Arman Rahbar; Emilio Jorge; Devdatt P. Dubhashi; Morteza Haghir Chehreghani (Neural Process. Lett., 2023)

Pure Exploration in Bandits with Linear Constraints. - Emil Carlsson; Debabrota Basu; Fredrik D. Johansson; Devdatt P. Dubhashi (AISTATS, 2024)

Active preference learning for ordering items in- and out-of-sample. - Herman Bergström; Emil Carlsson; Devdatt P. Dubhashi; Fredrik D. Johansson (NeurIPS, 2024)

Predicting Ground State Properties: Constant Sample Complexity and Deep Learning Algorithms. - Marc Wanner; Laura Lewis; Chiranjib Bhattacharyya; Devdatt P. Dubhashi; Alexandru Gheorghiu (NeurIPS, 2024)

Learning Efficient Recursive Numeral Systems via Reinforcement Learning. - Jonathan D. Thomas; Andrea Silvi; Devdatt P. Dubhashi; Emil Carlsson; Moa Johansson 001 (CoRR, 2024)

ACE: Abstractions for Communicating Efficiently. - Jonathan D. Thomas; Andrea Silvi; Devdatt P. Dubhashi; Vikas Garg 001; Moa Johansson 001 (CoRR, 2024)

Variational Quantum Optimization with Continuous Bandits. - Marc Wanner; Johan Jonasson; Emil Carlsson; Devdatt P. Dubhashi (CoRR, 2025)

Recursive numeral systems are highly regular and easy to process. - Ponrawee Prasertsom; Andrea Silvi; Jennifer Culbertson; Moa Johansson 001; Devdatt P. Dubhashi; Kenny Smith (CoRR, 2025)