Devdatt Dubhashi
13 papers · 2012–2026 · 7 venues · across top CS/AI venues
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Achievements
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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Half 🌉 Interdisciplinary Bridge · Gold 🗺️ Taxonomy Completionist (32)
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Keyword Collector
(72)
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Trend Setter
💎
Century Club · Bronze
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Conference Pioneer
🌈
Renaissance Researcher
(5)
Top co-authors
Research topics
Machine Learning
(12)
Mathematics & Optimization
(9)
Core Methods
(9)
Optimization
(7)
Optimization & Theory
(6)
Mathematics
(4)
Learning Types
(2)
Artificial Intelligence
(1)
Data Science & Analytics
(1)
Deep Learning
(1)
Interdisciplinary
(1)
Natural Language Processing
(1)
Application Areas
(1)
Applications
(1)
Architectures
(1)
Keywords
correlation clustering
(2)
convex optimization
(2)
multiple kernel learning
(2)
support vector machine
(2)
graph theory
(2)
combinatorial optimization
(2)
lovasz theta function
(2)
proximal algorithm
(2)
semidefinite programming
(2)
multi-armed bandit
(2)
asymptotic analysis
(1)
kernel learning
(1)
sample complexity
(1)
convex relaxation
(1)
sample efficiency
(1)
document summarization
(1)
optimal transport
(1)
variance reduction
(1)
regularized regression
(1)
epistemic uncertainty
(1)
Papers
Recursive numeral systems are highly regular and easy to process
EACL 2026
Active preference learning for ordering items in- and out-of-sample
NeurIPS 2024
Predicting Ground State Properties: Constant Sample Complexity and Deep Learning Algorithms
NeurIPS 2024
Pure Exploration in Bandits with Linear Constraints
AISTATS 2024
Random Features Model with General Convex Regularization: A Fine Grained Analysis with Precise Asymptotic Learning Curves
AISTATS 2023
Recovery Bounds on Class-Based Optimal Transport: A Sum-of-Norms Regularization Framework
ICML 2023
Thompson Sampling for Bandits with Clustered Arms
IJCAI 2021
A Non–Convex Optimization Approach to Correlation Clustering
AAAI 2019
Clustering by Sum of Norms: Stochastic Incremental Algorithm, Convergence and Cluster Recovery
ICML 2017
Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization
NeurIPS 2015
Global graph kernels using geometric embeddings
ICML 2014
Lovasz theta function, SVMs and Finding Dense Subgraphs
JMLR 2013
The Lovász ϑ function, SVMs and finding large dense subgraphs
NeurIPS 2012